Mendeley TY _ JOUR ID - 2022021934192 TI - A Novel Detector based on Compressive Sensing for Uplink Massive MIMO Systems JO - Journal of Information Systems and Telecommunication (JIST) JA - ES LA - en SN - 2322-1437 AU - AU - Akhavan Amir AD - دانشگاه صنعتی اصفهان AD - Tehran university Y1 - 2022 PY - 2022 VL - 40 IS - SP - 249 EP - 256 KW - Massive MIMO KW - MMSE Detector KW - Error Recovery KW - Compressive Sensing KW - Iteratively Reweighted Least Squares (IRLS) Method. DO - N2 - Massive multiple-input multiple-output is a promising technology in future communication networks where a large number of antennas are used. It provides huge advantages to the future communication systems in data rate, the quality of services, energy efficiency, and spectral efficiency. Linear detection algorithms can achieve a near-optimal performance in large-scale MIMO systems, due to the asymptotic orthogonal channel property. But, the performance of linear MIMO detectors degrades when the number of transmit antennas is close to the number of receive antennas (loaded scenario). Therefore, this paper proposes a series of detectors for large MIMO systems, which is capable of achieving promising performance in loaded scenarios. The main idea is to improve the performance of the detector by finding the hidden sparsity in the residual error of the received signal. At the first step, the conventional MIMO model is converted into the sparse model via the symbol error vector obtained from a linear detector. With the aid of the compressive sensing methods, the incorrectly detected symbols are recovered and performance improvement in the detector output is obtained. Different sparse recovery algorithms have been considered to reconstruct the sparse error signal. This study reveals that error recovery by imposing sparse constraint would decrease the bit error rate of the MIMO detector. Simulation results show that the iteratively reweighted least squares method achieves the best performance among other sparse recovery methods. UR - rimag.ir/en/Article/34192 L1 - rimag.ir/en/Article/Download/34192 ER -