Patent Publication Number: US-2020305002-A1

Title: Wireless device and wireless transmission method

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is based upon and claims the benefit of priority of the prior Japanese Patent Application No. 2019-054276, filed on Mar. 22, 2019, the entire contents of which are incorporated herein by reference. 
     FIELD 
     The embodiments discussed herein are related to a wireless device and a wireless transmission method. 
     BACKGROUND 
     In wireless communications, radio waves also arrive at terminal devices other than a destination node. Hence, such communications will involve a higher risk of interception than wire communications such as optical fiber communications. Accordingly, a proposed method is one for implementing a secure communication by using characteristics of a wireless channel between a source node and a destination node in addition to mathematical encryption for encrypting transmission data. 
     For example, the source node may transmit a signal to which distortions in the wireless channel between the source node and the destination node have been added. Then, the destination node receives the signal with the distortions canceled out in the wireless channel. Hence, the destination node can recover data from the received signal. However, since the wireless channel between the source node and another terminal device is different from that between the source node and the destination node, distortions in a signal arriving at the other terminal device are not canceled out. Hence, the other terminal device cannot recover data from the received signal (e.g., International Publication Pamphlet No. WO 2009/022423). 
     However, in many cases, wireless signals are transmitted using signal points (phase and amplitude) corresponding to a constellation based on a specified modulation scheme, and hence candidates for signal points of individual symbols are known. Thus, an interception node could recover data from a signal transmitted from a source node to a destination node by compensating for distortions in the wireless channel by using the differences between the signal point of the received signal and candidates for the signal point. 
     A method for implementing a secure communication using artificial noise when a source node includes a plurality of antennas has been proposed (e.g., Japanese Laid-open Patent Publication No. 2004-266818 and reference document 1). In this scheme, the source node generates, according to a wireless channel between the source node and the destination node, artificial noise to be canceled out at the destination node. Then, the source node performs the precoding of a data signal and the artificial noise and transmits a plurality of signals obtained from the precoding via a plurality of antennas. Hence, the destination node can recover data from the signal with the artificial noise canceled out. In addition, related arts are described in reference documents 2 and 3. 
     Reference Document 1: S. Goel and R. Negi, “Guaranteeing Secrecy using Artificial Noise,” IEEE Trans. Wireless Commun., VOL. 7, NO. 6, pp. 2180-2189, JUNE 2008 Reference Document 2: Vicente Zarzoso and Pierre Comon, “Robust Independent Component Analysis by Iterative Maximization of the Kurtosis Contrast With Algebraic Optimal Step Size”, IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 21, NO. 2, FEBRUARY 2010 
     Reference Document 3: S. Liu, Y. Hong, and E. Viterbo, “Artificial Noise Revisited,” IEEE Trans. Inf. Theory, VOL. 61, NO. 7, pp. 3901-3911, JULY 2015 
     In a secure communication using artificial nose, the artificial noise in a received signal is canceled out, as described above, at a destination node, and the artificial noise remains in a received signal at another terminal device. Hence, it is difficult for the other terminal device to recover data from the received signal. 
     However, when the number of reception antennas of an interception node is larger than the number of transmission antennas of the source node, the interception node could separate an artificial noise series from a received signal without recognizing a signal combining scheme based on precoding performed by the source node (e.g., non-patent document 2). In this case, the interception node could recover data. 
     SUMMARY 
     According to an aspect of the embodiments, a wireless device includes: a plurality of antennas; a first correlation series generator configured to generate a first correlation series based on transmission data; a second correlation series generator configured to generate a second correlation series based on the first correlation series; a first modulator configured to modulate the transmission data to generate a first modulated signal; a second modulator configured to modulate the first correlation series to generate a second modulated signal; a third modulator configured to modulate the second correlation series to generate a third modulated signal; a signal combiner configured to combine the first modulated signal, the second modulated signal and the third modulated signal to generate a first transmission signal, a second transmission signal and a third transmission signal; and a transmitter configured to output the first transmission signal, the second transmission signal and the third transmission signal respectively via a first antenna, a second antenna and a third antenna among the plurality of antennas. 
     The object and advantages of the invention will be realized and attained by means of the elements and combinations particularly pointed out in the claims. 
     It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory and are not restrictive of the invention. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  illustrates an example of a wireless communication system; 
         FIG. 2  illustrates an example of a concealing method using artificial noises; 
         FIG. 3  illustrates an example of a simulation result of a successful decipher rate; 
         FIG. 4  illustrates an example of a wireless device in accordance with a first embodiment; 
         FIG. 5  illustrates an example of a signal generator; 
         FIG. 6  is a flowchart illustrating an example of a process performed by a signal generator; 
         FIG. 7  is a flowchart illustrating an example of a method for generating an artificial noise series; 
         FIG. 8  illustrates an example of an effect achieved in accordance with a first embodiment; 
         FIG. 9  illustrates an example of a wireless device in accordance with a second embodiment; 
         FIG. 10  illustrates an example of a table that stores information for determining a correlation coefficient; 
         FIG. 11  illustrates an example of a signal generator in accordance with a third embodiment; 
         FIG. 12  illustrates an example of a signal generator in accordance with a fourth embodiment; and 
         FIG. 13  illustrates an example of the hardware configuration of a wireless device. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
       FIG. 1  illustrates an example of a wireless communication system in accordance with embodiments of the invention. The wireless communication system  100  includes a source node  1 , a destination node  2 , and an interception node  3 . For example, the source node  1  may be implemented by a base station. In this case, the destination node  2  and the interception node  3  are each implemented by a terminal device (or user equipment). The source node  1 , the destination node  2 , and the interception node  3  are each an example of a wireless device. 
     The source node  1  transmits data to the destination node  2 . However, a wireless signal carrying the data arrives not at only the destination node  2  but also at the interception node  3 . Thus, the source node  1  has a function for concealing the wireless signal so as to prevent the interception node  3  from deciphering the data. Specifically, the source node  1  has a function for concealing transmission data by using artificial noise. 
     Concealing Based on Artificial Noise 
       FIG. 2  illustrates an example of a concealing method using artificial noise. In this example, the source node  1  transmits data S to the destination node  2 . Data S is represented as a symbol of s 1 , s 2 , . . . , sn. Each symbol of data S is mapped onto a constellation in accordance with a designated modulation scheme. The source node  1  also generates artificial noise series AN 1  and AN 2 . Each symbol of the artificial noise series AN 1  and AN 2  is randomly mapped onto the constellation. A signal combiner generates transmission signals  1 - 3  by combining signals output from mappers. Each of the transmission signals  1 - 3  includes data S and artificial noises AN 1  and AN 2 . The signal combiner generates the transmission signals  1 - 3  according to a wireless channel H between the source node  1  and the destination node  2  so that the artificial noises AN 1  and AN 2  can be canceled out at the destination node  2 . As depicted in  FIG. 2 , the transmission signals  1 - 3  are output respectively via antennas A 1 -A 3 . 
     The transmission signals  1 - 3  propagate to the destination node  2  via the wireless channel H. The artificial noises AN 1  and AN 2  are canceled out in the wireless channel H. Hence, the destination node  2  can recover data S from the received signals. The transmission signals  1 - 3  also propagate to the interception node  3  via a wireless channel G. However, since the transmission signals  1 - 3  have been generated according to the wireless channel H, and the wireless channel G is different from the wireless channel H, the artificial noises AN 1  and AN 2  remain in the interception node  3 . Hence, the interception node  3  cannot recover data S from the received signals. 
     However, in the example depicted in  FIG. 2 , each symbol of the artificial noises AN 1  and AN 2  is transmitted using a random phase/amplitude. Accordingly, the occurrence frequency of the phase/amplitude of the artificial noises AN 1  and AN 2  is dependent on Gaussian distribution. Hence, there are no correlations between data S and the artificial noises AN 1  and AN 2 , and there are no correlations between the artificial noises AN 1  and AN 2 . 
     In the meantime, researches have been carried out on a method for separating, at a reception node, a plurality of signals combined at a source node. For example, the blind source separation or the blind equalization may allow a plurality of combined signals to be separated without using information on a wireless channel between a source node and a reception node. The independent component analysis (ICA) among these is known as a representative separation method. 
     When a plurality of signals combined at a source node are independent of each other, the ICA allows these signals to be separated with a high probability. In the example depicted in  FIG. 2 , there are no correlations between data S and the artificial noises AN 1  and AN 2 , and there are no correlations between the artificial noises AN 1  and AN 2 . Hence, when the number of reception antennas of the interception node  3  is larger than the number of transmission antennas of the source node  1 , the interception node  3  can separate data S from the artificial noises AN 1  and AN 2  with a high probability by using the ICA. 
       FIG. 3  illustrates an example of a simulation result of a successful decipher rate that could be achieved if data is transmitted using the method depicted in  FIG. 2  and the interception node  3  uses the ICA. According to this simulation, data S is deciphered with a very high probability when the power of interference waves (i.e., the power of artificial noise) is low. Data S is also deciphered with a probability of about 40 percent even when the power of interference waves is high. 
     First Embodiment 
       FIG. 4  illustrates an example of a wireless device in accordance with a first embodiment of the invention. For example, a wireless device  10  may correspond to the base station (source node)  1  in the wireless communication system depicted in  FIG. 1 . The following descriptions are based on the assumption that the wireless device  10  transmits data S to the terminal device (destination node)  2  depicted in  FIG. 1 . 
     As depicted in  FIG. 4 , the wireless device  10  includes a receiver  11 , a signal generator  12 , a signal combiner  13 , a transmitter  14 , and a plurality of transmission antennas A 1 -A 3 . However, the wireless device  10  may include functions or elements that are not depicted in  FIG. 4 . For example, the wireless device  10  may include one or more reception antennas. 
     The receiver  11  receives a wireless signal transmitted from another wireless device. Each wireless device periodically transmits a pilot signal. The pilot signal has a known transmission power and a known bit pattern. Thus, the receiver  11  can estimate the state of a wireless channel by receiving and demodulating the pilot signal. In this example, the receiver  11  receives and demodulates a pilot signal transmitted from the destination node  2  so as to estimate the wireless channel H between the wireless device  10  and the destination node  2 . Channel information indicating the wireless channel H is supplied from the receiver  11  to the signal combiner  13 . 
     The signal generator  12  generates a data series and artificial noise series from data S. In this example, a data series S and artificial noise series AN 1  and AN 2  are generated. Data S is supplied from an application (or application layer) to the wireless device  10 . There are correlations between the data series and the artificial noise series, as will be described hereinafter in detail. When a plurality of artificial noises are generated, there will also be correlations between these artificial noises. 
     The signal combiner  13  combines the data series and the artificial noise series according to the channel information indicating the wireless channel H. In particular, the signal combiner  13  performs a precoding process for the data series and the artificial noise series according to the channel information indicating the wireless channel H. As a result, transmission signals T 1 -T 3  are generated. This precoding process is such that the transmission signals T 1 -T 3  are generated in such a manner as to cancel out the artificial noise at the wireless channel H when these signals are transmitted from the wireless device  10 . 
     The transmitter  14  outputs the transmission signals T 1 -T 3  via the antennas A 1 -A 3 . Specifically, the transmission signal T 1  is output via the antenna A 1 , the transmission signal T 2  is output via the antenna A 2 , and the transmission signal T 3  is output via the antenna A 3 . 
     The transmission signals T 1 -T 3  propagate to the destination node  2  via the wireless channel H. The transmission signals T 1 -T 3  have been generate in such a manner as to cancel out the artificial noise at the wireless channel H. Hence, the artificial noises AN 1  and AN 2  are canceled out at the wireless channel H, and the destination node  2  can recover data S from the received signals. The transmission signals T 1 -T 3  also propagate to the interception node  3  via the wireless channel G. However, since the transmission signals T 1 -T 3  have been generated according to the wireless channel H, the artificial noises AN 1  and AN 2  remain in the interception node  3 . Hence, the interception node  3  cannot recover data S from the received signals. 
     The signal generator  12  and the signal combiner  13  may be implemented by a processor system that includes a processor and a memory. In this case, the processor provides the functions of the signal generator  12  and the signal combiner  13  by executing a program stored in the memory. The signal generator  12  and the signal combiner  13  may be implemented by one or more processor systems. Alternatively, the signal generator  12  and the signal combiner  13  may be implemented by a digital signal processing circuit. In addition, the signal generator  12  and the signal combiner  13  may be implemented by a combination of software processing and a hardware circuit. 
       FIG. 5  illustrates an example of the signal generator  12 . In this example, the signal generator  12  includes correlation series generators  21 - 22  and mappers  23 - 25 . The signal generator  12  may include functions or elements that are not depicted in  FIG. 5 . The signal generator  12  is supplied with data S. In this example, data S is represented as a symbol string (s 1  to s N ). Each symbol carries data with as many bits as are dependent on a modulation scheme. For example, when the wireless device  10  transmits data in accordance with QPSK, each symbol may transmit two bits of data. When the wireless device  10  transmits data in accordance with 16QAM, each symbol transmits four bits of data. 
     The correlation series generator  21  generates a first correlation series according to data S. The first correlation series is used as an artificial noise. Accordingly, a first correlation series generated by the correlation series generator  21  may hereinafter be referred to as an “artificial noise series AN 1 ”. The artificial noise series AN 1  is represented as a symbol string (an 1   1  to an 1   N ) The number of symbols of the artificial noise series AN 1  is equal to that of data S. 
     The correlation series generator  22  generates a second correlation series according to the artificial noise series AN 1 . The second correlation series is also used as an artificial noise. Accordingly, a second correlation series generated by the correlation series generator  22  may hereinafter be referred to as an “artificial noise series AN 2 ”. The artificial noise series AN 2  is represented as a symbol string (an 2   1  to an 2   N ). The number of symbols of the artificial noise series AN 2  is also equal to that of data S. 
     The mapper (modulator)  23  sequentially maps the symbols of data S onto a constellation in accordance with a designated modulation scheme. As a result, a modulated signal indicating data S is generated. For example, when the wireless device  10  transmits data in accordance with QPSK, each symbol may be mapped to a signal point that corresponds to the value (00, 01, 10, 11) of the symbol. As a result of this mapping process, each symbol is expressed as, for example, a complex number. This complex number indicates the phase and amplitude of the signal. 
     The mapper (modulator)  24  sequentially maps the symbols of the artificial noise series AN 1  onto the constellation in accordance with a designated modulation scheme. As a result, a modulated signal indicating the artificial noise series AN 1  is generated. The mapper (modulator)  25  sequentially maps the symbols of the artificial noise series AN 2  onto the constellation in accordance with a designated modulation scheme. As a result, a modulated signal indicating the artificial noise series AN 2  is generated. Note that the mappers  23 - 25  preferably perform the mapping in accordance with the same modulation scheme. 
     The modulated signals generated by the mappers  23 - 25  are supplied to the signal combiner  13 . Then, the signal combiner  13  combines these modulated signals according to the channel information indicating the wireless channel H between the wireless device  10  and the destination node  2 . As a result, transmission signals T 1 -T 3  are generated. 
       FIG. 6  is a flowchart illustrating an example of a process performed by the signal generator  12 . The wireless device  10  has already acquired channel information indicating the wireless channel H between the wireless device  10  and the destination node  2  before performing the processes of the flowchart. For example, the wireless channel H may be estimated as a result of the receiver  11  receiving a pilot signal transmitted from the destination node  2 . 
     In S 1 , the signal generator  12  acquires transmission data. The transmission data is supplied from an application (or application layer) to the wireless device  10 . The signal generator  12  generates a data series from the transmission data in accordance with a modulation scheme used by the wireless device  10 . For example, when the data is transmitted in accordance with QPSK, each symbol carries two bits of data. As a result, a data series (s 1 -s N ) is obtained. 
     In S 2 , the signal generator  12  initializes and sets a variable k as 1. The variable k is used to count the number of artificial noise series to be generated. 
     In S 3 , the signal generator  12  generates a first artificial noise series according to the data series. In particular, an artificial noise series AN 1  is generated. In the example depicted in  FIG. 5 , the correlation series generator  21  generates the artificial noise series AN 1 . A method for generating the artificial noise series AN 1  will be described hereinafter by referring to  FIG. 7 . 
     In S 4 , it is decided whether the variable k is greater than a specified number. In this example, the specified number is “the number of transmission antennas of the wireless device  10  minus 2”. In the example depicted in  FIG. 4 , the wireless device  10  includes three antennas (A 1 -A 3 ). Hence, in this case, the specified number is “1”, and it is decided whether the variable k is greater than 1. 
     When the variable k is not greater than the specified number, the signal generator  12  generates, in S 5 , a new artificial noise series according to the artificial noise series that has already been generated. For example, when an artificial noise series AN 1  has already been generated in the example depicted in  FIG. 5 , the correlation series generator  22  may generate an artificial noise series AN 2  according to the artificial noise series AN 1 . A method for generating a new artificial noise series according to a previously generated artificial noise series is substantially the same as the method for generating an artificial noise series according to a data series and will be described hereinafter by referring to  FIG. 7 . 
     In S 6 , the signal generator  12  increments the variable k by one. Subsequently, the process of the signal generator  12  returns to S 4 . In this way, the signal generator  12  repeatedly performs the processes of S 4 -S 6  until the variable k exceeds the specified number. Thus, the number of artificial noise series to be generated will be “the number of antennas minus 1”. In this case, an (i+1)-th artificial noise series is generated according to an i-th artificial noise series. In the example depicted in  FIGS. 4-5 , two artificial noise series (AN 1 , AN 2 ) are generated. Note that the sum of the number of data series and the number of artificial noise series is equal to the number of transmission antennas of the wireless device  10 . 
     When the variable k exceeds the specified number (S 4 : Yes), the signal generator  12  performs mapping for each symbol of each series in S 7 . In the example depicted in  FIG. 5 , the mapper  23  generates a modulated signal indicating the data series, the mapper  24  generates a modulated signal indicating the artificial noise series AN 1 , and the mapper  25  generates a modulated signal indicating the artificial noise series AN 2 . The signal combiner  13  combines these modulated signals. 
       FIG. 7  is a flowchart illustrating an example of a method for generating an artificial noise series. The processes of this flowchart correspond to S 3  in  FIG. 6 . Thus, the correlation series generator  21  generates an artificial noise series AN 1  from a data series. 
     In S 11 , the correlation series generator  21  makes initial settings for a process of generating an artificial noise series. In particular, the correlation series generator  21  initializes and sets a variable i as 1. The variable i is used to identify the symbols of a data series. The correlation series generator  21  also obtains a threshold C. In the example depicted in  FIG. 5 , the threshold C corresponds to a coefficient C s-AN  indicating the correlation between the data series and the artificial noise series. The threshold C is determined in advance through, for example, a simulation and stored in a memory provided for the wireless device  10 . 
     In S 12 , the correlation series generator  21  decides whether the variable i is greater than N. N indicates the number of symbols of the data series. Thus, the correlation series generator  21  decides whether the processes of S 13 -S 16  have been performed for all symbols in the data series. When the data series still includes a symbol for which the processes of S 13 -S 16  have not been performed, the process of the correlation series generator  21  shifts to S 13 . 
     In S 13 , the correlation series generator  21  generates a random number R greater than or equal to zero but less than 1. In S 14 , the correlation series generator  21  compares the random number R generated in S 13  with the threshold C. 
     When the random number R is less than or equal to the threshold C, the correlation series generator  21  determines, in S 15 , a symbol of the artificial noise series AN 1  according to a corresponding symbol of the data series S. Specifically, a value equal to the value of an i-th symbol s i  of the data series S is output as an i-th symbol an 1   i  of the artificial noise series AN 1 . Note that each symbol is expressed as, for example, a complex number. 
     When the random number R is greater than the threshold C, the correlation series generator  21  determines, in S 16 , a symbol of the artificial noise series AN 1  regardless of the data series S. In this case, the correlation series generator  21  randomly selects one of a plurality of signal points provided in accordance with a modulation scheme used by the wireless device  10 . For example, when the wireless device  10  transmits data in accordance with QPSK, one signal point may be randomly selected from four signal points (00, 01, 10, 11) provided by QPSK. Then, the correlation series generator  21  outputs a value indicating the selected signal point as an i-th symbol an 1   i  of the artificial noise series AN 1 . 
     In S 17 , the correlation series generator  21  increments the variable i by one. Subsequently, the process of the correlation series generator  21  returns to S 12 . Thus, the correlation series generator  21  performs the processes of S 13 -S 16  for all symbols in the data series. As a result, an artificial noise series AN 1  having as many symbols as the number of symbols of the data series is generated. 
     As described above, when the random number R is less than or equal to the threshold C, an artificial noise symbol based on data S is generated. When the random number R is greater than the threshold C, an artificial noise symbol irrelevant to data S is generated. Accordingly, the correlation between data S and the artificial noise AN 1  is high when the threshold C is a large value, and low when the threshold C is a small value. Thus, the degree of correlation between data S and the artificial noise AN 1  can be determined by adjusting the threshold C. 
     A method for generating a new artificial noise series from a previously generated artificial noise series is substantially the same as the method for generating an artificial noise series from a data series. Hence, a new artificial noise series may be generated from a previously generated artificial noise series in accordance with the flowchart depicted in  FIG. 7 . However, in the example depicted in  FIG. 5 , the process of generating a new artificial noise series from a previously generated artificial noise series is performed by the correlation series generator  22 . The threshold used in the process of generating a new artificial noise series from a previously generated artificial noise series (C AN-AN  in  FIG. 5 ) may be different from the threshold used in the process of generating an artificial noise series from a data series (C S-AN  in  FIG. 5 ). 
     The signal combiner  13  combines the data series S and the artificial noise series AN 1  and AN 2 . Accordingly, descriptions are given in the following of a precoding process performed by the signal combiner  13 . 
     Let H indicate a wireless channel between the wireless device  10  and the destination node  2 . In this case, H is a complex matrix with N B  rows and N A  columns. N A  indicates the number of transmission antennas of the wireless device  10 . N B  indicates the number of reception antennas of the destination node  2 . 
     The channel matrix H may be expressed as formula (1) by performing singular value decomposition of the channel matrix H. 
         H=UΛV   H   (1)
 
     U is a unitary matrix with N B  rows and N B  columns. V is a unitary matrix with N A  rows and N A  columns. Λ is a complex matrix with N B  rows and N A  columns. The first to N B -th rows and the first to N B -th columns of Λ are a diagonal matrix. The elements on the diagonal lines in this diagonal matrix each correspond to a singular value. The (N B +1)-th to N A -th columns of Λ are a zero matrix. 
     The matrix V can be decomposed into a sub-matrix V 1  with first to N B -th columns and a sub-matrix Z with (N B +1)-th to NA-th columns ([V=V 1 , Z]). U, Λ, and V are obtained by performing singular value decomposition of the channel matrix H. Hence, HZ is a zero matrix. Z indicates a null space that corresponds to the wireless channel H. 
     The signal combiner  13  performs the precoding process by multiplying a signal vector formed from a data series and a plurality of artificial noise series by a vector V. The case depicted in  FIGS. 4-5  will be described as an example. N A  is 3 since the wireless device  10  includes three transmission antennas. It is assumed that the destination node  2  receives a wireless signal by using one reception antenna, and hence N B  is 1. 
     Assume that a column vector [s i , an 1   1 , an 2   1 ] T  formed from data S and artificial noises AN 1  and AN 2  in a first symbol is input to the signal combiner  13 . The signal combiner  13  multiplies this column vector by a complex matrix V. This multiply operation is expressed as formula (2), where X indicates a transmission signal vector generated by the signal combiner  13 . 
     
       
         
           
             
               
                 
                   X 
                   = 
                   
                     
                       ( 
                       
                         
                           
                             
                               v 
                               11 
                             
                           
                           
                             
                               z 
                               11 
                             
                           
                           
                             
                               z 
                               12 
                             
                           
                         
                         
                           
                             
                               v 
                               12 
                             
                           
                           
                             
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     Accordingly, transmission signals are expressed as formulae (3). 
         x 1= v   11   s   1   +z   11   an 1 1   +z   12   an 2 1    
         x 2= v   21   s   1   +z   21   an 1 1   +z   22   an 2 1    
         x 3= v   31   s   1   +z   31   an 1 1   +z   32   an 2 1   (3)
 
     Transmission signals x 1 , x 2 , and x 3  are output via the antennas A 1 , A 2 , and A 3 , respectively. 
     The destination node  2  receives the signals x 1 -x 3  transmitted from the wireless device  10 . Accordingly, a signal received by the destination node  2 , i.e., received signal r 1 , is expressed as formula (4), where nd indicates noise power at the destination node  2 . 
     
       
         
           
             
               
                 
                   
                     
                       
                         
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     As indicated above, since HZ is zero, artificial noise components are canceled out in the wireless channel H and becomes zero. Thus, the signal received by the destination node  2  includes no artificial noise components. Hence, the destination node  2  can recover the data symbol s 1  from the received signal r 1 . Subsequent data symbols are also recovered in a similar manner. 
     By contrast, a signal received by the interception node  3 , i.e., a received signal r 2 , is expressed as formula (5). In this formula, ne indicates noise power at the interception node  3 . 
     
       
         
           
             
               
                 
                   
                     
                       
                         
                           r 
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     However, there are no correlations between the wireless channel H between the wireless device  10  and the destination node  2  and the wireless channel G between the wireless device  10  and the interception node  3 . Thus, GZ is not zero, and the signal received by the interception node includes artificial noise components. Hence, the interception node  3  cannot recover the data from the received signal r 2 . 
     In the meantime, as described above, when a plurality of signals combined at a source node are independent of each other, the interception node  3  can separate these signals from each other with a high probability by using the ICA. Accordingly, the interception node  3  could decipher transmission data when there are no correlations between the transmission data and artificial noises. 
     However, unlike in the configuration depicted in  FIG. 2 , the wireless device  10  in accordance with the first embodiment generates the values of the symbols of artificial noise series according to transmission data, i.e., does not randomly generate such values. Thus, artificial noise series generated by the wireless device  10  are non-Gaussian distribution signals. In addition, there are correlations between a plurality of signals combined by the signal combiner  13 . Specifically, there are correlations between data S and an artificial noise AN 1 , and there are also correlations between artificial noises AN 1  and AN 2 . Hence, it will be difficult to separate data S and the artificial noises AN 1  and AN 2  from each other by using the ICA. 
       FIG. 8  illustrates an example of an effect achieved in accordance with the first embodiment. In this example, artificial noise series AN 1  and AN 2  are generated in the configuration depicted in  FIG. 5  by using the method illustrated in  FIG. 7 . QPSK is used as a modulation scheme. A threshold C S-AN  used in the process of generating the artificial noise AN 1  from data S is 0.5. A threshold C AN-AN  used in the process of generating the artificial noise AN 2  from the artificial noise AN 1  is 0.9. 
     In this example, the interception node  3  has a successful decipher rate of about 3 percent when the wireless device  10  in accordance with the first embodiment transmits data S. Accordingly, the wireless device  10  in accordance with the first embodiment reduces the successful decipher rate of the interception node  3  by less than one-tenth in comparison with the configuration depicted in  FIG. 2 . 
     Second Embodiment 
     The threshold C is determined in advance in the first embodiment. By contrast, in the second embodiment, the threshold C is determined in accordance with a communication environment or the like. 
       FIG. 9  illustrates an example of a wireless device in accordance with the second embodiment of the invention. A wireless device  30  includes a receiver  11 , a signal generator  12 , a signal combiner  13 , a transmitter  14 , a plurality of transmission antennas A 1 -A 3 , and a correlation coefficient calculator  31 . The receiver  11 , the signal generator  12 , the signal combiner  13 , the transmitter  14 , and the plurality of transmission antennas A 1 -A 3  in the second embodiment are substantially the same as those in the first embodiment. 
     As depicted in  FIG. 9 , the correlation coefficient calculator  31  determines a correlation coefficient in accordance with setting information and/or the state of a wireless channel. The correlation coefficient includes a coefficient indicating a correlation between a data series and artificial noise series and a coefficient indicating a correlation between the artificial noise series. 
     For example, the correlation coefficient calculator  31  may determine a correlation coefficient in accordance with a concealing capability demanded by a wireless communication system. When the interception node  3  attempts to separate a signal by using the ICA, a higher correlation coefficient will make transmission data less likely to be deciphered. Hence, when a high concealing capability is demanded, the correlation coefficient calculator  31  will preferably set a high correlation coefficient. Meanwhile, when a low concealing capability is demanded, the correlation coefficient calculator  31  may set a low correlation coefficient. In the example depicted in  FIG. 9 , the concealing capability demanded by the wireless communication system is reported to the correlation coefficient calculator  31  as setting information. 
     The correlation coefficient calculator  31  may determine a correlation coefficient in accordance with the number of transmission antennas of the wireless device  30 . When there are many transmission antennas, there will be a large number of artificial noise series, thereby making transmission data unlikely to be deciphered. Hence, when there are many transmission antennas, the correlation coefficient calculator  31  may set a low correlation coefficient. When there are few transmission antennas, the correlation coefficient calculator  31  will preferably set a high correlation coefficient. In the example depicted in  FIG. 9 , the number of transmission antennas of the wireless device  30  is reported to the correlation coefficient calculator  31  as setting information. 
     A plurality of channels (or paths) are configured between a plurality of antennas of the source node and one or more antennas of the reception node. The degrees of the correlations between the channels are dependent on an environment where the source node and the reception node are provided. In particular, the correlation between channels is likely to be low in a multipath environment (e.g., indoor environment) where many reflections or diffractions occur. By contrast, the correlation between channels is likely to be high in an environment (e.g., outdoor open space) where multipath propagation rarely occurs. 
     When the correlation between channels is high, the correlation between signals received by the interception node  3  becomes high, and the analytical performance based on the ICA is likely to be low. Hence, when the correlation between channels is high, the correlation coefficient calculator  31  may set a low correlation coefficient. When the correlation between channels is low, the correlation coefficient calculator  31  will preferably set a high correlation coefficient. The wireless device  30  can estimate a multipath environment between the wireless device  30  and the destination node  2  (i.e., correlation between channels) by using a pilot signal transmitted from the destination node  2 . 
     The decipherability of the ICA is dependent on a modulation scheme for transmitting data. For example, a modulation scheme that involves a large number of bits per symbol may provide distribution of data signals mapped on a constellation that is close to Gaussian distribution. The deciphering based on the ICA is difficult to perform when the distribution of data signals is close to Gaussian distribution. Hence, when data is transmitted using a modulation scheme that involves a large number of bits per symbol, the coefficient correlation calculator  31  may set a low correlation coefficient. When data is transmitted using a modulation scheme that involves a small number of bits per symbol, the correlation coefficient calculator  31  will preferably set a high correlation coefficient. In the example depicted in  FIG. 9 , the modulation scheme for transmitting data is reported to the correlation coefficient calculator  31  as setting information. 
     For example, the determination of a correlation coefficient may be realized by referring a table depicted in  FIG. 10 . In this example, a correlation coefficient is set for a combination of the number of transmission antennas of the wireless device  30 , a modulation scheme, and a multipath environment. This relation is created in advance through, for example, a simulation or measurement. The correlation coefficient calculator  31  may determine a correlation coefficient by referring to the table depicted in  FIG. 10  according to setting information and channel information. 
     The correlation coefficient is used as the threshold C in the example depicted in  FIG. 5 or 7 . Accordingly, a higher correlation coefficient will provide a higher correlation between series. In particular, as a correlation coefficient to be used as the threshold C S-AN  increases, the correlation between data and an artificial noise becomes higher. Meanwhile, as a correlation coefficient to be used as the threshold C AN-AN  increases, the correlation between artificial noises becomes higher. 
     As described above, when the interception node  3  uses the ICA, a higher correlation coefficient will make transmission data less likely to be deciphered. Thus, using a higher correlation coefficient will increase the concealing capability. However, when the correlation coefficient is high, deciphering one of a plurality of signal series is likely to result in the deciphering of the other series as well. Thus, an excessively high correlation coefficient could lead to a decreased concealing capability. Accordingly, a correlation coefficient will preferably be determined with these facts taken into consideration. 
     For example, when the wireless communication system demands a low concealing capability, decreasing the correlation coefficient between transmission data and artificial noises may be prioritized over decreasing the correlation coefficient between the artificial noises. In this case, even if the artificial noises are deciphered, it will be difficult to estimate the transmission data from the artificial noises. 
     Third Embodiment 
     In the first and second embodiments, an artificial noise series AN 1  is generated from a data series S, and an artificial noise series AN 2  is generated from the artificial noise series AN 1 . By contrast, in the third embodiment, artificial noise series AN 1  and AN 2  are generated from a data series S. 
       FIG. 11  illustrates an example of a signal generator in accordance with the third embodiment. In the third embodiment, a signal generator  12   a  includes correlation series generators  21   a  and  22   a  in place of the correlation series generators  21  and  22  depicted in  FIG. 5 . The correlation series generator  21   a  is substantially the same as the correlation series generator  21  and generates an artificial noise series AN 1  from a data series S. In the meantime, the correlation series generator  22   a  generates an artificial noise series AN 2  from the data series S, unlike the correlation series generator  22 . 
     The number of symbols of the data series S and the numbers of symbols of the individual artificial noise series AN 1  and AN 2  are equal. The threshold C S-AN ′ used by the correlation series generator  21   a  and the threshold C S-AN2  used by the correlation series generator  22   a  may be the same or different from each other. The configurations and operations of the receiver  11 , the signal combiner  13 , the transmitter  14 , and the mappers  23 - 25  are substantially the same in the first to third embodiments. 
     Fourth Embodiment 
     In the first to third embodiments, there are correlations between transmission data and artificial noises. In the fourth embodiment, by contrast, artificial noises are generated independently of transmission data. 
       FIG. 12  illustrates an example of a signal generator in accordance with the fourth embodiment. In the fourth embodiment, a signal generator  12   b  includes a correlation series generator  26  in place of the correlation series generators  21  and  22  depicted in  FIG. 5 . The correlation series generator  26  generates artificial noise series AN 1  and AN 2  independently of a data series S. Thus, there are no correlations between the data series S and the artificial noise series AN 1  and AN 2 . However, both of the numbers of symbols of the artificial noise series AN 1  and AN 2  are equal to that of the data series S. Meanwhile, there are correlations between the artificial noise series AN 1  and AN 2 . The degree of correlation between the artificial noise series AN 1  and AN 2  is designated by the threshold C. 
     Variation 
     In the examples described above, the wireless device includes three transmission antennas, and three signal series (data series S and artificial noise series AN 1  and AN 2 ) are combined and output. However, the present invention is not limited to this configuration. In particular, the wireless device may include N (N is an integer that is 4 or larger) transmission antennas and combine and output N signal series. In this case, the first artificial noise series is generated from the data series, and an i-th (i=2 to N−1) artificial noise series is generated according to an (i−1)-th artificial noise series. As a result, (N−1) artificial noise series are generated. Then, the data series and the (N−1) artificial noise series are combined and output. 
     In the examples described above, the wireless device  10  or  30  is operated as the base station  1  depicted in  FIG. 1 . However, the present invention is not limited to this configuration. In particular, the wireless device  10  or  30  may be operated as the terminal device depicted in  FIG. 1  or as any other wireless device. 
     Hardware Configuration 
       FIG. 13  illustrates an example of the hardware configuration of a wireless device. In this example, the wireless device includes a receiver circuit  41 , a processor  42 , a memory  43 , and a transmitter circuit  44 . The receiver circuit  41  corresponds to the receiver  11  depicted in  FIG. 4  and receives and demodulates a wireless signal. The processor  42  provides the functions of the signal generator  12  and the signal combiner  13  by executing a program stored in the memory  43 . In this case, the program describes the procedures of the flowcharts depicted in  FIGS. 6-7 . The transmitter circuit  44  corresponds to the transmitter  14  depicted in  FIG. 4  and outputs a transmission signal via an antenna. 
     All examples and conditional language provided herein are intended for the pedagogical purposes of aiding the reader in understanding the invention and the concepts contributed by the inventor to further the art, and are not to be construed as limitations to such specifically recited examples and conditions, nor does the organization of such examples in the specification relate to a showing of the superiority and inferiority of the invention. Although one or more embodiments of the present inventions have been described in detail, it should be understood that the various changes, substitutions, and alterations could be made hereto without departing from the spirit and scope of the invention.