Near-Optimal Energy-Efficient Joint Resource Allocation for Multi-Hop MIMO-AF Systems

Energy efficiency (EE) is becoming an important performance indicator for ensuring both the economical and environmental sustainability of the next generation of communication networks. Equally, cooperative communication is an effective way of improving communication system performances. In this paper, we propose a near-optimal energy-efficient joint resource allocation algorithm for multi-hop multiple-input-multiple-output (MIMO) amplify-and-forward (AF) systems. We first show how to simplify the multivariate unconstrained EE-based problem, based on the fact that this problem has a unique optimal solution, and then solve it by means of a low-complexity algorithm. We compare our approach with classic optimization tools in terms of energy efficiency as well as complexity, and results indicate the near-optimality and low-complexity of our approach. As an application, we use our approach to compare the EE of multi-hop MIMO-AF with MIMO systems and our results show that the former outperforms the latter mainly when the direct link quality is poor

Employing Antenna Selection to Improve Energy-Efficiency in Massive MIMO Systems

Massive MIMO systems promise high data rates by employing large number of antennas, which also increases the power usage of the system as a consequence. This creates an optimization problem which specifies how many antennas the system should employ in order to operate with maximal energy efficiency. Our main goal is to consider a base station with a fixed number of antennas, such that the system can operate with a smaller subset of antennas according to the number of active user terminals, which may vary over time. Thus, in this paper we propose an antenna selection algorithm which selects the best antennas according to the better channel conditions with respect to the users, aiming at improving the overall energy efficiency. Then, due to the complexity of the mathematical formulation, a tight approximation for the consumed power is presented, using the Wishart theorem, and it is used to find a deterministic formulation for the energy efficiency. Simulation results show that the approximation is quite tight and that there is significant improvement in terms of energy efficiency when antenna selection is employed.Comment: To appear in Transactions on Emerging Telecommunications Technologies, 12 pages, 8 figures, 2 table

Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication

The adoption of a Reconfigurable Intelligent Surface (RIS) for downlink multi-user communication from a multi-antenna base station is investigated in this paper. We develop energy-efficient designs for both the transmit power allocation and the phase shifts of the surface reflecting elements, subject to individual link budget guarantees for the mobile users. This leads to non-convex design optimization problems for which to tackle we propose two computationally affordable approaches, capitalizing on alternating maximization, gradient descent search, and sequential fractional programming. Specifically, one algorithm employs gradient descent for obtaining the RIS phase coefficients, and fractional programming for optimal transmit power allocation. Instead, the second algorithm employs sequential fractional programming for the optimization of the RIS phase shifts. In addition, a realistic power consumption model for RIS-based systems is presented, and the performance of the proposed methods is analyzed in a realistic outdoor environment. In particular, our results show that the proposed RIS-based resource allocation methods are able to provide up to $300\%$ higher energy efficiency, in comparison with the use of regular multi-antenna amplify-and-forward relaying.Comment: Accepted by IEEE TWC; additional materials on the topic are included in the 2018 conference publications at ICASSP (https://ieeexplore.ieee.org/abstract/document/8461496) and GLOBECOM 2018 (arXiv:1809.05397

Energy efficiency of some non-cooperative, cooperative and hybrid communication schemes in multi-relay WSNs

In this paper we analyze the energy efficiency of single-hop, multi-hop, cooperative selective decode-and-forward, cooperative incremental decode-and-forward, and even the combination of cooperative and non-cooperative schemes, in wireless sensor networks composed of several nodes. We assume that, as the sensor nodes can experience either non line-of-sight or some line-of-sight conditions, the Nakagami-m fading distribution is used to model the wireless environment. The energy efficiency analysis is constrained by a target outage probability and an end-to-end throughput. Our results show that in most scenarios cooperative incremental schemes are more energy efficient than the other methods

A Survey of Physical Layer Security Techniques for 5G Wireless Networks and Challenges Ahead

Physical layer security which safeguards data confidentiality based on the information-theoretic approaches has received significant research interest recently. The key idea behind physical layer security is to utilize the intrinsic randomness of the transmission channel to guarantee the security in physical layer. The evolution towards 5G wireless communications poses new challenges for physical layer security research. This paper provides a latest survey of the physical layer security research on various promising 5G technologies, including physical layer security coding, massive multiple-input multiple-output, millimeter wave communications, heterogeneous networks, non-orthogonal multiple access, full duplex technology, etc. Technical challenges which remain unresolved at the time of writing are summarized and the future trends of physical layer security in 5G and beyond are discussed.Comment: To appear in IEEE Journal on Selected Areas in Communication