Mobile Fog Computing-Assisted Resource Allocation for Two-Hop SWIPT OFDM Networks

The mobile fog computing-assisted resource allocation (RA) is studied for simultaneous wireless information and power transfer (SWIPT) two-hop orthogonal frequency division multiplexing (OFDM) networks, where a decode-and-forward (DF) relay first harvests energy from signals emitted by a source and then helps the source to forward information to its destination by using the harvested energy. Power splitting (PS) strategy is adopted at the relay and a different PS (DPS) receiver architecture is proposed, where the PS factors of all subcarriers are different. A RA problem is formulated to maximize the system’s achievable rate by jointly optimizing subcarrier pairing, power allocation, and PS factors. Since the RA problem is a nonconvex problem and is difficult to solve, an efficient RA algorithm is designed. As the wireless channels are fast time-varying, the computation is performed in mobile fog node close to end nodes, instead of remote clouds. Results demonstrate that the achievable rate is significantly increased by using the proposed RA algorithm. It is also found that the computation complexity of RA algorithm of DPS receiver architecture is much lower than the existing identical PS (IPS) receiver architecture, and thus the proposed DPS architecture is more suitable for computation-constrained fog system.

Throughput Maximization of Cognitive Radio Multi Relay Network with Interference Management

<span>In this paper, an Orthogonal Frequency Division Multiplexing (OFDM) based cognitive multi relay network is investigated to maximize the transmission rate of the cognitive radio (CR) with enhanced fairness among CR users with interference to the primary users (PUs) being managed below a certain threshold level. In order to improve the transmission rate of the CR, optimization of the subcarrier pairing and power allocation is to be carried out simultaneously. Firstly joint optimization problem is formulated and Composite Genetic and Ordered Subcarrier Pairing (CGOSP) algorithm is proposed to solve the problem. The motivation behind merging genetic and OSP algorithm is to reduce the complexity of Genetic Algorithm (GA). Further, to have a fair allocation of resources among CR users, the Round Robin allocation method is adopted so as to allocate subcarrier pairs to relays efficiently. The degree of fairness of the system is calculated using Jain’s Fairness Index (JFI). Simulation results demonstrate the significant improvement in transmission rate of the CR, low computational complexity and enhanced fairness.</span>

Energy Efficiency Maximized Resource Allocation for Opportunistic Relay-Aided OFDMA Downlink with Subcarrier Pairing

This paper studies the energy efficiency (EE) maximization for an orthogonal frequency division multiple access (OFDMA) downlink network aided by a relay station (RS) with subcarrier pairing. A highly flexible transmission protocol is considered, where each transmission is executed in two time slots. Every subcarrier in each slot can either be used in direct mode or be paired with a subcarrier in another slot to operate in relay mode. The resource allocation (RA) in such a network is highly complicated, because it has to determine the operation mode of subcarriers, the assignment of subcarriers to users, and the power allocation of the base station and RS. We first propose a mathematical description of the RA strategy. Then, a RA algorithm is derived to find the globally optimum RA to maximize the EE. Finally, we present extensive numerical results to show the impact of minimum required rate of the network, the user number, and the relay position on the maximum EE of the network.