Abstract
<p>In order to guarantee the quality of service (QoS) for primary users (PUs) and secondary users (SUs) in fading channel, a distributed power control algorithm is proposed based on convex optimization theory in underlay OFDM cognitive radio networks (CRNs). Our purpose obtains the maximum transmit data rate of each SU at all subcarriers under three constraints of the maximum allowable transmission power, the minimum signal to interference plus ratio (SINR) of each SU and the maximum allowable interference generated from SUs to PU at each subcarrier. Simulation results show that the performance of the proposed algorithms (m2) are superior to the geometric programming algorithm (m1) in fading channel environment.</p>
Highlights
As the explosive growth of wireless communication services and applications, the limited spectrum resources becomes increasingly crowded and have not satisfied the growing needs of people [1]
We focus on underlay cognitive radio networks (CRNs) [4,5] with multiple primary users (PUs) and multiple secondary users (SUs) to study resource allocation problem
In [6], a distributed power control algorithm based on a cooperative game theoretic is proposed which satisfied the interference power constraint to protect transmission quality of service (QoS) of PUs
Summary
As the explosive growth of wireless communication services and applications, the limited spectrum resources becomes increasingly crowded and have not satisfied the growing needs of people [1]. Radio resource allocation based orthogonal frequency division multiple access (OFDMA) in cognitive radio networks is proposed to aim at maximizing secondary users throughput under the interference constraint of PUs in [7]. Based on the above discuss, in this paper, a distributed power control algorithm is proposed to minimum the interference power from SU-Tx to PU-Rx based on convex optimization theory in underlay OFDM CRNs. In order to guarantee communication quality of PUs and SUs in fading channel, our proposed power control scheme considers that the transmit power of each SU at all subcarriers should not exceed its maximum power, and takes the minimum SINR at secondary receivers (SUTxs) and the interference temperature threshold in each subcarrier into account. Simulation results show that the proposed algorithm is superior to algorithms (m2) are superior to the geometric programming algorithm (m1) [11] in fading channel environment
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