In this chapter, the authors consider a multi-user multiple input multiple output (MU-MIMO) system and present the spectral efficiency (SE) performance analysis against pilot contamination mitigation with different parameters. The goal is to reach the maximum area throughput limit of a multi-cell Massive MIMO system by increasing bandwidth, cell density, and spectral efficiency. The SE, which makes use of the linear Zero Forcing uplink combining method, can be modeled under the Rician fading channel to assess the area throughput for such scenarios. In the case of uplinks, the base station (BS) is responsible for channel estimation. The proposed model incorporates various estimators such as Minimum Mean Square Error (MMSE), Element-Wise Minimum Mean Square Error estimators under Rician fading. The multi-cell scenarios with uplink (UL) massive MIMO have been analyzed using the proposed model under different cases such as pilot reuse factor, coherence block length, different numbers of antennas, and different estimators. Based on these parameters, the analysis and outcomes of the simulation are presented. It is discovered that employing an efficient pilot reuse factor, building multiple BS antennas, servicing multiple numbers of UEs per cell, and optimizing MMSE channel estimation utilizing ZF UL combiner can all improve the average summation of SE per cell. The MMSE and ZF uplink combining are found to be more suitable in improving SE as compared to MMSE-MR. The results show that the uplink SE of MMSE channel estimator for pilot reuse factors,1,3,4 is calculated as 22.5 bit/s/Hz/cell, 22.3 bit/s/Hz/cell and 21 bit/s/Hz/cell respectively. The uplink SE for EW-MMSE channel estimator with pilot reuse factors, 1, 3, 4 is calculated as 22.5bit/s/Hz/cell, 22 bit/s/Hz/cell and 22 bit/s/Hz/cell respectively. For the uplink SE of LS channel estimators, it can be 17.9bit/s/Hz/cell, 20.2 bit/s/Hz/cell, 20bit/s/Hz/cell with pilot reuse factors as f = 1, 3, 4 respectively. Therefore, for f=3, the maximum calculated uplink SE for MMSE, EW-MMSE, and LS is 17.6 bit/s/Hz/cell, 17.8bit/s/Hz/cell and 13bit/s/Hz/cell respectively. It is also observed that there is not much effect on coherence block as when it increases, the SE increases as well. Furthermore, the ZF uplink combining technique can suppress the coherence interference, and hence the average sum SE is enhanced with MMSE channel estimator and a pilot reuse factor of f=3 with ZF uplink combining. However, there is also a trade-off between the pilot contamination mitigation and the larger SE. Overall, this analysis provides valuable insights into the performance of MU-MIMO systems and the impact of different parameters on SE and pilot contamination mitigation.
Author(s) Details:
Rajeev Kumar Shakya,
Department of Electronics and Communication Engineering, School of Electrical Engineering and Computing, Adama Science and Technology University, Adama, P.O. Box 1888, Ethiopia.
Yibeltal Abebaw,
Department of Electronics and Communication Engineering, School of Electrical Engineering and Computing, Adama Science and Technology University, Adama, P.O. Box 1888, Ethiopia.
Demissie Jobir Gelmecha,
Department of Electronics and Communication Engineering, School of Electrical Engineering and Computing, Adama Science and Technology University, Adama, P.O. Box 1888, Ethiopia.
Eshetu Tessema Ware,
Department of Electronics and Communication Engineering, School of Electrical Engineering and Computing, Adama Science and Technology University, Adama, P.O. Box 1888, Ethiopia.
