Investigation on Evolving Single-Carrier NOMA into Multi-Carrier NOMA in 5G

© 2013 IEEE. Non-orthogonal multiple access (NOMA) is one promising technology, which provides high system capacity, low latency, and massive connectivity, to address several challenges in the fifth-generation wireless systems. In this paper, we first reveal that the NOMA techniques have evolved from single-carrier NOMA (SC-NOMA) into multi-carrier NOMA (MC-NOMA). Then, we comprehensively investigated on the basic principles, enabling schemes and evaluations of the two most promising MC-NOMA techniques, namely sparse code multiple access (SCMA) and pattern division multiple access (PDMA). Meanwhile, we consider that the research challenges of SCMA and PDMA might be addressed with the stimulation of the advanced and matured progress in SC-NOMA. Finally, yet importantly, we investigate the emerging applications, and point out the future research trends of the MC-NOMA techniques, which could be straightforwardly inspired by the various deployments of SC-NOMA

Low-Complexity Expectation Propagation Detection for Uplink MIMO-SCMA Systems

We consider uplink sparse code multiple access (SCMA) systems associated with multiple input multiple output (MIMO), where the transmitters and the receiver are equipped with multiple antennas, for enhanced reliability (diversity gain) or improved data rate (multiplexing gain). For each diversity or multiplexing based MIMO scheme combined with SCMA, we develop low-complexity iterative detection algorithms based on the message passing algorithm (MPA) and the expectation propagation algorithm (EPA). We show that the MIMO-SCMA under EPA enjoys the salient advantage of linear complexity (in comparison to the MPA counterpart with exponential complexity) as well as enhanced error rate performances due to the MIMO transmission. We also show that the performance of EPA depends on the codebook size and the number of antennas

General Framework and Novel Transceiver Architecture based on Hybrid Beamforming for NOMA in Massive MIMO Channels

Massive MIMO and non-orthogonal multiple access (NOMA) are crucial methods for future wireless systems as they provide many advantages over conventional systems. Power domain NOMA methods are investigated in massive MIMO systems, whereas there is little work on integration of code domain NOMA and massive MIMO which is the subject of this study. We propose a general framework employing user-grouping based hybrid beamforming architecture for mm-wave massive MIMO systems where NOMA is considered as an intra-group process. It is shown that classical receivers of sparse code multiple access (SCMA) and multi-user shared access (MUSA) can be directly adapted. Additionally, a novel receiver architecture which is an improvement over classical one is proposed for uplink MUSA. This receiver makes MUSA preferable over SCMA for uplink transmission with lower complexity. We provide a lower bound on achievable information rate (AIR) as a performance measure. We show that code domain NOMA schemes outperform conventional methods with very limited number of radio frequency (RF) chains where users are spatially close to each other. Furthermore, we provide an analysis in terms of bit-error rate and AIR under different code length and overloading scenarios for uplink transmission where flexible structure of MUSA is exploited.Comment: Partially presented at IEEE ICC 2020 Workshop on NOMA for 5G and Beyond and to be submitted to IEEE Transactions on Communication

Sub-graph based joint sparse graph for sparse code multiple access systems

Sparse code multiple access (SCMA) is a promising air interface candidate technique for next generation mobile networks, especially for massive machine type communications (mMTC). In this paper, we design a LDPC coded SCMA detector by combining the sparse graphs of LDPC and SCMA into one joint sparse graph (JSG). In our proposed scheme, SCMA sparse graph (SSG) defined by small size indicator matrix is utilized to construct the JSG, which is termed as sub-graph based joint sparse graph of SCMA (SG-JSG-SCMA). In this paper, we first study the binary-LDPC (B-LDPC) coded SGJSG- SCMA system. To combine the SCMA variable node (SVN) and LDPC variable node (LVN) into one joint variable node (JVN), a non-binary LDPC (NB-LDPC) coded SG-JSG-SCMA is also proposed. Furthermore, to reduce the complexity of NBLDPC coded SG-JSG-SCMA, a joint trellis representation (JTR) is introduced to represent the search space of NB-LDPC coded SG-JSG-SCMA. Based on JTR, a low complexity joint trellis based detection and decoding (JTDD) algorithm is proposed to reduce the computational complexity of NB-LDPC coded SGJSG- SCMA system. According to the simulation results, SG-JSGSCMA brings significant performance improvement compare to the conventional receiver using the disjoint approach, and it can also outperform a Turbo-structured receiver with comparable complexity. Moreover, the joint approach also has advantages in terms of processing latency compare to the Turbo approaches

SCMA for Open-Loop Joint Transmission CoMP

Sparse Code Multiple Access (SCMA), a non-orthogonal multiple access scheme, has been introduced as a key 5G technology to improve spectral efficiency. In this work, we propose SCMA to enable open-loop coordinated multipoint (CoMP) joint transmission (JT). The scheme combines CoMP techniques with multi-user SCMA (MU-SCMA) in downlink. This scheme provides open-loop user multiplexing and JT in power and code domains, with robustness to mobility and low overhead of channel state information (CSI) acquisition. The combined scheme is called MU-SCMA-CoMP, in which SCMA layers and transmit power of multiple transmit points (TPs) are shared among multiple users while a user may receive multiple SCMA layers from multiple TPs within a CoMP cluster. The benefits of the proposed scheme includes: i) drastic overhead reduction of CSI acquisition, ii) significant increase in throughput and coverage, and iii) robustness to channel aging. Various algorithms of MU-SCMA-CoMP are presented, including the detection strategy, power sharing optimization, and scheduling. System level evaluation shows that the proposed schemes provide significant throughput and coverage gains over OFDMA for both pedestrian and vehicular users