Ahmad Alsharoa

Relay Selection and Resource Allocation for Two-Way DF-AF Cognitive Radio Networks

In this letter, the problem of relay selection and optimal resource allocation for two-way relaying cognitive radio networks using half duplex amplify-and-forward and decode-and-forward protocols is investigated. The primary and secondary users are assumed to access the spectrum simultaneously, in a way that the interference introduced to the primary users should be below a certain tolerated limit. Dual decomposition and subgradient methods are used to find the optimal power allocation. A suboptimal approach based on a genetic algorithm is also presented. Simulation results show that the proposed suboptimal algorithm offers a performance close to the optimal performance with a considerable complexity saving.

Optimal Transmit Power Allocation for MIMO Two-Way Cognitive Relay Networks with Multiple Relays using AF Strategy

In this letter, we consider a multiple-input multiple-output two-way cognitive radio system under a spectrum sharing scenario, where primary and secondary users operate on the same frequency band. The secondary terminals aims to exchange different messages with each other using multiple relays where each relay employs an amplify-and-forward strategy. The main objective of our work is to maximize the secondary sum rate allowed to share the spectrum with the primary users by respecting a primary user tolerated interference threshold. In this context, we derive an analytical expression of the optimal power allocated to each antenna of the terminals. We then discuss the impact of some system parameters on the performance in the numerical result section.

Transmit Power Minimization and Base Station Planning for High-Speed Trains With Multiple Moving Relays in OFDMA Systems

A high-speed railway system equipped with moving relay stations placed on the middle of the ceiling of each train wagon is investigated. The users inside the train are served in two hops via orthogonal frequency-division multiple-access (OFDMA) technology. In this paper, we first focus on minimizing the total downlink power consumption of the base station (BS) and the moving relays while respecting specific quality-of-service (QoS) constraints. We first derive the optimal resource-allocation solution, in terms of OFDMA subcarriers and power allocation, using the dual decomposition method. Then, we propose an efficient algorithm based on the Hungarian method to find a suboptimal but low-complexity solution. Moreover, we propose an OFDMA planning solution for high-speed trains by finding the maximal inter-BS distance, given the required user data rates to perform seamless handover. Our simulation results illustrate the performance of the proposed resource-allocation schemes in the case of Third-Generation Partnership Project (3GPP) Long-Term Evolution Advanced (LTE-A) and compare them with previously developed algorithms, as well as with the direct transmission scenario. Our results also highlight the significant planning gain obtained, owing to the use of multiple relays instead of the conventional single-relay scenario.

A Genetic Algorithm for Multiple Relay Selection in Two-Way Relaying Cognitive Radio Networks

In this paper, we investigate a multiple relay selection scheme for two-way relaying cognitive radio networks where primary users and secondary users operate on the same frequency band. More specifically, cooperative relays using Amplify-and- Forward (AF) protocol are optimally selected to maximize the sum rate of the secondary users without degrading the Quality of Service (QoS) of the primary users by respecting a tolerated interference threshold. A strong optimization tool based on genetic algorithm is employed to solve our formulated optimization problem where discrete relay power levels are considered. Our simulation results show that the practical heuristic approach achieves almost the same performance of the optimal multiple relay selection scheme either with discrete or continuous power distributions.

A low complexity algorithm for multiple relay selection in two-way relaying Cognitive Radio networks

In this paper, a multiple relay selection scheme for two-way relaying cognitive radio network is investigated. We consider a cooperative Cognitive Radio (CR) system with spectrum sharing scenario using Amplify-and-Forward (AF) protocol, where licensed users and unlicensed users operate on the same frequency band. The main objective is to maximize the sum rate of the unlicensed users allowed to share the spectrum with the licensed users by respecting a tolerated interference threshold. A practical low complexity heuristic approach is proposed to solve our formulated optimization problem. Selected numerical results show that the proposed algorithm reaches a performance close to the performance of the optimal multiple relay selection scheme either with discrete or continuous power distributions while providing a considerable saving in terms of computational complexity. In addition, these results show that our proposed scheme significantly outperforms the single relay selection scheme.

Hybrid Energy Harvesting-Based Cooperative Spectrum Sensing and Access in Heterogeneous Cognitive Radio Networks

In order to design energy efficient and energy harvesting (EEH) cooperative spectrum sensing (EEH-CSS), four fundamental constraints must be considered: 1) collision constraint to protect primary users from the collision with secondary users (SUs); 2) energy-causality constraint which states that the energy harvested by a time instant must be greater than or equal to the consumed energy until that time instant; 3) energy half-duplex (EHD) constraint which prevents the batteries from charging and discharging at the same time; and 4) correlation constraint which limits the information about the primary channel (PC) state of next time slot can be extracted from the current PC state. In this regard, we consider a hybrid energy harvesting SU (EH-SU) model which can harvest energy from both renewable sources, e.g., solar and ambient radio frequency signals. A heterogeneous EEH-CSS scheme is first proposed to handle EH-SUs with nonidentical harvesting, sensing, and reporting characteristics by permitting them to sense and report at different sensing accuracy. Formulating the energy state evolution of EH-SUs with and without EHD constraint, we analyze the asymptotic activity behavior of a single EH-SU by deriving the theoretical upper bound for the chance of being active to sense and transmit. Thereafter, we develop a convex framework to find maximum achievable total throughput by optimizing the asymptotic active probability, sensing duration, and detection threshold of each SU subject to above constraints. Given a potential set of SUs, determining the optimal subset of cooperating EH-SUs is of the essence to achieve maximum achievable total throughput. Since EH-SU selection is inherently a combinatorial problem, a fast yet high performance solution is proposed based on SUs’ energy harvesting, sensing, and reporting attributes. Finally, a myopic access procedure is developed to determine the active set of EH-SUs given the best subset of SUs.

Near-optimal power allocation with PSO algorithm for MIMO cognitive networks using multiple AF two-way relays

In this paper, the problem of power allocation for a multiple-input multiple-output two-way system is investigated in underlay Cognitive Radio (CR) set-up. In the CR underlay mode, secondary users are allowed to exploit the spectrum allocated to primary users in an opportunistic manner by respecting a tolerated temperature limit. The secondary networks employ an amplify-and-forward two-way relaying technique in order to maximize the sum rate under power budget and interference constraints. In this context, we formulate an optimization problem that is solved in two steps. First, we derive a closed-form expression of the optimal power allocated to terminals. Then, we employ a strong optimization tool based on particle swarm optimization algorithm to find the power allocated to secondary relays. Simulation results demonstrate the efficiency of the proposed solution and analyze the impact of some system parameters on the achieved performance.

Green Networking in Cellular HetNets: A Unified Radio Resource Management Framework With Base Station ON/OFF Switching

In this paper, the problem of energy efficiency in cellular heterogeneous networks (HetNets) is investigated using radio resource and power management combined with the base station (BS) ON/OFF switching. The objective is to minimize the total power consumption of the network while satisfying the quality of service requirements of each connected user. We consider the case of coexisting macrocell BS, small cell BSs, and private femtocell access points (FAPs). Three different network scenarios are investigated, depending on the status of the FAPs, i.e., HetNets without FAPs, HetNets with closed FAPs, and HetNets with semiclosed FAPs. A unified framework is proposed to simultaneously allocate spectrum resources to users in an energy efficient manner and switch OFF redundant small cell BSs. The high complexity dual decomposition technique is employed to achieve optimal solutions for the problem. A low complexity iterative algorithm is also proposed and its performances are compared to those of the optimal technique. The particularly interesting case of semiclosed FAPs, in which the FAPs accept to serve external users, achieves the highest energy efficiency due to increased degrees of freedom. In this paper, a cooperation scheme between FAPs and mobile operator is also investigated. The incentives for FAPs, e.g., renewable energy sharing and roaming prices, enabling cooperation are discussed to be considered as a useful guideline for interoperator agreements.

Wireless RF-based energy harvesting for two-way relaying systems

In this paper, we investigate the Energy Harvesting (EH)-based two-way relaying system using Amplify-and-Forward (AF) and Decode-and-Forward (DF) strategies. The relay is considered as an EH node that harvests the received Radio Frequency (RF) signal and uses this harvested energy to forward the information. Two relaying protocols based on Time Switching (TS) and Power Splitting (PS) receiver architectures are proposed to enable EH and information processing at the relay. Analytical throughput expressions are derived and optimized for both protocols. The goal is to find the optimal TS and PS ratios that maximize the total throughput Numerical results illustrate the performance of TS and PS protocols for different strategies, and show that at high signal-to-noise ratio, PS is superior to TS, and AF is superior to DF in terms of achievable sum-rate.

Energy-efficient two-hop LTE resource allocation in high speed trains with moving relays

High-speed railway system equipped with moving relay stations placed on the middle of the ceiling of each train wagon is investigated. The users inside the train are served in two hops via the 3GPP Long Term Evolution (LTE) technology. The objective of this work is to maximize the number of served users by respecting a specific quality-of-service constraint while minimizing the total power consumption of the eNodeB and the moving relays. We propose an efficient algorithm based on the Hungarian method to find the optimal resource allocation over the LTE resource blocks in order to serve the maximum number of users with the minimum power consumption. Moreover, we derive a closed-form expression for the power allocation problem. Our simulation results illustrate the performance of the proposed scheme and compare it with various previously developed algorithms as well as with the direct transmission scenario.