Abstract
Massive multi-input multi-output (MIMO) is envisioned as a key technology for the emerging fifth generation of communication networks (5G). However, considering the energy consumption of the large number of radio frequency (RF) chains, massive MIMO poses a problem to energy efficiency (EE) requirement of 5G. In this paper, we propose an energy-efficient power allocation method for millimeter-wave (mmWave) beamspace MIMO non-orthogonal multiple access (NOMA) systems, where there may be multiple users in each selected beam. First, according to the beam selection (BS) results, we get the precoding matrix through zero-forcing (ZF) beamforming method. Second, we formulate the energy efficiency (EE) maximization optimization problem as a fractional programming. Through sequential convex approximation (SCA) and second-order cone (SOC) transformation, the original optimization problem can be transformed to a convex optimization problem. By using iterative optimization algorithm, we can get the power allocation results. Then, we analyze the convergence of our proposed iterative optimization method and get that the solution in each iteration is a suboptimal solution to the original non-convex optimization problem. Simulation results show that the proposed energy-efficient power allocation scheme has better EE performance comparing with the conventional methods when the transmitted power exceeds the power threshold.
Highlights
With the rapid development of mobile Internet and Internet of things (IoT), there will be the prediction of 1000-fold data traffic increase by the year 2020 [1], [2]
SIMULATION RESULTS the performances of the proposed energyefficient power allocation method for millimeter wave (mmWave) beamspace multi-input multi-output (MIMO)-non-orthogonal multiple access (NOMA) scheme are evaluated through numerical simulations
The number of selected radio frequency (RF) chains is variable according to the different transmission strategies, which are based on different beam selection methods
Summary
With the rapid development of mobile Internet and Internet of things (IoT), there will be the prediction of 1000-fold data traffic increase by the year 2020 [1], [2]. P. Liu et al.: Energy-Efficient Power Allocation for mmWave Beamspace MIMO-NOMA Systems an EE-optimal power allocation strategy was proposed. Based on the Sherman-Morrison-Woodbury formula and iterative optimization method [27], the dynamic power allocation problem was solved for mmWave massive MIMO-NOMA with simultaneous wireless information and power transfer. We study on the energy-efficient power allocation method for mmWave beamspace MIMO-NOMA systems. Based on the BS method for mmWave beamspace MIMO-NOMA [26] and ZF beamforming technique, we formulate the energy-efficient power allocation problem as a non-convex fractional programming, which considers the constraints of all users, i.e., minimum rate constraints, successive interference cancellation (SIC) constraints and maximum power budget.
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