M2M Random Access Detection Algorithm In LTE System

As a key technology to implement Internet of Things(Io T), Machine-to-Machine(M2M) communication is a crucial business growth point of the next generation of LTE wireless communication, which is called the third revolution of information industry. However, the existing cellular networks are designed based on the communication characteristics of Human-to-Human(H2H) and the number of terminals is limited. Therefore, loading massive MTC terminals in the LTE system will be a huge challenge to the existing cellular networks. The first challenge is that when the massive machine type communication(MTC) terminals access to the base station, it may easily lead to the overload of random access channel. To address this problem, the existing literatures mainly focus on the MAC protocol modification and resource allocation improvement. But the research of receiver detection algorithm can be more direct and effective for capacity enhancement of random access, so the main point of this thesis is focused on the research of M2 M random access detection of LTE systems.Since the relative speeds between different MTC terminals and base station are different and the Doppler shifts caused by relative motion will have a greater impact on detection performances, we consider two scenarios with low-speed and high-speed, respectively, to investigate the detection algorithms of M2 M random access. In the low-speed case, we firstly elaborate the existing algorithms, such as the conventional correlation detection algorithm, the generalized likelihood ratio test algorithm and the iterative parallel interference cancellation algorithm. Then we modify the iterative parallel interference cancellation algorithm based on the analysis of multiple access interference. Through accurate interference reconstruction and cancellation, the modified algorithm can achieve performance improvements both in terms of detection and parameter estimation compared to the existing algorithms. When it comes to the high-speed scene, we analyze the impact of frequency offset on the correlation detection first. Then by referring to the iterative parallel interference cancellation algorithm in the low-speed scene, a multi-steps hybrid multiuser detection algorithm based on frequency offset compensation is proposed. This algorithm can not only improve the detection performance, but also improve the parameter estimation, especially the frequency offset estimation performance. By building MATLAB simulation platform of LTE system, performances of the above algorithms have been verified by simulations.The proposed random access multi-user detection algorithms have great significance for improving the random access capacity of LTE system and addressing the random access channel blocking problems caused by the access of massive MTC terminals.