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QoS constrained resource allocation to secondary users in cognitive radio networks
Authors:Lutfa Akter  Balasubramaniam Natarajan
Affiliation:1. Department of Electrical Engineering, Stanford University, Stanford, CA, 94305, USA;2. Department of Management Sciences & Engineering, Stanford University, Stanford, CA, 94305, USA;1. Physical Research Laboratory, Ahmedabad 380009, India;2. Center for Atmospheric and Space Sciences, Utah State University, Logan, UT 84322, USA;3. Indian Institute of Geomagnetism, Navi Mumbai 410218, India;4. Space Physics Laboratory, Vikram Sarabhai Space Centre, Trivandrum 695022, India;5. Instituto Nacional de Pesquisas Espaciais-INPE, C.P. 515, 12201-970-Saõ José dos Campos, SP, Brazil
Abstract:In this paper, we consider a multi-channel cognitive radio network (CRN) where multiple secondary users share a single channel and multiple channels are simultaneously used by a single secondary user (SU) to satisfy their rate requirements. In such an environment, we attempt to evaluate the optimal power and rate distribution choices that each secondary user has to make in order to maintain their quality of service (QoS). Our measures for QoS include signal to interference plus noise ratio (SINR)/bit error rate (BER) and minimum rate requirement. We propose two centralized optimization frameworks in order to solve for the optimal resource management strategies. In the first framework, we determine the minimum transmit power that SUs should employ in order to maintain a certain SINR and use that result to calculate the optimal rate allocation strategy across channels. In the second framework, both transmit power and rate per channel are simultaneously optimized with the help of a bi-objective problem formulation. Unlike prior efforts, we transform the BER constraint into a convex constraint in order to guarantee optimality of the resulting solutions. Simulation results demonstrate that in both frameworks, optimal transmit power follows “reverse water filling” process and rate allocation follows SINR. We also observe that, due to the ability to adapt both power and rate simultaneously to attain a certain BER, the joint optimization framework results in a lower total transmit power than the two-stage approach.
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