Joint Rate-and-Power Allocation for Multi-channel Spectrum Sharing Networks with Balanced QoS Provisioning and Power Saving

Authors:
Yuan Wu;Danny H. Tsang
Affiliations:
Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong, People's Republic of China;Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong, People's Republic of China
Venue:
Mobile Networks and Applications
Year:
2009

Citing 7
Cited 1

Matrix analysis

Matrix analysis
Parallel and Distributed Computation: Numerical Methods

Parallel and Distributed Computation: Numerical Methods
Convex Optimization

Convex Optimization
Optimal Linear Precoding Strategies for Wideband Noncooperative Systems Based on Game Theory—Part I: Nash Equilibria

IEEE Transactions on Signal Processing
Balancing transport and physical Layers in wireless multihop networks: jointly optimal congestion control and power control

IEEE Journal on Selected Areas in Communications
Spectrum sharing for unlicensed bands

IEEE Journal on Selected Areas in Communications
Convergence of Iterative Waterfilling Algorithm for Gaussian Interference Channels

IEEE Journal on Selected Areas in Communications

Comprehensive Capacity Ensured Distributed Binary Power Allocation in Dense Cognitive Networks

Journal of Network and Systems Management

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we study the joint rate-and-power allocation for multi-channel spectrum sharing networks with balanced QoS provisioning and power saving. We formulate this cross-layer optimization problem as a non-cooperative game G JRPA in which each user has a coupled two-tuple strategy, i.e., simultaneous rate and multi-channel power allocations. A multi-objective cost function is proposed to represent user's awareness of both QoS provisioning and power saving. We analyze the properties of Nash equilibrium (N.E.) for our G JRPA , including its existence, and properties of QoS provisioning and power saving. Furthermore, we derive a layered structure by applying the Lagrangian dual decomposition to G JRPA and design a distributed algorithm to find the N.E.. Simulation results are presented to show the validity of our game theoretic formulation and the performance of our proposed algorithm. Detailed studies on the performance tradeoff between QoS provisioning and power saving are also carried out.