Low‐complexity detection for uplink massive MIMO SCMA systems

Sanjeev Sharma, Kuntal Deka, Baltasar Beferull‐Lozano
2020 IET Communications  
This paper presents a sparse code multiple access (SCMA) system with massive antennas at the base station. This system is referred to as M-SCMA system. A spectrally-efficient and massive access next-generation wireless network is realized through massive antennas and non-orthogonal SCMA techniques. Two detection algorithms, namely, modified message passing algorithm (MMPA) and extended message passing algorithm (EMPA) are proposed to detect multiple users' symbols in M-SCMA. A deep learning
more » ... A deep learning (DL)-based detection scheme is also proposed for M-SCMA so as to avoid channel estimation and to lower the detection complexity. Numerical results show that the DL-based detection has similar performance as MMPA even when the channel information is not estimated explicitly. Furthermore, authors also establish the sum rate trade-off between SCMA and orthogonal multiple access in a massive antenna system. The impact of various M-SCMA parameters such as the number of antennas and the overloading factor, on the proposed DL, MMPA, and EMPA-based detection are also investigated. Recently non-orthogonal multiple access (NOMA) schemes are gaining interest for 5G and beyond wireless networks [1-6] NOMA-based systems have higher spectral efficiency than the orthogonal multiple access (OMA). Therefore, NOMA can support higher user density in next-generation wireless networks. Furthermore, multiple input and multiple output (MIMO) technology also increases spectral efficiency and/or improves wireless networks' performance. Upcoming wireless networks will be massive MIMO-based to enhance a system's performance [7] [8] [9] . Therefore, NOMA and MIMO will play a crucial role to design next-generation networks. In the literature [1, 4, 10-15], NOMA techniques are categorized into two: power domain (PD) and code domain (CD). In CD-NOMA, the users occupy more than one orthogonal resources for communication and they are distinguished by different codewords. Examples for CD-NOMA include sparse code multiple access (SCMA) and pattern division multiple access (PDMA) methods. SCMA is more efficient than the PDMA due to high shaping and coding gain [16] . SCMA is gaining more interest than the PD-NOMA and PDMA [1] . There-This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. fore, in this paper, we focus on the design and analysis of massive MIMO-based uplink SCMA system. Related works: In [11], a beamforming technique is analysed for downlink NOMA system by considering the intra-beam interference in the system. However, [11] only focused on PD-NOMA based approach. In [10], a joint MIMO and SCMA detection is considered using message passing algorithm (MPA). However, the considered approach is analysed for only two antennas and has a very high complexity for large number of antennas. In [17] , downlink SCMA capacity is analysed using multiple antennas, however, symbol error rate (SER) is not considered in [17] . In [18] , spatial modulation SCMA system is analysed for small number of antennas. A space time block coding is also analysed in [19] for SCMA system. Furthermore, mostly work in MIMO-based NOMA systems are analysed for PD-NOMA in literature [20, 21] . Furthermore, some deep learning (DL)-based approaches are also analysed for SCMA system design [22, 23] . However, SCMA system with massive MIMO is not analysed by considering MPA or DL based detection method in SCMA literature. Therefore, it is interesting and useful to study a massive MIMO SCMA system by considering MPA or DL-based symbols detection. IET Commun. 2021;15:51-59. wileyonlinelibrary.com/iet-com 51
doi:10.1049/cmu2.12057 fatcat:yf66rge4mjccfczpgbq45gfzbi