Wireless Energy Harvesting For Autonomous Reconfigurable Intelligent Surfaces

in IEEE Transactions on Green Communications and Networking (in press)

Energy-Efficient Backscatter-Assisted Coded Cooperative-NOMA for B5G Wireless Communications

in IEEE Transactions on Green Communications and Networking (2022)

In this manuscript, we propose an alternating optimization framework to maximize the energy efficiency of a backscatter-enabled cooperative Non-orthogonal multiple access (NOMA) system by optimizing the ... [more ▼]

In this manuscript, we propose an alternating optimization framework to maximize the energy efficiency of a backscatter-enabled cooperative Non-orthogonal multiple access (NOMA) system by optimizing the transmit power of the source, power allocation coefficients (PAC), and power of the relay node under imperfect successive interference cancellation (SIC) decoding. A three-stage low-complexity energy-efficient alternating optimization algorithm is introduced which optimizes the transmit power, PAC, and relay power by considering the quality of service (QoS), power budget, and cooperation constraints. Subsequently, a joint channel coding framework is introduced to enhance the performance of far user which has no direct communication link with the base station (BS) and has bad channel conditions. In the destination node, the far user data is jointly decoded using a Sum-product algorithm (SPA) based joint iterative decoder realized by jointly-designed Quasi-cyclic Low-density parity-check (QC-LDPC) codes. Simulation results evince that the proposed backscatter-enabled cooperative NOMA system outperforms its counterpart by providing an efficient performance in terms of energy efficiency. Also, proposed jointly-designed QC-LDPC codes provide an excellent bit-error-rate (BER) performance by jointly decoding the far user data for considered BSC cooperative NOMA system with only a few decoding iterations. [less ▲]

EnPlace: Energy-Aware Network Partitioning for Controller Placement in SDN

in IEEE Transactions on Green Communications and Networking (2022)

This paper addresses the energy-aware controller placement problem (CPP) in Software-Defined Networking (SDN), considering the Internet of Things (IoT) flows. CPP involves partitioning the network into ... [more ▼]

This paper addresses the energy-aware controller placement problem (CPP) in Software-Defined Networking (SDN), considering the Internet of Things (IoT) flows. CPP involves partitioning the network into multiple subsets of switches with a single controller assigned to each subset. On the other hand, an energy-aware CPP reduces the energy consumption by link deactivation and ensures that each controller is reachable from the associated switches with a minimal set of active links. Existing literature considers static data traffic and out-of-band control plane having dedicated control links. However, the out-of-band control plane increases the infrastructure cost. Moreover, with IoT devices, SDN experiences uneven data traffic volume due to diverse activation models of the IoT devices. Hence, an energy-aware CPP should consider the effects of dynamic data traffic as improper controller placement and unplanned link deactivation cause link congestion and controller overload. In this work, we present an energy-aware controller placement scheme, named EnPlace, considering in-band control plane and IoT traffic. Additionally, we propose an energy-aware route selection scheme for existing flows. EnPlace increases energy savings significantly as compared to the existing works. In particular, for 200 IoT devices, the proposed scheme increases energy savings by 22.74% as compared to GreCo, an existing scheme. [less ▲]

Towards Optimal Energy Efficiency in Cell-Free Massive MIMO Systems

in IEEE Transactions on Green Communications and Networking (2021), 5(2), 816-831

Motivated by the ever-growing demand for green wireless communications and the advantages of cell-free (CF) massive multiple-input multiple-output (mMIMO) systems, we focus on the design of their downlink ... [more ▼]

Motivated by the ever-growing demand for green wireless communications and the advantages of cell-free (CF) massive multiple-input multiple-output (mMIMO) systems, we focus on the design of their downlink (DL) for optimal energy efficiency (EE). To address this fundamental topic, we assume that each access point (AP) is deployed with multiple antennas and serves multiple users on the same time-frequency resource while the APs are Poisson point process (PPP) distributed, which approaches realistically their opportunistic spatial randomness. Relied on tools from stochastic geometry, we derive a lower bound on the DL average achievable spectral efficiency (SE). Next, we consider a realistic power consumption model for CF mMIMO systems. These steps enable the formulation of a tractable optimization problem concerning the DL EE, which results in the analytical determination of the optimal pilot reuse factor, the AP density, and the number of AP antennas and users that maximize the EE. Hence, we provide useful design guidelines for CF mMIMO systems relating to fundamental system variables towards optimal EE. Among the results, we observe that an optimal pilot reuse factor and AP density exist, while larger values result in an increase of the interference, and subsequently, lower EE. Overall, it is shown that the CF mMIMO technology is a promising candidate for next-generation networks achieving simultaneously high SE and EE. [less ▲]

Feasible Point Pursuit and Successive Convex Approximation for Transmit Power Minimization in SWIPT-Multigroup Multicasting Systems

in IEEE Transactions on Green Communications and Networking (2021)

We consider three wireless multi-group (MG) multicasting (MC) systems capable of handling heterogeneous user types viz., information decoding (ID) specific users with conventional receiver architectures ... [more ▼]

We consider three wireless multi-group (MG) multicasting (MC) systems capable of handling heterogeneous user types viz., information decoding (ID) specific users with conventional receiver architectures, energy harvesting (EH) only users with non-linear EH module, and users with joint ID and EH capabilities having separate units for the two operations, respectively. Each user is categorized under unique group(s), which can be of MC type specifically meant for ID users, and/or an energy group consisting of EH explicit users. The joint ID and EH users are a part of both EH group and single MC group. We formulate an optimization problem to minimize the total transmit power with optimal precoder designs for the three aforementioned scenarios, under certain quality-of-service constraints. The problem may be adapted to the well-known semidefinite program and solved via relaxation of rank-1 constraint. However, this process leads to performance degradation in some cases, which increases with the rank of solution obtained from the relaxed problem. Hence, we develop a novel technique motivated by the feasible-point pursuit successive convex approximation method in order to address the rank-related issue. The benefits of proposed method are illustrated under various operating conditions and parameter values, with comparison between the three above-mentioned scenarios. [less ▲]

System Energy-Efficient Hybrid Beamforming for mmWave Multi-user Systems

in IEEE Transactions on Green Communications and Networking (2020), 4(4), 2473-2400

This paper develops energy-efficient hybrid beamforming designs for mmWave multi-user systems where analog precoding is realized by switches and phase shifters such that radio frequency (RF) chain to ... [more ▼]

This paper develops energy-efficient hybrid beamforming designs for mmWave multi-user systems where analog precoding is realized by switches and phase shifters such that radio frequency (RF) chain to transmit antenna connections can be switched off for energy saving. By explicitly considering the effect of each connection on the required power for baseband and RF signal processing, we describe the total power consumption in a sparsity form of the analog precoding matrix. However, these sparsity terms and sparsity-modulus constraints of the analog precoding make the system energy-efficiency maximization problem non-convex and challenging to solve. To tackle this problem, we first transform it into a subtractive-form weighted sum rate and power problem. A compressed sensing-based re-weighted quadratic-form relaxation method is employed to deal with the sparsity parts and the sparsity-modulus constraints. We then exploit alternating minimization of the mean-squared error to solve the equivalent problem where the digital precoding vectors and the analog precoding matrix are updated sequentially. The energy efficiency upper bound and a heuristic algorithm are also examined for comparison purposes. Numerical results confirm the superior performances of the proposed algorithm over benchmark energy-efficiency hybrid precoding algorithms and heuristic one. [less ▲]

Dynamic RF Chain Selection for Energy Efficient and Low Complexity Hybrid Beamforming in Millimeter Wave MIMO Systems

in IEEE Transactions on Green Communications and Networking (2019)

This paper proposes a novel architecture with a framework that dynamically activates the optimal number of radio frequency (RF) chains used to implement hybrid beamforming in a millimeter wave (mmWave ... [more ▼]

This paper proposes a novel architecture with a framework that dynamically activates the optimal number of radio frequency (RF) chains used to implement hybrid beamforming in a millimeter wave (mmWave) multiple-input and multiple-output (MIMO) system. We use fractional programming to solve an energy efficiency maximization problem and exploit the Dinkelbach method (DM)-based framework to optimize the number of active RF chains and data streams. This solution is updated dynamically based on the current channel conditions, where the analog/digital (A/D) hybrid precoder and combiner matrices at the transmitter and the receiver, respectively, are designed using a codebook-based fast approximation solution called gradient pursuit (GP). The GP algorithm shows less run time and complexity while compared to the state-of-the-art orthogonal matching pursuit (OMP) solution. The energy and spectral efficiency performance of the proposed framework is compared with the existing state-of-the-art solutions, such as the brute force (BF), the digital beamformer, and the analog beamformer. The codebook-free approaches to design the precoders and combiners, such as alternating direction method of multipliers (ADMMs) and singular value decomposition (SVD)-based solution are also shown to be incorporated into the proposed framework to achieve better energy efficiency performance. [less ▲]