2020/06/11 by Mohammad Vahid Jamali, Jamali, Mohammad Vahid, Hessam Mahdavifar +1
Engineering · #Advanced Wireless Communication Technologies #FOS: Computer and information sciences #FOS: Electrical engineering #Information Theory (cs.IT) #Optical Wireless Communication Technologies #PAPR reduction in OFDM #Signal Processing (eess.SP) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2006.06917
openalex publication_date 2020/06/11 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28
In this paper, we present a low-complexity recursive approach for massive and\nscalable code-domain nonorthogonal multiple access (NOMA) with applications to\nemerging low-capacity scenarios. The problem definition in this paper is\ninspired by three major requirements of the next generations of wireless\nnetworks. Firstly, the proposed scheme is particularly beneficial in\nlow-capacity regimes which is important in practical scenarios of utmost\ninterest such as the Internet-of-Things (IoT) and massive machine-type\ncommunication (mMTC). Secondly, we employ code-domain NOMA to efficiently share\nthe scarce common resources among the users. Finally, the proposed recursive\napproach enables code-domain NOMA with low-complexity detection algorithms that\nare scalable with the number of users to satisfy the requirements of massive\nconnectivity. To this end, we propose a novel encoding and decoding scheme for\ncode-domain NOMA based on factorizing the pattern matrix, for assigning the\navailable resource elements to the users, as the Kronecker product of several\nsmaller factor matrices. As a result, both the pattern matrix design at the\ntransmitter side and the mixed symbols' detection at the receiver side can be\nperformed over matrices with dimensions that are much smaller than the overall\npattern matrix. Consequently, this leads to significant reduction in both the\ncomplexity and the latency of the detection. We present the detection algorithm\nfor the general case of factor matrices. The proposed algorithm involves\nseveral recursions each involving certain sets of equations corresponding to a\ncertain factor matrix. We then characterize the system performance in terms of\naverage sum rate, latency, and detection complexity. Our latency and complexity\nanalysis confirm the superiority of our proposed scheme in enabling large\npattern matrices.\n