Energy Efficiency Optimization Algorithm Research Articles

Energy efficiency optimization for SWIPT in K-user MIMO interference channels

In this paper, we investigate the energy efficiency (EE) for K-user multiple-input multiple-output (MIMO) interference channels with simultaneous wireless information and power transfer (SWIPT) and interference alignment (IA). Specifically, power splitting architecture is leveraged at each receiver for information decoding (ID) and energy harvesting simultaneously. Taking the quality of service (Qos) requirement and harvested power constraints into consideration, we maximize the system EE by jointly designing transmit beamformers, transmit power, power splitters and receive filters. To solve the nonconvex EE optimization problem, we first eliminate the interference among users for ID via the maximal signal to interference plus noise ratio (Max-SINR) IA method, which yields a two-dimensional EE optimization problem. And then, we propose an EE-Max algorithm coupled with the Max-SINR, nonlinear fraction programming and one dimension searching to solve the reformulated problem. Simulation results show the effectiveness of the proposed EE optimization algorithm and reveal the influence of the maximum transmit power constraint and the QoS requirement on the system EE.

Soft frequency reuse-based optimization algorithm for energy efficiency of multi-cell networks

This paper studies the optimization problem of energy efficiency in multi-cell networks with multiple users such as 5G network. However, the spectrum allocation and inter-cell interference (ICI) in multi-cell networks are the important challenges. The Soft Frequency Reuse (SFR) scheme which manages the spectrum and reduces ICI is used to build SFR-cellular networks. We take the global energy efficiency of the SFR-cellular network as the objective function of the optimal problem to obtain the maximum energy efficiency. Unfortunately, the objective function is a non-concave function, which is significantly difficult to be solved directly. Therefore, we utilize the fractional program, successive convex approximation, Lagrange dual, and Karush–Kuhn–Tucker (KKT) conditions to transform the objective function into a concave function. In such case, we could solve the problem with the convex optimization method. Finally, based on SFR, we propose a global energy efficiency optimization algorithm to search for the optimal energy efficiency of networks. Simulation results show that the proposed algorithm holds the better performance.

Low complexity energy optimization algorithm for massive MIMO systems

We consider the problem of nearly optimal energy efficiency in massive (Multiinput Multi-output) MIMO systems. Considering the correlated channel in practice, we derive the ergodic expression with zero-forcing precoding and analyze the simplified antennas selection method. Aiming at optimizing the energy efficiency, the closed form expressions of the nearly optimal number of transmit antennas and transmit power are given under the circuit consumption model. The joint solution of the number of transmit antennas and transmit power was replaced to only solve transmit power. Based on the expression only related with transmit power, we give an energy efficiency optimization algorithm. The simulation results show that the proposed algorithm can achieve nearly optimal energy efficiency with fast convergence speed.

Full-Duplex Versus Half-Duplex Amplify-and-Forward Relaying: Which is More Energy Efficient in 60-GHz Dual-Hop Indoor Wireless Systems?

We provide a comprehensive energy efficiency (EE) analysis of the full-duplex (FD) and half-duplex (HD) amplify-and-forward (AF) relay-assisted 60-GHz dual-hop indoor wireless systems, aiming to answer the question of which relaying mode is greener (more energy efficient) and to address the issue of EE optimization. We develop an opportunistic relaying mode selection scheme, where FD relaying with one-stage self-interference cancellation (passive suppression) or two-stage self-interference cancellation (passive suppression + analog cancellation) or HD relaying is opportunistically selected, together with transmission power adaptation, to maximize the EE with given channel gains. A low-complexity joint mode selection and EE optimization algorithm are proposed. We show a counter-intuitive finding that with a relatively loose maximum transmission power constraint, FD relaying with two-stage self-interference cancellation is preferable to both FD relaying with one-stage self-interference cancellation and HD relaying, resulting in a higher optimized EE. A full range of power consumption sources is considered to rationalize our analysis. The effects of imperfect self-interference cancellation at relay, drain efficiency, and static circuit power on EE are investigated. Simulation results verify our theoretical analysis.

Multi-Objective Energy Efficient Optimization Algorithm for Coverage Control in Wireless Sensor Networks

Multi-Objective Energy Efficient Optimization Algorithm for Coverage Control in Wireless Sensor Networks