Opportunistic Power Allocation Research Articles

Opportunistic power allocation strategies and fair subcarrier allocation in OFDM-based cognitive radio networks

In this paper we have studied the subcarrier and optimal power allocation strategy for OFDM-based cognitive radio (CR) networks. Firstly, in order to protect the primary user communication from the interference of the cognitive user transmissions in fading wireless channels, we design an opportunistic power control scheme to maximize the cognitive user capacity without degrading primary user's QoS. The mathematical optimization problem is formulated as maximizing the capacity of the secondary users under the interference constraint at the primary receiver and the Lagrange method is applied to obtain the optimal solution. Secondly, in order to limit the outage probability within primary user's tolerable range we analyze the outage probability of the primary user with respect to the interference power of the secondary user for imperfect CSI. Finally, in order to get the better tradeoff between fairness and system capacity in cognitive radio networks, we proposed an optimal algorithm of jointing subcarrier and power allocation scheme among multiple secondary users in OFDM-based cognitive radio networks. Simulation results demonstrate that our scheme can improve the capacity performance and efficiently guarantee the fairness of secondary users.

Scaling Law of an Opportunistic Power Allocation Scheme for Amplify-and-Forward Wireless Sensor Networks

In this letter, we address the problem of decentralized parameter estimation with Amplify-and-Forward Wireless Sensor Networks (WSNs). We focus on a previously proposed Opportunistic Power Allocation (OPA) scheme and derive the scaling law which determines how distortion decreases when the number of sensors grows without bound. Performance is assessed and compared with that of Uniform Power Allocation (UPA) and optimal Water-Filling (WF) strategies.

Improving the performance of space shift keying (SSK) modulation via opportunistic power allocation

In this Letter, we show that the performance of Space Shift Keying (SSK) modulation can be improved via opportunistic power allocation methods. For analytical tractability, we focus on a 2 × 1 Multiple-Input-Multiple-Output (MIMO) system setup over correlated Rayleigh fading channels. A closed-form solution of the optimal power allocation problem is derived, and it is shown that the transmit-power of each transmit-antenna should be chosen as a function of the power imbalance ratio and correlation coefficient of the transmit-receive wireless links. Numerical results are shown to substantiate the analytical derivation and the claimed performance improvement.

Opportunistic power allocation and sensor selection schemes for wireless sensor networks

In this letter, we analyze a class of Opportunistic Power Allocation (OPA) and sensor selection schemes for parameter estimation in wireless sensor networks. In all cases, only sensors experiencing favorable conditions participate in the estimation process by adjusting their transmit power on the basis of local Channel State Information (CSI) and Residual Energy Information. We address a number of classical problems: the minimization of distortion and transmit power, or the enhancement of network lifetime. Furthermore, we derive an improved version which is robust to CSI imperfections. Interestingly, the performance of OPA schemes are close to the optimal approaches.

Novel packet-level resource allocation with effective QoS provisioning for wireless mesh networks

Joint power-subcarrier-time resource allocation is imperative for wireless mesh networks due to the necessity of packet scheduling for quality-of-service (QoS) provisioning, multi-channel communications, and opportunistic power allocation. In this work, we propose an efficient intra-cluster packet-level resource allocation approach. Our approach takes power allocation, subcarrier allocation, packet scheduling, and QoS support into account. The proposed approach combines the merits of a Karush-Kuhn-Tucker (KKT)-driven approach and a genetic algorithm (GA)-based approach. It is shown to achieve a desired balance between time complexity and system performance. Bounds for the throughputs obtained by real-time and non-real-time traffic are also derived analytically.