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  4. Iterative Receivers for Downlink MIMO-SCMA: Message Passing and Distributed Cooperative Detection - 2018
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Category: MTech NS2 Projects
By MTech Projects
MTech Projects
28.Nov
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Iterative Receivers for Downlink MIMO-SCMA: Message Passing and Distributed Cooperative Detection - 2018

PROJECT TITLE :

Iterative Receivers for Downlink MIMO-SCMA: Message Passing and Distributed Cooperative Detection - 2018

ABSTRACT:

The fast development of mobile communications requires even higher spectral potency. Non-orthogonal multiple access (NOMA) has emerged as a promising technology to additional increase the access efficiency of wireless networks. Among many NOMA schemes, it has been shown that sparse code multiple access (SCMA) is ready to realize higher performance. In this Project, we consider a downlink MIMO-SCMA system over frequency selective fading channels. For optimal detection, the complexity will increase exponentially with the merchandise of the number of users, the number of antennas and also the channel length. To tackle this challenge, we have a tendency to propose near optimal low-complexity iterative receivers based mostly on issue graph. By introducing auxiliary variables, a stretched issue graph is constructed and a hybrid belief propagation (BP) and expectation propagation (EP) receiver, named stretch-BP-EP, is proposed. Considering the convergence problem of BP algorithm on loopy factor graph, we have a tendency to convexify the Bethe free energy and propose a convergence-guaranteed BP-EP receiver, named conv-BP-EP. We tend to any contemplate cooperative network and propose 2 distributed cooperative detection schemes to use the diversity gain, particularly, belief consensus-primarily based algorithm and the Bregman different direction methodology of multipliers (ADMM)-primarily based method. Simulation results verify the superior performance of the proposed conv-BP-EP receiver compared with different strategies. The two proposed distributed cooperative detection schemes can improve the bit error rate performance by exploiting the variety gain. Moreover, Bregman ADMM methodology outperforms the assumption consensus-based mostly algorithm in noisy inter-user links.

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