Abstract
Massive multiinput-multioutput (M-MIMO) systems are crucial for maximizing energy efficiency (EE) in fifth-generation (5G) wireless networks. A M-MIMO system's achievable high data rate is highly related to the number of antennas, but increasing the number of antennas the system raises energy consumption. In this paper, we derive ergodic EE based on the optimal transmit power and joint optimization antenna selection (AS) with impact pilot reuse sequences (PRSs). We apply Newton's method and the Lagrange multiplier to derive jointly optimized AS and optimal transmission power under the effect of PRSs. The proposed algorithm prevents repeated searching for joint optimal AS and optimal transmission power to reduce the complexity caused by an increasing number of antennas. From the simulation results, we conclude that EE could be maximized by employing the minimal PRSs and transmission power that are greater than the circuit's power consumption. The proposed algorithm offers maximum EE by repeating a minimizing pilot signal until the optimal AS and transmission power are achieved.
Highlights
Massive multiinput-multioutput systems are an exciting area of study and an important technology for fifthgeneration (5G) wireless networks that support high-data-rate traffic
We studied the joint optimal antenna selection (AS) and optimal transmission power of UEs under the effect of pilot reuse sequences (PRSs)
We formulated the problem of transmission power and AS under effect pilot sequences by applying Newton’s method and Lagrange multipliers to reduce the complexity of the iteration for AS and transmission power
Summary
Massive multiinput-multioutput systems are an exciting area of study and an important technology for fifthgeneration (5G) wireless networks that support high-data-rate traffic. Improving energy efficiency (EE) in a massive multiinput-multioutput (M-MIMO) system depends on reducing transmission power per active user (UE) and per antenna. Regarding energy resources in cellular networks, power allocation algorithms require minimizing power consumption and maximizing the achievable data rate [2,3]. We derived an ergodic EE based on optimized AS and optimal transmission power with the impact of pilot interference by applying Newton’s method and the Lagrange multiplier This enabled us to reuse pilot sequences, minimize the total transmit power based on the proportional number of AS, and reduce the number of RF chains at the receiver by allocating every RF chain to one of the massive receiver antennas
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