Publication Type:

Journal Article

Source:

Wireless Personal Communications, Springer US, Volume 90, Number 3, p.1317–1329 (2016)

URL:

https://link.springer.com/article/10.1007/s11277-016-3392-8

Abstract:

Semidefinite relaxation detector is a promising approach to large-MIMO detection but for its computational complexity. The major computational cost is incurred in solving the semidefinite program (SDP). In this paper, we propose a sparse semidefinite relaxation (S-SDR) detector by reformulating the SDP problem thereby reducing the computational complexity. We formulate the system model using a sparse approach and further introduce a regularization term inducing sparsity into the semidefinite programming model. We provide a sparse formulation requiring approximately 50 % of the computations compared to the conventional semidefinite programming approach. We apply the proposed semidefinite relaxation detector in large-MIMO channels upto 100×100 systems and compare its BER performance and complexity. We observe that the BER performance is similar to the conventional semidefinite relaxation with the proposed S-SDR detector requiring relatively fewer computations.

Cite this Research Publication

Dr. Ramanathan R. and Dr. Jayakumar M., “A Low Complex Sparse Formulation of Semidefinite Relaxation Detector for Large-MIMO Systems Employing BPSK Constellations”, Wireless Personal Communications, vol. 90, pp. 1317–1329, 2016.

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