# Real-Time Statistical Measurement of Wideband Signals Based on Software Defined Radio Technology
## 1 Introduction  
New communication technologies have led to significant shifts in the way the electromagnetic spectrum is used. Signals that generate electromagnetic fields, such as WLAN, LTE or 5G NR, exhibit quasi-stochastic variations, and their massive deployment is leading to an unprecedented increase in the density of electromagnetic spectrum consumption. Since 1980, mobile communications have been the technology with the most significant changes in system architecture, constantly focused on meeting the growing needs of users. The introduction of the third-generation communication networks (3G) in 2000 brought higher spectral efficiency and radio frequency bandwidths of up to 5 MHz [1, 2]. The 3G standard has been continuously improved to increase data throughput by implementing new enhancements such as High-Speed Packet Access (HSPA+) [3]. As 3G networks were unable to meet the ever-increasing demands for high data rates, the fourth-generation technology (4G) was introduced by the 3 rd Generation Partnership Project (3 GPP) to meet theserequirements. Although LTE is being promoted as a 4G standard, it does not fully meet the technical requirements set by the International Telecommunications Union (ITU) [4]. Even so, LTE is capable of delivering data rates of up to 300 Mbps through the use of scalable bandwidths from 1.4 MHz to 20 MHz, the implementation of a MIMO configuration of up to 4 \(\times\) 4 for download and 1 \(\times\) 1 for upload, and the first use of OFDM (Orthogonal Frequency Division Multiplexing). ITU technical requirements for 4G were met through the implementation of the LTE-Advanced (LTE-A) standard. LTE-A inherits existing LTE features but brings significant changes: aggregation of up to five carriers (5 \(\times\) 20 = 100 MHz) bandwidth, which implicitly increases throughput; use of 8 \(\times\) 8 MIMO configuration for download and 4 \(\times\) 4 for upload; implementation of new concepts such as Coordinated Multi-Point transmission and reception (CoMP) and improved Self-organizing Network (SON) [1]. LTE-A also uses OFDM technology, but 3 GPP is making some adjustments, such as using OFDMA for the download and SC-FDMA for the uplink. The use of OFDMA solves one of the most serious problems associated with increasing bit rates, namely intersymbol interference. The immunity to the effects of multiple reflections on the receiver channel capacity comes from the simple algorithm that the OFDMA system transmits information using multiple orthogonal narrowband subcarriers, where the bit rate for each subcarrier is inversely proportional to the total number of subcarriers. Depending on the bandwidth, we can have N subcarriers and the transmission on each subcarrier is performed at a bit rate of 1/N times the bit rate of the source signal [5]. Although OFDM is favored in 4G wireless communications for its ability to eliminate multipath fading and increase spectral efficiency, it has one major limitation: high peak-to-average power ratio (PAPR) [6; 7; 8]. The main common interest of these three papers is to study and improve the performance of wireless communication systems by addressing key issues such as reducing PAPR, improving spectral efficiency, and optimizing resource allocation in OFDMA and SC-FDMA technologies. The PAPR is further increased by the use of higher order modulation schemes: e.g., for GSM PAPR was 0.0 dB, for WCDMA 3.5 dB, for LTE 11 dB and for 5 GNR is 13 dB. For LTE networks, in the uplink, the high PAPR signal can be handled by a NodeB, in the downlink case the user equipment usually has limited battery power. Therefore, to increase the transmission efficiency and reduce the cost of using mobile station power amplifiers, the SC-FDMA technique is used for the uplink, with a significantly reduced PAPR compared to a standard OFDM signal [9]. The aforementioned research and many recent studies [10; 11] focus solely on PAPR reduction.