To overcome these issues, this PhD thesis proposes a design methodology that leverages both high-level synthesis tools and dynamic reconfiguration. However, main drawbacks of FPGA design are the level of the input description language that basically needs to be the hardware level, and, the reconfiguration time that may exceed run-time requirements if the complete FPGA is reconfigured. Thus, including FPGAs into the SDR concept may allow to support more waveforms with more strict requirements than a processor-based approach. Indeed, FPGAs have both high computing power and reconfiguration capacity. To tackle this issue, FPGA technology turns out to be a good alternative for implementing SDRs. However, it usually provides low computing capability and therefore low throughput performance. When relying on a software-based technology such as microprocessors, this approach is clearly flexible and quite easy to design. It can be easily reprogrammed at a software level to implement different waveforms. Software defined radio (SDR) is a promising technology to tackle flexibility requirements of new generations of communication standards. The results show that the detection algorithm can detect such small signals well, and has considerable reference value for the discovery of abnormal signals and subsequent tracking. Considering that some small signals have strong attenuation and high burstiness characteristics, we propose an abnormal signals detection method based on time series analysis which can identify such small signals in time. In this paper, the FM broadcast signal frequency bands are dynamically tracked, and the dynamic characteristics of the signal are deeply explored and analyzed. Moreover, various data analysis algorithms also allow us to analyze electromagnetic signals more flexibly and efficiently. With the proposed software-defined radio (SDR) concept, some new methods for analyzing wireless signal have emerged, but there are several researchers applying SDR method on electromagnetic signals analysis. However, because there is still a lack of supervision and control on wireless signals, it is difficult to detect and locate those malicious signals accurately in time, which poses great threats on social stability and people's property and privacy. In the condition, the significance of wireless security cannot be ignored. The wide use of wireless devices provides great convenience for people's communication in public and private. Nowadays, mobile wireless devices are becoming more and more indispensable. This article presents various applications areas of FPGAs for the upcoming 5G network planning. Dynamic reconfigurability and in-field programming features of FPGAs compared to fixed function ASICs help in developing better wireless systems. It can accelerate network performance without making a large investment in new hardware. As FPGA has the potential to be resource/power efficient, it can be used for building up constituents of 5G infrastructure. To provide individuals and companies with a real-time, social, and all connected experience, an end-to-end coordinated architecture which is agile and intelligent has to be designed at each stage. 5G promises a robust solution by offering ultra-low latency and high bandwidth for data transmission. This massive scaling of mobile communication requires higher bandwidth to operate. This evolution of communication will not only improve the performance of the existing networks, but will also enables various applications in other fields while integrating different heterogeneous systems. Next generation communication relies on standardized protocols, heterogeneous architectures and advanced technologies that are envisioned to bring ubiquitous and seamless connectivity.
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