For uplink massive MIMO systems with hundreds of antennas at the base station, the Linear Minimum Mean Square Error (MMSE) signal detection algorithm is near optimal but involves matrix inversion with high complexity. In this paper, we proposed a low complexity detection algorithm in uplink large-scale MIMO based on Reactive Tabu Search (RTS) algorithm by using SOR iterative algorithm as the initial solution vector algorithm. The simulation result shows that it can reduce the computational complexity from ο(K3) to ο(K2), where K is the number of users. Under the premise of BER performance of the original algorithm, the simulation result shows that the performance of SOR-RTS method is always close to the original RTS algorithm.
This paper focuses on the design of flexible and wearable antennas using textile substrates for wireless/satellite based communication and control systems supporting Internet of Things (IoT). The same are based on on-body communication in Wireless body area network (WBANs). The antennas are designed using two different textile substrates i.e. Jeans and Polyester with εr of 1.7 and 2.8 respectively. The substrates are selected for the ease of wearability and the compact size of the designed antennas. The antennas are designed to operate in the C-Band (4-8 GHz) which is popular for satellite communications. The reason that a higher frequency band is selected is to overcome the congestion issues in the lower satellite frequency bands. Various simulation parameters like bandwidth, reflection coefficient (S11), 2D and 3D radiation patterns, directivity, gain and efficiency of both the antennas are compared and analysed. The maximum achieved gain, bandwidth and efficiency are 3.8dBi, 9.8GHz and 88.4 % for jeans substrate antenna and 3.1dBi, 6.7GHz and 77.5% for polyester substrate antenna respectively. The antennas are designed using Agilent Advance Design System simulator.