Abstract
Full-spreading non-orthogonal multiple access (FS-NOMA) is one category of the candidate technologies designed to support massive connectivity in wireless communication systems. Before it can handle the massive volume of user connections, it is important for the FS-NOMA to develop a receiver that successfully decodes target data from non-orthogonally overlapped receiving signals. However, the decoding performance of conventional interference-cancellation (IC)-based receivers is far from optimal because of error-propagation problems. To improve the decoding performance, we propose a novel FS-NOMA receiver based on the tabu-search (TS) algorithm which is a sort of machine-learning algorithm. Specifically, a novel TS mechanism and a diversification scheme are proposed to overcome the inherent adverse conditions of FS-NOMA systems which lead the TS algorithm to local optima. Simulation results demonstrate that the proposed TS-based receiver has decoding performance that is superior to that of the conventional IC-based receiver. The results also show that the proposed receiver accommodates a higher number of user connections with a given packet drop rate threshold.
Highlights
It has been forecasted from both industry and academy that the ‘massive connectivity’ will play a pivotal role in future wireless networks [1]–[4]
The elements of the sequences are randomly selected from the set C = {1 + 1i, 1 − 1i, −1 + 1i, −1 − 1i, 1, −1, 1i, −1i, 0}, which is one of the common complex-type sequence types of Full-spreading non-orthogonal multiple access (FS-nonorthogonal multiple access (NOMA)) systems [16], [17], [23]
Regarding the transmitted block model, we drew from the recent documents from 3rd generation partnership project (3GPP) meetings which discuss the evaluating environment of uplink NOMA systems for massive machine type communications (mMTC) scenarios [41], [42], [52]
Summary
It has been forecasted from both industry and academy that the ‘massive connectivity’ will play a pivotal role in future wireless networks [1]–[4]. The SIC receiver has a chronic error propagation problem which degrades multi-user detection performance This propagation occurs more frequently in NOMA systems since the initial linear solutions are inaccurate. Thanks to the joint design combining a multi-user code, a detector and a decoder, the detection performance of the proposed receiver is within a mere 0.8dB of achieving the capacity limit of the MIMO-NOMA system. Is one of those sorts of combinatorial optimization problems whose solution spaces are composed of quantized symbol candidates, we propose a novel FS-NOMA receiver based on the tabu search algorithm to obtain near-optimal performance with low complexity. Since the complexity of the ML detector was proven to be an NP-hard [28], our attempt focused on obtaining a near-optimal solution with low complexity based on the e-TS algorithm proposed below
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