281 research outputs found

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

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    © 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

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

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    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

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

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    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

    Joint Domain Based Massive Access for Small Packets Traffic of Uplink Wireless Channel

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    The fifth generation (5G) communication scenarios such as the cellular network and the emerging machine type communications will produce massive small packets. To support massive connectivity and avoid signaling overhead caused by the transmission of those small packets, this paper proposes a novel method to improve the transmission efficiency for massive connections of wireless uplink channel. The proposed method combines compressive sensing (CS) with power domain NOMA jointly, especially neither the scheduling nor the centralized power allocation is necessary in the method. Both the analysis and simulation show that the method can support up to two or three times overloading.Comment: 6 pages, 5 figures.submitted to globecom 201
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