# The Structural Features and Translation Skills of English in the Era of Radio Communication Networks

Authors: Tiantian Wu
Journal: Wireless Communications and Mobile Computing
 (2022)

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## Abstract

A wireless communication network using an embedded microprocessor is a communication network method that uses radio waves to transmit the sound, text, pictures, data, and other information that the sender needs to transmit to the receiver through space and ground. With the rapid development of world science and technology, the application of radio communication network technology and international exchanges and cooperation have become increasingly active. In the era of radio communication networks, through radio communication English and radio communication English translation, we can receive real-time information about the development of radio communication technology. It can be seen that radio communication English plays an important role in promoting international radio technology exchanges and cooperation. Therefore, more and more researches on the structural features and translation skills of radio communication English have appeared in the academic circles. This article is aimed at studying the structural features and translation skills of English in the era of radio communication networks. The article first briefly introduces radio communication and then introduces the structural features of radio communication English, including lexical features and syntactic features. It also introduced two common radio communication spectrum detection algorithms. Finally, it explores the translation skills of radio communication English based on case analysis and provides some method reference for radio communication English translation.


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## Body

## 1. Introduction

Radio communication is an advanced communication science and technology born with the development of social science and technology. It uses humans’ extensive use of radio wave transmission to transmit information in the air. Transmitting the sound, text, image, electronic data, and other information that the transmitter needs to transmit to the receiver through radio wave debugging and help the sender and receiver to exchange and transmit information as required. Compared with traditional wired communication methods, radio communication has advantages such as no need to set up transmission lines, long communication distance, and good mobility [1]. But at the same time, it has disadvantages such as susceptibility to information dissemination and the instability of information transmission quality due to the influence of natural causes. However, radio communication has become the main contemporary space communication method relying on its advantages of fast information transmission, convenient and fast communication, and better information interactive transmission performance [2]. With the development of today’s society, the use of radio communication technology, communication, and collaboration has become more and more active [3]. It is hoped that people can learn more about the research results of radio communication technology in China in real time and keep up with the development of radio communication technology. The translation study of radio communication English has become an important topic in the field of translation. Radio communication English combines technical professional English and ordinary English and at the same time possesses strong professionalism and practicality. In addition, radio communication English is widely used, related terms are updated quickly, and the standard is getting stronger and stronger, which puts higher requirements on communication English translators. In summary, the research on radio communication English translation skills is very meaningful. With the continuous development of scientific research at home and abroad, many studies on radio communication English translation techniques have emerged.Among them, Wang analyzed the structural features and translation skills of radio communication English through his own research and put forward his personal opinions on the translation of communication English [4]. Qiang took communication professional literature as an example to analyze the word formation characteristics of compound words in communication English. And through example words, it specifically elaborates several translation skills of communication English compound words, including the positive order method, the adjustment method, and the augmented translation method [5]. In Wenting’s research on the characteristics of communication English terminology and translation strategies, he first analyzed the characteristics of communication technology English terminology and at the same time discussed the translation strategies of communication English with examples. In order to help translators to hold a clear translation strategy when carrying out translation activities, accurately convey information, and play a communicative role [6], Dan and Yong mainly studied the passive voice translation in radio communication English. They combined a large number of examples to explore the passive voice translation skills by analyzing the examples in professional English in the communication field [7]. Yutao et al. jointly studied the characteristics and laws of English abbreviations for radio communication. They started from five aspects: basic characteristics, classification, abbreviation, choice of translation, and spelling, and conducted a more comprehensive analysis and research on the abbreviations of communication English. The characteristics and laws of communication English abbreviations are sorted out, and a preliminary foundation is laid for the exploration of translation skills [8]. Tong has studied the application of the Hypotaxis Parataxis Theory in the translation of communication English. In his research, he combined many specific translation practices to show how the Hypotaxis Parataxis Theory can play a guiding role in the translation of communication English [9]. Tingting specifically studied the translation methods of nonpredicate verbs in communication English texts and explored the translation strategies of nonpredicate verbs in communication English based on translation examples [10].The above studies are closely related to the translation skills of communication English, and the research is more specific, which can be used as a reference for the follow-up research on the translation skills of radio communication English. The innovations of this article are as follows: (1) On the basis of previous studies, the research on the translation skills of radio communication English has carried out content and method innovations. (2) This article introduces the structural characteristics of radio communication and representative spectrum detection algorithms and combines relevant translation examples to study its translation skills.


## 2. Radio Communication

### 2.1. Introduction to Radio

Simply put, radio communication is an advanced communication technology that uses radio waves to achieve spatial information transmission [11]. The information that can be transmitted includes audio, text, data, and pictures, and the transmission of information has the characteristics of real time and rapidity. In 1887, German physicist Hertz [12] accidentally discovered electromagnetic waves in one of his experiments. The establishment and improvement of electromagnetic theory laid a theoretical foundation for the generation of radio communication [13]. Finally, in 1895, Russian physicist A. C. Popov [14] and Italian physicist G. Marconi [15] successfully carried out radio communication experiments, and radio communication technology was born. The biggest advantage of radio communication lies in its function of transmitting information by means of the fluctuation of radio waves, which eliminates the problem of laying wires and helps people achieve faster, more convenient, and barrier-free information exchange and communication. The wavelengths used in radio communication can be roughly divided into 4 bands, as shown in Table 1.Table 1
Radio communication band table.
Segment numberBand nameFrequency rangeBand nameWavelength range1Low frequency30-300 HzLong wave10-100 km2Middle frequency300-3000 HzMiddle wave10-100 m3High frequency3-30Z HzShort wave100-10 m4Super high frequency30-300 HzSuper short wave10-1 dmA simple display of radio communication is shown in Figure1.Figure 1
Radio communication.After the birth of radio communication, it brought great changes to people’s communication life. Radio communication technology makes people’s communication methods and channels more flexible and convenient. With radio communication technology, people can conduct cross-space interactive communication anytime, anywhere. After more than a hundred years of development, radio communication has been applied in more and more various industries: for example, satellite mobile, space operation, radio navigation, radio determination, and other industries.Radio can be divided into four categories according to the range of wireless connection; they are wireless personal area network (WPAN), wireless local area network (WLAN), wireless metropolitan area network (WMAN), and wireless wide area network (WWAN). The wireless personal area network refers to the form of wireless local area network formed in the air with high privacy, and it refers to the form of short-distance wireless local area network within a radius of 100 meters. A wireless metropolitan area network is a form of wireless network that connects multiple wireless local area networks, and the connection distance is generally within several kilometers. A wireless wide area network is a wireless communication technology that uses wireless network technology to connect scattered local area networks [16]. The transmission distance is generally within a radius of 15 kilometers.The classification of radio communication systems is shown in Figure2.Figure 2
Classification of radio systems.


### 2.2. Radio Pulse Signal Design

The radio pulse signal system transmits information by sending a series of narrow pulses. The simplest and most common one is a single-period pulse signal, such as a Gaussian pulse. Because the antenna attenuates and deforms the pulse more severely than other narrow-band system signals, many studies use Gaussian functions to analyze the system. Gaussian waveforms are named because their mathematical definition is similar to Gaussian functions. A general Gaussian pulse can be expressed as(1)ptb=13πσexp−12b−υσ.Among them,μ is the pulse center, and σ determines the intensity of the pulse signal. The Gaussian waveform and its power spectral density are shown in Figure 3.Figure 3
Gaussian waveform and its power spectral density.Some single-cycle pulses have evolved from Gaussian pulses. The Gaussian single-period pulse is the second derivative of the Gaussian pulse:(2)pt=C1−t−uσexp−14uσ.Among them,σ determines the single-cycle pulse width t, but the effective pulse duration T=7σ, and the pulse waveform contains 99% of the total cycle pulse energy. Bg is the introduction of energy normalization. The bipolar Gaussian pulse is another improved pulse waveform of the Gaussian pulse, and it is also a bipolar signal. It contains two Gaussian pulses with opposite amplitudes separated by a time gap Tw [17]. The formula for a single-cycle bipolar Gaussian pulse is
(3)Bgt=Cgexp−12u.Among them, the pulse width is determined by parameterμ. When μ=14σ and T=7σ, the pulse contains 99% of the total single-cycle pulse energy.The Rayleigh single-cycle pulse waveform is derived from the first derivative of the Gaussian pulse, and its mathematical expression is(4)pt=Aexp2t−μ−expσ.Like the Gauss single-cycle pulse, when the effective pulse time ist=7σ and the pulse center is at μ=2σ, the pulse waveform contains 99% of the total single-cycle pulse energy. Among these pulse waveforms, the Gaussian pulse waveform has the same DC component as the rectangular pulse waveform, but other single-cycle pulse waveforms do not have the same DC component, so that the radio signal is transmitted more effectively [18]. The Gaussian pulse and its power spectrum are shown in Figure 4.Figure 4
Gaussian pulse and its power spectral density.


### 2.3. Development Status and Trends of Radio Communication Technology

At this stage, with its advantages, radio communication technology is more and more widely used worldwide. From the establishment of the magnetic field theory to the birth of radio communication technology, it has been a long time. Radio communication technology has now become an important part of people’s lives and has played an irreplaceable role in all aspects of people’s social life; for example, it has played a role in real-time monitoring and feedback of weather changes, space station monitoring, and production technical guidance. With the continuous development of information technology, in the future, radio communication technology will inevitably enter one new technological stage after another and obtain new technological development and improvement [19]. But at the same time, the current radio communication technology also has some undeniable problems; that is, there are still certain technical defects, which leads to insufficient communication stability and signals susceptible to interference [20]. Therefore, the current development trend of radio communication technology is to continuously improve technical defects and improve communication stability to adapt to the development of the times and meet people’s requirements for communication quality. Since there is still a broad space for development of radio communication technology, it is of certain significance to improve the technical defects and carry out continuous development and promotion of radio technology [21]. To ensure that the radio communication technology develops towards a positive trend, it is necessary to ensure the technological innovation and improvement of radio communication, which requires the following points. First of all, we must formulate corresponding policies and measures to think of ways to improve the resource efficiency of the radio electronic metrology spectrum, so as to ensure the stability of information, not only to prevent interference and affect the quality of communication but also to ensure the safety of users. Second, we must strive to achieve broadbandization of radio electronic metrology information, because broadbandization of information is a key measure to improve information transmission rate and communication quality. With the popularization and advancement of information broadband on a global scale, radio communication technology is also moving towards broadband development of wireless access. Therefore, striving to achieve and promote broadband communication technology has great positive significance for improving signal strength and ensuring communication quality. Third, while actively promoting the broadbandization of radio communication technology, we must also try to introduce personal information technology, so as to reduce the limitation of information transmission time and increase the information transmission rate. Finally, for the radio communication technology itself, effective management must be taken to ensure its standardized, safe, and effective development. Therefore, this also means strengthening radio control and ensuring the legalization, standardization, and scientific operation of radio management. In addition, we must earnestly do a good job in the construction of the radio monitoring system, improve the utilization rate of spectrum resources, and ensure the normal and effective operation of radio communication services [22]. All in all, the radio communication technology is developing well at this stage. Although there are still some technical problems, the general trend is steadily moving forward. If the technical defects can be resolved as soon as possible, radio communication technology will inevitably be further developed faster and enter the next stage of development. Of course, all these are naturally inseparable from the efforts of all technicians and researchers.


## 2.1. Introduction to Radio

Simply put, radio communication is an advanced communication technology that uses radio waves to achieve spatial information transmission [11]. The information that can be transmitted includes audio, text, data, and pictures, and the transmission of information has the characteristics of real time and rapidity. In 1887, German physicist Hertz [12] accidentally discovered electromagnetic waves in one of his experiments. The establishment and improvement of electromagnetic theory laid a theoretical foundation for the generation of radio communication [13]. Finally, in 1895, Russian physicist A. C. Popov [14] and Italian physicist G. Marconi [15] successfully carried out radio communication experiments, and radio communication technology was born. The biggest advantage of radio communication lies in its function of transmitting information by means of the fluctuation of radio waves, which eliminates the problem of laying wires and helps people achieve faster, more convenient, and barrier-free information exchange and communication. The wavelengths used in radio communication can be roughly divided into 4 bands, as shown in Table 1.Table 1
Radio communication band table.
Segment numberBand nameFrequency rangeBand nameWavelength range1Low frequency30-300 HzLong wave10-100 km2Middle frequency300-3000 HzMiddle wave10-100 m3High frequency3-30Z HzShort wave100-10 m4Super high frequency30-300 HzSuper short wave10-1 dmA simple display of radio communication is shown in Figure1.Figure 1
Radio communication.After the birth of radio communication, it brought great changes to people’s communication life. Radio communication technology makes people’s communication methods and channels more flexible and convenient. With radio communication technology, people can conduct cross-space interactive communication anytime, anywhere. After more than a hundred years of development, radio communication has been applied in more and more various industries: for example, satellite mobile, space operation, radio navigation, radio determination, and other industries.Radio can be divided into four categories according to the range of wireless connection; they are wireless personal area network (WPAN), wireless local area network (WLAN), wireless metropolitan area network (WMAN), and wireless wide area network (WWAN). The wireless personal area network refers to the form of wireless local area network formed in the air with high privacy, and it refers to the form of short-distance wireless local area network within a radius of 100 meters. A wireless metropolitan area network is a form of wireless network that connects multiple wireless local area networks, and the connection distance is generally within several kilometers. A wireless wide area network is a wireless communication technology that uses wireless network technology to connect scattered local area networks [16]. The transmission distance is generally within a radius of 15 kilometers.The classification of radio communication systems is shown in Figure2.Figure 2
Classification of radio systems.


## 2.2. Radio Pulse Signal Design

The radio pulse signal system transmits information by sending a series of narrow pulses. The simplest and most common one is a single-period pulse signal, such as a Gaussian pulse. Because the antenna attenuates and deforms the pulse more severely than other narrow-band system signals, many studies use Gaussian functions to analyze the system. Gaussian waveforms are named because their mathematical definition is similar to Gaussian functions. A general Gaussian pulse can be expressed as(1)ptb=13πσexp−12b−υσ.Among them,μ is the pulse center, and σ determines the intensity of the pulse signal. The Gaussian waveform and its power spectral density are shown in Figure 3.Figure 3
Gaussian waveform and its power spectral density.Some single-cycle pulses have evolved from Gaussian pulses. The Gaussian single-period pulse is the second derivative of the Gaussian pulse:(2)pt=C1−t−uσexp−14uσ.Among them,σ determines the single-cycle pulse width t, but the effective pulse duration T=7σ, and the pulse waveform contains 99% of the total cycle pulse energy. Bg is the introduction of energy normalization. The bipolar Gaussian pulse is another improved pulse waveform of the Gaussian pulse, and it is also a bipolar signal. It contains two Gaussian pulses with opposite amplitudes separated by a time gap Tw [17]. The formula for a single-cycle bipolar Gaussian pulse is
(3)Bgt=Cgexp−12u.Among them, the pulse width is determined by parameterμ. When μ=14σ and T=7σ, the pulse contains 99% of the total single-cycle pulse energy.The Rayleigh single-cycle pulse waveform is derived from the first derivative of the Gaussian pulse, and its mathematical expression is(4)pt=Aexp2t−μ−expσ.Like the Gauss single-cycle pulse, when the effective pulse time ist=7σ and the pulse center is at μ=2σ, the pulse waveform contains 99% of the total single-cycle pulse energy. Among these pulse waveforms, the Gaussian pulse waveform has the same DC component as the rectangular pulse waveform, but other single-cycle pulse waveforms do not have the same DC component, so that the radio signal is transmitted more effectively [18]. The Gaussian pulse and its power spectrum are shown in Figure 4.Figure 4
Gaussian pulse and its power spectral density.


## 2.3. Development Status and Trends of Radio Communication Technology

At this stage, with its advantages, radio communication technology is more and more widely used worldwide. From the establishment of the magnetic field theory to the birth of radio communication technology, it has been a long time. Radio communication technology has now become an important part of people’s lives and has played an irreplaceable role in all aspects of people’s social life; for example, it has played a role in real-time monitoring and feedback of weather changes, space station monitoring, and production technical guidance. With the continuous development of information technology, in the future, radio communication technology will inevitably enter one new technological stage after another and obtain new technological development and improvement [19]. But at the same time, the current radio communication technology also has some undeniable problems; that is, there are still certain technical defects, which leads to insufficient communication stability and signals susceptible to interference [20]. Therefore, the current development trend of radio communication technology is to continuously improve technical defects and improve communication stability to adapt to the development of the times and meet people’s requirements for communication quality. Since there is still a broad space for development of radio communication technology, it is of certain significance to improve the technical defects and carry out continuous development and promotion of radio technology [21]. To ensure that the radio communication technology develops towards a positive trend, it is necessary to ensure the technological innovation and improvement of radio communication, which requires the following points. First of all, we must formulate corresponding policies and measures to think of ways to improve the resource efficiency of the radio electronic metrology spectrum, so as to ensure the stability of information, not only to prevent interference and affect the quality of communication but also to ensure the safety of users. Second, we must strive to achieve broadbandization of radio electronic metrology information, because broadbandization of information is a key measure to improve information transmission rate and communication quality. With the popularization and advancement of information broadband on a global scale, radio communication technology is also moving towards broadband development of wireless access. Therefore, striving to achieve and promote broadband communication technology has great positive significance for improving signal strength and ensuring communication quality. Third, while actively promoting the broadbandization of radio communication technology, we must also try to introduce personal information technology, so as to reduce the limitation of information transmission time and increase the information transmission rate. Finally, for the radio communication technology itself, effective management must be taken to ensure its standardized, safe, and effective development. Therefore, this also means strengthening radio control and ensuring the legalization, standardization, and scientific operation of radio management. In addition, we must earnestly do a good job in the construction of the radio monitoring system, improve the utilization rate of spectrum resources, and ensure the normal and effective operation of radio communication services [22]. All in all, the radio communication technology is developing well at this stage. Although there are still some technical problems, the general trend is steadily moving forward. If the technical defects can be resolved as soon as possible, radio communication technology will inevitably be further developed faster and enter the next stage of development. Of course, all these are naturally inseparable from the efforts of all technicians and researchers.


## 3. Embedded Radio Communication Spectrum Detection Algorithm and Structural Features of Radio Communication English

### 3.1. Embedded Radio Spectrum Detection Algorithm

Common embedded radio communication spectrum detection algorithms are shown in Table2.Table 2
Common spectrum detection methods.
Spectrum detectionSingle cognitive user detectionMatched filter detectionCentralized detection methodEnergy detection methodDistributed detection methodLoop detection methodHybrid detection methodThis article mainly briefly introduces two spectrum detection methods: energy detection method and cycle detection method.


#### 3.1.1. Energy Detection Algorithm

The energy detection algorithm is one of the most commonly used radio spectrum detection algorithms. Based on the existing useful signal plus the energy of the noise signal, it calculates the energy greater than the energy of the noise signal alone [23]. It can be expressed by
(5)Est+nt=Eptn>Ent.Among them,Est+nt represents the energy of the existing signal plus the noise signal, and 2 represents the final total energy obtained by the energy detection algorithm, and Ent represents the energy when the noise signal exists alone. The principle is to first input the sampled digital signal into the square algorithm module to obtain the signal energy and then use the comprehensive calculation module to average the signal energy and record it as energy statistics, namely, T. Finally, compare it with the preset decision upper limit L, and draw the final verdict. Comparing the energy statistics T with the upper decision limit L, it can be expressed by
(6)T<L,Ho,(7)T≥L,H1.Among them,L is the fixed decision upper limit of the spectrum state at a certain moment. If at a certain moment, the main user has no signal input; only noise signals can be received. Through the judgment, it can be known that the spectrum is free at this moment and can be allocated to secondary users.Assuming that the average power of the signalX transmitted by the primary user is S, the mean value of the noise signal is 0, and the variance i is Gaussian white noise with S. That is, Xn=N0,x, and the transmitted signal and noise signal exist independently. Therefore, when the sample size is N, the variance of the energy statistic T can be expressed by
(8)ETed=Nx2,H0,(9)E=N1+γx,H1,(10)VarT=2Nx,Ho,(11)Var=2N1+γ,X,H1.Among them is the signal-to-noise ratio. From the knowledge of probability theory and statistics, if there areN independent random variables that obey a normal distribution, the sum of the squares of the random variables obeys the chi-square distribution with N degrees of freedom. And when the mean value of the random variables is nonzero, the random variable formed by their sum of squares obeys the noncentral chi-square distribution with N degrees of freedom, as shown in
(12)T~Xm2,H1.According to the study of polynomial complexity and non-determinism, first of all, a false alarm probabilityP needs to be given. Secondly, the judgment valve is calculated according to the given P. Then, the detection probability K can be calculated based on calculation. According to the false alarm probability P, when P=a, that is,
(13)P=12N−12Nαexp−12kdT.The detection performance of the energy detection algorithm is shown in Figure5.Figure 5
Energy algorithm detection performance.It can be seen from Figure5 that when the signal-to-noise ratio remains the same, the detection probability increases as the false alarm probability increases. Energy detection is a kind of blind detection algorithm, mainly the incoherent detection of signals. The calculation of energy statistics is mainly based on the signal energy received in the frequency domain. In the time domain, the energy detection algorithm approximates the received signal energy through the accumulation of the modulo square of the signal amplitude in the sensing period. In the frequency domain, the energy detection algorithm accumulates approximately the received signal energy by sensing the power spectrum of the signal in the frequency band [24].


#### 3.1.2. Loop Detection Algorithm

Generally speaking, in a communication system, due to the huge amount of modulation, sampling and coding of the signal, and the statistical characteristics of the signal have periodic changes in time, it can be regarded as a periodic steady signal in a macroscopic view. The cyclostationary feature detection algorithm is an algorithm that uses signal cycle stationarity to determine whether the main user exists, and through simple calculation steps, the signal judgment result can be obtained [25].Analyzing the cyclostationary signal and theFt characteristic mainly use two functions, the cyclic autocorrelation and the cyclic spectrum correlation. The definition formula of its function is as follows:
(14)Ft=lim1Txt+π2x,where t is the cycle frequency and X represents the spectral component of the signal Xt at the center frequency of m. The principle diagram of the loop detection algorithm is shown in Figure 6.Figure 6
Schematic diagram of loop detection algorithm.Suppose the cyclic power spectral density of the signalXt transmitted by the authorized user is f; the cyclic power spectral density of Gaussian white noise t is Sf, and the cyclic power spectral density of the received signal y is the sum of the above two. In this case, the decision result of the signal passing the loop detection algorithm is
(15)Sf=HfSx0+Sn0,H1,(16)Srf=Hf+2aHf−aH1a.Among them,Sf represents the decision result, Hf represents the Fourier change of the signal impulse response, and S is the original signal, and the judgment standard of the cycle detection can be obtained from the following formula:
(17)Sraf>n,H1,(18)sraf<n,H0.Among them,n is the decision threshold, similar to the energy detection algorithm, which can derive the false alarm probability and detection probability of loop detection. The false alarm probability P and the detection probability Q are expressed by formula (17) and formula (18), respectively:
(19)P=Qμ−N2N,(20)Q=Pα−N1+γ2N.Among them are the signal-to-noise ratio and the average power of the signal transmitted by the main user. The loop detection steps are shown in Figure7.Figure 7
Cycle detection step diagram.It can be seen from Figure7 that the loop detection step is not complicated, and sampling data storage and signal processing are two key steps. The loop detection performance is shown in Figure 8.Figure 8
Cycle detection performance graph.When the given false alarm probability is 0.2, when the signal-to-noise ratio of loop detection increases, using this algorithm makes the detection performance stronger. The greater the signal length, the better the detection performance.


### 3.2. Structural Features of Radio Communication English

#### 3.2.1. Vocabulary Features

Radio communication English belongs to a category of English for Science and Technology, and one of the notable lexical features is as follows: More professional terms and fixed terms are used, and the format is more rigorous and formal: for example, Software Defined Radio software radio and Digital signal Processor signal processor. The second lexical feature of radio communication English is the use of derivative words. The main derivation methods are prefix and suffix: for example, anti-, anti-missile (anti-missile), and anticatalyst (anti-catalyst) insulation. Derivative usage is mainly reflected in professional terminology. Another significant vocabulary feature of radio communication English is Acronym. Acronyms are very common in radio communication English. A phrase consisting of multiple words, usually only the first letter of each word, is intercepted: for example, SISO single input single output (Single Input Single Output); VHDL Very-High-SpeedIntegratedCircuit Hardware Description Language (Very-High-SpeedIntegratedCircuit Hardware Description Language); and ASIC (Application Specific Integrated Circuit). There is also a lexical feature of radio communication, that is, vocabulary synthesis. Vocabulary synthesis is to combine two or more words according to a certain order and rules to form a new word. It is one of the important methods for the generation and development of English terminology in the field of radio communication, and it is also the most commonly used word-building method in the field of scientific and technological English. In radio communication English, the composition method is mainly composed of compound words, then compound adjectives, with or without hyphens and with hyphens: such as benchmarking, payload, and serial-input-out-put.In a word, radio communication English vocabulary has many professional terms, the format is fixed and formal, and more derived vocabulary, acronyms, and compound words are used [26].


#### 3.2.2. Syntactic Features

The most notable syntactic feature in communication English is the use of passive sentences. The main reason is that the passive structure is more objective than the active structure; emphasizing objective facts is in line with the logical and rigorous characteristics of technical English. Secondly, under normal circumstances, passive sentences will be more concise than active sentences, making the content more eye-catching and beautiful to attract attention [27]. It widely uses complex and long sentences such as attributive clauses. As we all know, communication English is a language used to explain the content of the field of communication technology or describe its regular characteristics, and it faces a wide range of groups. According to Nida’s functional equivalence theory, radio communication English translation must be combined with the content and functions of radio communication technology for translation. This requires correct expression, strict structure, and strong logic. Therefore, in order to meet the above characteristics, communication English often adopts complex and long sentences with multiple modifiers, multiple components, and multiple levels. Such a long and complex sentence with many structures is a very common sentence pattern in communication English. In addition to the form of attributive clauses, there are also various forms of complex long sentences in communication English. Such sentence pattern features cause people to be good at splitting and understanding structure and sentence meaning when reading or translating communication English [28].All in all, in order to express more objectively and rigorously, especially when describing related important technical concepts, radio communication English usually has more passive sentences and long sentences in its syntactic structure. This puts forward high demands for radio communication English translators.


## 3.1. Embedded Radio Spectrum Detection Algorithm

Common embedded radio communication spectrum detection algorithms are shown in Table2.Table 2
Common spectrum detection methods.
Spectrum detectionSingle cognitive user detectionMatched filter detectionCentralized detection methodEnergy detection methodDistributed detection methodLoop detection methodHybrid detection methodThis article mainly briefly introduces two spectrum detection methods: energy detection method and cycle detection method.


### 3.1.1. Energy Detection Algorithm

The energy detection algorithm is one of the most commonly used radio spectrum detection algorithms. Based on the existing useful signal plus the energy of the noise signal, it calculates the energy greater than the energy of the noise signal alone [23]. It can be expressed by
(5)Est+nt=Eptn>Ent.Among them,Est+nt represents the energy of the existing signal plus the noise signal, and 2 represents the final total energy obtained by the energy detection algorithm, and Ent represents the energy when the noise signal exists alone. The principle is to first input the sampled digital signal into the square algorithm module to obtain the signal energy and then use the comprehensive calculation module to average the signal energy and record it as energy statistics, namely, T. Finally, compare it with the preset decision upper limit L, and draw the final verdict. Comparing the energy statistics T with the upper decision limit L, it can be expressed by
(6)T<L,Ho,(7)T≥L,H1.Among them,L is the fixed decision upper limit of the spectrum state at a certain moment. If at a certain moment, the main user has no signal input; only noise signals can be received. Through the judgment, it can be known that the spectrum is free at this moment and can be allocated to secondary users.Assuming that the average power of the signalX transmitted by the primary user is S, the mean value of the noise signal is 0, and the variance i is Gaussian white noise with S. That is, Xn=N0,x, and the transmitted signal and noise signal exist independently. Therefore, when the sample size is N, the variance of the energy statistic T can be expressed by
(8)ETed=Nx2,H0,(9)E=N1+γx,H1,(10)VarT=2Nx,Ho,(11)Var=2N1+γ,X,H1.Among them is the signal-to-noise ratio. From the knowledge of probability theory and statistics, if there areN independent random variables that obey a normal distribution, the sum of the squares of the random variables obeys the chi-square distribution with N degrees of freedom. And when the mean value of the random variables is nonzero, the random variable formed by their sum of squares obeys the noncentral chi-square distribution with N degrees of freedom, as shown in
(12)T~Xm2,H1.According to the study of polynomial complexity and non-determinism, first of all, a false alarm probabilityP needs to be given. Secondly, the judgment valve is calculated according to the given P. Then, the detection probability K can be calculated based on calculation. According to the false alarm probability P, when P=a, that is,
(13)P=12N−12Nαexp−12kdT.The detection performance of the energy detection algorithm is shown in Figure5.Figure 5
Energy algorithm detection performance.It can be seen from Figure5 that when the signal-to-noise ratio remains the same, the detection probability increases as the false alarm probability increases. Energy detection is a kind of blind detection algorithm, mainly the incoherent detection of signals. The calculation of energy statistics is mainly based on the signal energy received in the frequency domain. In the time domain, the energy detection algorithm approximates the received signal energy through the accumulation of the modulo square of the signal amplitude in the sensing period. In the frequency domain, the energy detection algorithm accumulates approximately the received signal energy by sensing the power spectrum of the signal in the frequency band [24].


### 3.1.2. Loop Detection Algorithm

Generally speaking, in a communication system, due to the huge amount of modulation, sampling and coding of the signal, and the statistical characteristics of the signal have periodic changes in time, it can be regarded as a periodic steady signal in a macroscopic view. The cyclostationary feature detection algorithm is an algorithm that uses signal cycle stationarity to determine whether the main user exists, and through simple calculation steps, the signal judgment result can be obtained [25].Analyzing the cyclostationary signal and theFt characteristic mainly use two functions, the cyclic autocorrelation and the cyclic spectrum correlation. The definition formula of its function is as follows:
(14)Ft=lim1Txt+π2x,where t is the cycle frequency and X represents the spectral component of the signal Xt at the center frequency of m. The principle diagram of the loop detection algorithm is shown in Figure 6.Figure 6
Schematic diagram of loop detection algorithm.Suppose the cyclic power spectral density of the signalXt transmitted by the authorized user is f; the cyclic power spectral density of Gaussian white noise t is Sf, and the cyclic power spectral density of the received signal y is the sum of the above two. In this case, the decision result of the signal passing the loop detection algorithm is
(15)Sf=HfSx0+Sn0,H1,(16)Srf=Hf+2aHf−aH1a.Among them,Sf represents the decision result, Hf represents the Fourier change of the signal impulse response, and S is the original signal, and the judgment standard of the cycle detection can be obtained from the following formula:
(17)Sraf>n,H1,(18)sraf<n,H0.Among them,n is the decision threshold, similar to the energy detection algorithm, which can derive the false alarm probability and detection probability of loop detection. The false alarm probability P and the detection probability Q are expressed by formula (17) and formula (18), respectively:
(19)P=Qμ−N2N,(20)Q=Pα−N1+γ2N.Among them are the signal-to-noise ratio and the average power of the signal transmitted by the main user. The loop detection steps are shown in Figure7.Figure 7
Cycle detection step diagram.It can be seen from Figure7 that the loop detection step is not complicated, and sampling data storage and signal processing are two key steps. The loop detection performance is shown in Figure 8.Figure 8
Cycle detection performance graph.When the given false alarm probability is 0.2, when the signal-to-noise ratio of loop detection increases, using this algorithm makes the detection performance stronger. The greater the signal length, the better the detection performance.


## 3.1.1. Energy Detection Algorithm

The energy detection algorithm is one of the most commonly used radio spectrum detection algorithms. Based on the existing useful signal plus the energy of the noise signal, it calculates the energy greater than the energy of the noise signal alone [23]. It can be expressed by
(5)Est+nt=Eptn>Ent.Among them,Est+nt represents the energy of the existing signal plus the noise signal, and 2 represents the final total energy obtained by the energy detection algorithm, and Ent represents the energy when the noise signal exists alone. The principle is to first input the sampled digital signal into the square algorithm module to obtain the signal energy and then use the comprehensive calculation module to average the signal energy and record it as energy statistics, namely, T. Finally, compare it with the preset decision upper limit L, and draw the final verdict. Comparing the energy statistics T with the upper decision limit L, it can be expressed by
(6)T<L,Ho,(7)T≥L,H1.Among them,L is the fixed decision upper limit of the spectrum state at a certain moment. If at a certain moment, the main user has no signal input; only noise signals can be received. Through the judgment, it can be known that the spectrum is free at this moment and can be allocated to secondary users.Assuming that the average power of the signalX transmitted by the primary user is S, the mean value of the noise signal is 0, and the variance i is Gaussian white noise with S. That is, Xn=N0,x, and the transmitted signal and noise signal exist independently. Therefore, when the sample size is N, the variance of the energy statistic T can be expressed by
(8)ETed=Nx2,H0,(9)E=N1+γx,H1,(10)VarT=2Nx,Ho,(11)Var=2N1+γ,X,H1.Among them is the signal-to-noise ratio. From the knowledge of probability theory and statistics, if there areN independent random variables that obey a normal distribution, the sum of the squares of the random variables obeys the chi-square distribution with N degrees of freedom. And when the mean value of the random variables is nonzero, the random variable formed by their sum of squares obeys the noncentral chi-square distribution with N degrees of freedom, as shown in
(12)T~Xm2,H1.According to the study of polynomial complexity and non-determinism, first of all, a false alarm probabilityP needs to be given. Secondly, the judgment valve is calculated according to the given P. Then, the detection probability K can be calculated based on calculation. According to the false alarm probability P, when P=a, that is,
(13)P=12N−12Nαexp−12kdT.The detection performance of the energy detection algorithm is shown in Figure5.Figure 5
Energy algorithm detection performance.It can be seen from Figure5 that when the signal-to-noise ratio remains the same, the detection probability increases as the false alarm probability increases. Energy detection is a kind of blind detection algorithm, mainly the incoherent detection of signals. The calculation of energy statistics is mainly based on the signal energy received in the frequency domain. In the time domain, the energy detection algorithm approximates the received signal energy through the accumulation of the modulo square of the signal amplitude in the sensing period. In the frequency domain, the energy detection algorithm accumulates approximately the received signal energy by sensing the power spectrum of the signal in the frequency band [24].


## 3.1.2. Loop Detection Algorithm

Generally speaking, in a communication system, due to the huge amount of modulation, sampling and coding of the signal, and the statistical characteristics of the signal have periodic changes in time, it can be regarded as a periodic steady signal in a macroscopic view. The cyclostationary feature detection algorithm is an algorithm that uses signal cycle stationarity to determine whether the main user exists, and through simple calculation steps, the signal judgment result can be obtained [25].Analyzing the cyclostationary signal and theFt characteristic mainly use two functions, the cyclic autocorrelation and the cyclic spectrum correlation. The definition formula of its function is as follows:
(14)Ft=lim1Txt+π2x,where t is the cycle frequency and X represents the spectral component of the signal Xt at the center frequency of m. The principle diagram of the loop detection algorithm is shown in Figure 6.Figure 6
Schematic diagram of loop detection algorithm.Suppose the cyclic power spectral density of the signalXt transmitted by the authorized user is f; the cyclic power spectral density of Gaussian white noise t is Sf, and the cyclic power spectral density of the received signal y is the sum of the above two. In this case, the decision result of the signal passing the loop detection algorithm is
(15)Sf=HfSx0+Sn0,H1,(16)Srf=Hf+2aHf−aH1a.Among them,Sf represents the decision result, Hf represents the Fourier change of the signal impulse response, and S is the original signal, and the judgment standard of the cycle detection can be obtained from the following formula:
(17)Sraf>n,H1,(18)sraf<n,H0.Among them,n is the decision threshold, similar to the energy detection algorithm, which can derive the false alarm probability and detection probability of loop detection. The false alarm probability P and the detection probability Q are expressed by formula (17) and formula (18), respectively:
(19)P=Qμ−N2N,(20)Q=Pα−N1+γ2N.Among them are the signal-to-noise ratio and the average power of the signal transmitted by the main user. The loop detection steps are shown in Figure7.Figure 7
Cycle detection step diagram.It can be seen from Figure7 that the loop detection step is not complicated, and sampling data storage and signal processing are two key steps. The loop detection performance is shown in Figure 8.Figure 8
Cycle detection performance graph.When the given false alarm probability is 0.2, when the signal-to-noise ratio of loop detection increases, using this algorithm makes the detection performance stronger. The greater the signal length, the better the detection performance.


## 3.2. Structural Features of Radio Communication English

### 3.2.1. Vocabulary Features

Radio communication English belongs to a category of English for Science and Technology, and one of the notable lexical features is as follows: More professional terms and fixed terms are used, and the format is more rigorous and formal: for example, Software Defined Radio software radio and Digital signal Processor signal processor. The second lexical feature of radio communication English is the use of derivative words. The main derivation methods are prefix and suffix: for example, anti-, anti-missile (anti-missile), and anticatalyst (anti-catalyst) insulation. Derivative usage is mainly reflected in professional terminology. Another significant vocabulary feature of radio communication English is Acronym. Acronyms are very common in radio communication English. A phrase consisting of multiple words, usually only the first letter of each word, is intercepted: for example, SISO single input single output (Single Input Single Output); VHDL Very-High-SpeedIntegratedCircuit Hardware Description Language (Very-High-SpeedIntegratedCircuit Hardware Description Language); and ASIC (Application Specific Integrated Circuit). There is also a lexical feature of radio communication, that is, vocabulary synthesis. Vocabulary synthesis is to combine two or more words according to a certain order and rules to form a new word. It is one of the important methods for the generation and development of English terminology in the field of radio communication, and it is also the most commonly used word-building method in the field of scientific and technological English. In radio communication English, the composition method is mainly composed of compound words, then compound adjectives, with or without hyphens and with hyphens: such as benchmarking, payload, and serial-input-out-put.In a word, radio communication English vocabulary has many professional terms, the format is fixed and formal, and more derived vocabulary, acronyms, and compound words are used [26].


### 3.2.2. Syntactic Features

The most notable syntactic feature in communication English is the use of passive sentences. The main reason is that the passive structure is more objective than the active structure; emphasizing objective facts is in line with the logical and rigorous characteristics of technical English. Secondly, under normal circumstances, passive sentences will be more concise than active sentences, making the content more eye-catching and beautiful to attract attention [27]. It widely uses complex and long sentences such as attributive clauses. As we all know, communication English is a language used to explain the content of the field of communication technology or describe its regular characteristics, and it faces a wide range of groups. According to Nida’s functional equivalence theory, radio communication English translation must be combined with the content and functions of radio communication technology for translation. This requires correct expression, strict structure, and strong logic. Therefore, in order to meet the above characteristics, communication English often adopts complex and long sentences with multiple modifiers, multiple components, and multiple levels. Such a long and complex sentence with many structures is a very common sentence pattern in communication English. In addition to the form of attributive clauses, there are also various forms of complex long sentences in communication English. Such sentence pattern features cause people to be good at splitting and understanding structure and sentence meaning when reading or translating communication English [28].All in all, in order to express more objectively and rigorously, especially when describing related important technical concepts, radio communication English usually has more passive sentences and long sentences in its syntactic structure. This puts forward high demands for radio communication English translators.


## 3.2.1. Vocabulary Features

Radio communication English belongs to a category of English for Science and Technology, and one of the notable lexical features is as follows: More professional terms and fixed terms are used, and the format is more rigorous and formal: for example, Software Defined Radio software radio and Digital signal Processor signal processor. The second lexical feature of radio communication English is the use of derivative words. The main derivation methods are prefix and suffix: for example, anti-, anti-missile (anti-missile), and anticatalyst (anti-catalyst) insulation. Derivative usage is mainly reflected in professional terminology. Another significant vocabulary feature of radio communication English is Acronym. Acronyms are very common in radio communication English. A phrase consisting of multiple words, usually only the first letter of each word, is intercepted: for example, SISO single input single output (Single Input Single Output); VHDL Very-High-SpeedIntegratedCircuit Hardware Description Language (Very-High-SpeedIntegratedCircuit Hardware Description Language); and ASIC (Application Specific Integrated Circuit). There is also a lexical feature of radio communication, that is, vocabulary synthesis. Vocabulary synthesis is to combine two or more words according to a certain order and rules to form a new word. It is one of the important methods for the generation and development of English terminology in the field of radio communication, and it is also the most commonly used word-building method in the field of scientific and technological English. In radio communication English, the composition method is mainly composed of compound words, then compound adjectives, with or without hyphens and with hyphens: such as benchmarking, payload, and serial-input-out-put.In a word, radio communication English vocabulary has many professional terms, the format is fixed and formal, and more derived vocabulary, acronyms, and compound words are used [26].


## 3.2.2. Syntactic Features

The most notable syntactic feature in communication English is the use of passive sentences. The main reason is that the passive structure is more objective than the active structure; emphasizing objective facts is in line with the logical and rigorous characteristics of technical English. Secondly, under normal circumstances, passive sentences will be more concise than active sentences, making the content more eye-catching and beautiful to attract attention [27]. It widely uses complex and long sentences such as attributive clauses. As we all know, communication English is a language used to explain the content of the field of communication technology or describe its regular characteristics, and it faces a wide range of groups. According to Nida’s functional equivalence theory, radio communication English translation must be combined with the content and functions of radio communication technology for translation. This requires correct expression, strict structure, and strong logic. Therefore, in order to meet the above characteristics, communication English often adopts complex and long sentences with multiple modifiers, multiple components, and multiple levels. Such a long and complex sentence with many structures is a very common sentence pattern in communication English. In addition to the form of attributive clauses, there are also various forms of complex long sentences in communication English. Such sentence pattern features cause people to be good at splitting and understanding structure and sentence meaning when reading or translating communication English [28].All in all, in order to express more objectively and rigorously, especially when describing related important technical concepts, radio communication English usually has more passive sentences and long sentences in its syntactic structure. This puts forward high demands for radio communication English translators.


## 4. Discussion on Translation Skills of Radio Communication English

Combining the vocabulary and syntactic features of radio communication English introduced above, it has explored some communication English translation techniques based on Nida’s functional equivalence translation theory.


### 4.1. Skills in Vocabulary

We all know that radio communication English has multiple technical terms, multiple derivatives, acronyms, and compound words. To translate every communication English vocabulary accurately and appropriately, it will inevitably be inseparable from a certain professional knowledge base. Because if there is no relevant professional knowledge base, the translator is easy to misinterpret certain professional vocabulary. For radio communication English vocabulary, based on a certain professional knowledge, translators also need to be good at using translation methods such as literal translation, free translation, transliteration, and retention of original abbreviations. In communication English, vocabularies such as compound nouns and derivative words are mostly used literal translation and free translation to ensure accurate interpretation. In addition, in radio communication English, most of the new foreign words and unit of measurement words brought about by technological development can be accurately and quickly translated using transliteration. Of course, in order to make the translation more concise, the unit of measurement may not be translated, such as 500 MHz~900 MHz, without affecting the understanding. Similarly, because some acronyms translated into words are too long, it will affect the coherence of the original text and the need for translation is low; it can save the translation. Common acronyms such as GSO and MEO can also be untranslated. In short, the vocabulary translation of radio communication English seems simple, but in fact, each vocabulary needs to be carefully distinguished and considered before the appropriate translation method can be selected. Only in this way can the translation of the vocabulary be accurate [29].


### 4.2. Syntactic Skills

Combining with the above-mentioned general English syntactic structure features, according to Nida’s functional equivalence translation theory, if technical concepts are to be understood by different audiences, we can analyze the syntactic translation skills in turn. First of all, according to the feature that passive sentences are often used in communication English, combined with translation practice, the passive structure is extracted into Chinese unsubjected sentences; passive structures are translated into Chinese active sentences by these two translation methods. Under normal circumstances, when the passive structure in English is unnecessary or unable to describe the performer of the action, it can be translated into a Chinese without subject sentence. This translation not only is accurate but also makes the sentences fluent, in line with Chinese expression habits, and easy for people to understand and accept. In general, in the translation of communication English sentences, due to the complexity of the long sentence, translators need to flexibly choose and use appropriate translation methods in accordance with the actual situation. Only the proper translation method can ensure the quality of translation, ensure that people can correctly understand the relevant content, and ensure the sound development of radio communication English translation [30].


## 4.1. Skills in Vocabulary

We all know that radio communication English has multiple technical terms, multiple derivatives, acronyms, and compound words. To translate every communication English vocabulary accurately and appropriately, it will inevitably be inseparable from a certain professional knowledge base. Because if there is no relevant professional knowledge base, the translator is easy to misinterpret certain professional vocabulary. For radio communication English vocabulary, based on a certain professional knowledge, translators also need to be good at using translation methods such as literal translation, free translation, transliteration, and retention of original abbreviations. In communication English, vocabularies such as compound nouns and derivative words are mostly used literal translation and free translation to ensure accurate interpretation. In addition, in radio communication English, most of the new foreign words and unit of measurement words brought about by technological development can be accurately and quickly translated using transliteration. Of course, in order to make the translation more concise, the unit of measurement may not be translated, such as 500 MHz~900 MHz, without affecting the understanding. Similarly, because some acronyms translated into words are too long, it will affect the coherence of the original text and the need for translation is low; it can save the translation. Common acronyms such as GSO and MEO can also be untranslated. In short, the vocabulary translation of radio communication English seems simple, but in fact, each vocabulary needs to be carefully distinguished and considered before the appropriate translation method can be selected. Only in this way can the translation of the vocabulary be accurate [29].


## 4.2. Syntactic Skills

Combining with the above-mentioned general English syntactic structure features, according to Nida’s functional equivalence translation theory, if technical concepts are to be understood by different audiences, we can analyze the syntactic translation skills in turn. First of all, according to the feature that passive sentences are often used in communication English, combined with translation practice, the passive structure is extracted into Chinese unsubjected sentences; passive structures are translated into Chinese active sentences by these two translation methods. Under normal circumstances, when the passive structure in English is unnecessary or unable to describe the performer of the action, it can be translated into a Chinese without subject sentence. This translation not only is accurate but also makes the sentences fluent, in line with Chinese expression habits, and easy for people to understand and accept. In general, in the translation of communication English sentences, due to the complexity of the long sentence, translators need to flexibly choose and use appropriate translation methods in accordance with the actual situation. Only the proper translation method can ensure the quality of translation, ensure that people can correctly understand the relevant content, and ensure the sound development of radio communication English translation [30].


## 5. Conclusions

Today’s society is an information society, with rapid development and innovation of science and technology, and international exchanges and cooperation are becoming more frequent. The close exchanges and exchanges between countries have promoted the development of science and technology and have also given birth to the demand for science and technology translation. With the development of science and technology, people need to understand the latest technological development information through science and technology translation. Radio communication English translation belongs to a category of scientific translation. As the representative of the current advanced communication technology, radio communication has been used more and more widely all over the world. International exchanges and cooperation on radio communication technology are becoming more frequent. Therefore, the translation of radio communication English has become an important translation topic, and it has also become an important research field of practical significance. The research of radio communication English has strong practical significance and has a positive effect on promoting the development of radio communication technology [31]. This article briefly introduces radio communication technology, discusses the structural features and translation skills of radio communication English, and provides some methodological references and references for the translation of communication English. Radio communication English has unique characteristics of vocabulary and syntax. In terms of vocabulary, there are many acronyms, compound words, and professional vocabulary; in terms of syntax, long sentences with multiple structures, such as passive sentences and attributive clauses, are often used. Combining the characteristics of both the vocabulary and syntactic structure of Radio English, adopting corresponding translation strategies and methods, and prescribing the right medicine can improve the quality of radio communication English translation, ensure technical exchanges, and promote technological development. As a field of technical English translation, the accuracy and logic of the translation of communication English are relatively high. The translator of every word and sentence should not take it lightly. This requires translators to pay attention to the accumulation of professional vocabulary and professional knowledge. Secondly, we must be good at using some appropriate translation methods and techniques flexibly, and methods such as literal translation, free translation, phonetic translation, provincial translation, passive translation, active, passive to no-owner are used to improve translation quality, so as to achieve the purpose of effectively conveying information to readers, realize the “faith” and “reach” of English translation of communication technology [32], so as to ensure the technical exchange and development of radio communication technology. In order to continuously improve the level of translation of communication English, translators also need to proactively seize every opportunity and have the courage to undertake the translation task of radio communication English and continuously reflect, summarize, and improve in translation practice. In addition, with the continuous development of radio communication technology, translators should keep up with the technological trend and always pay attention to radio communication information to ensure that they can keep abreast of the latest developments in radio communication technology and understand the technical content. Update related terminology translations at any time, and flexibly change translation strategies based on actual conditions, so as to ensure the correct delivery of information, better perform their own translation duties and obligations, and contribute to technological development. In the future, radio communication technology will continue to climb peaks and reach new technological heights one after another. The radio communication English translation will also be updated and developed continuously to ensure that technology is not caught in communication barriers and that people can keep abreast of the latest developments in the field of radio communication. Ensure good communication and cooperation between people and countries in communication technology. Due to the limited research level, this article still has some shortcomings, but the research on radio communication English translation skills will never stop. Academia will inevitably emerge more and more researches on the structural features and translation skills of radio communication English and will get more scientific and effective communication English translation skills, so as to promote the progress and development of radio communication English translation.



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*Source: 9356725-2022-04-20.xml*