RETRACTED: Energy Efficient Antenna Selection Method for Massive MIMO System in Downlink Scenario

Abstract

Massive MIMO systems provide fast data speeds with a large number of antennas which leads to arise in the power consumption of the system. The basic concept behind massive MIMO is that base stations (BSs) with lots of antenna components supporting terminals over identical time-frequency spectrum. A promising method to improve energy efficiency for both present and future wireless communication systems is the massive multiple-input multiple-output (MIMO) system, which uses a large number of antennas. An increasing amount of energy is required to support the required quality of service due to the exponential expansion and requirement for high-speed wireless communications. As a result, energy-efficient communication has gained a lot of attention in transmission methods for limited energy resources. However, radio frequency (RF) chains can consume a significant amount of power, which presents significant issues. A common feature of numerous antennas is several RF chains, which are made up of filters, ADCs, mixers and amplifiers. Consequently, many RF chains improve the device's cost and hardware complexity. This study addresses the problem of transmitting RF chain configuration under total power limits in large MIMO systems with the goal of optimizing energy efficiency. This creates an optimization problem that decides how many antennas the gadget can employ in order to operate with maximum energy efficiency. The key goal is to choose a fixed number of antennas such that, based on the number of active user terminals that may vary over time, the device can function with a reduced subset of antennas. Thus, the RF chain structure may be ascertained and a minimum number of transmission antenna elements are selected to ensure energy efficiency by using antenna selection methods. The simulation's findings demonstrate how random antenna selection (RANDOM ANPUT SECTION) affects a huge MIMO system's energy efficiency when it uses NOMA and modulation methods to reduce power consumption. To maximize the capacity that was lost as a result of antenna selection, this NOMA and modulation scheme were employed.