Contention-based nonorthogonal massive access with massive MIMO

The sporadic communication character of massive machine-type communication systems provides natural advantages to utilize the principle of compressive sensing (CS). However, due to the high computational complexity of CS algorithms, CS-based contention-free access schemes have limited scalability and high computational complexity for massive access with user-specific pilots. To address these problems, in this paper, we propose a new contention-based scheme for CS-based massive access, which can support the sporadic access of massive devices (more than one million devices) with limited resources. Furthermore, an advanced receiver algorithm is designed to solve the optimal solutions for the proposed scheme, which utilizes various prior information to enhance the performance. In specific, the joint sparsity between the channel and data is used to improve the accuracy of pilot detection, and the information of modulation and cyclic redundancy check is exploited for channel correction to improve the performance of data recovery. The simulation results show that the proposed scheme can achieve improved active user detection performance and data recovery accuracy than existing methods.