Abstract
We first address the problem of power allocation at cognitive users (CUs) to maximize the throughput of a nonselfish symbiotic cognitive radio scheme, in which the CUs may assist the data transmission of primary users (PUs) via nonorthogonal amplify-and-forward (AF) cognitive relaying and obtain an incentive time for their own data transmission in a nonselfish manner. Then, an optimal power allocation algorithm is proposed based on the full channel state information (CSI) among PUs, CUs, and base station (BS). In order to reduce the feedback overhead, another power allocation algorithm is devised based only on the partial CSI, that is, the CSI of BS-PU and the CSI of BS-CUs. Simulation results demonstrate that, compared with the optimal power allocation algorithm, the power allocation algorithm with only the partial CSI can achieve a similar performance with a smaller channel feedback overhead.
Highlights
With underutilized time or frequency resources, the Federal Communications Commission (FCC) has recommended that more efficient spectrum utilization could be realized by implementing devices that can coexist with licensed users or primary users (PUs) [1]
base station (BS) and cognitive users (CUs) always have the data for transmission and this situation can be regarded as the worst condition for the CUs in conventional cognitive radio scheme (CCR), since PUs always take the entire time and CUs can never transmit data to the AP
We evaluate the performance of CCR and nonselfish symbiotic cognitive relaying scheme (NSCRS) with different power allocation algorithms, that is, optimal power allocation algorithm (OPA), Partial CSI based power allocation algorithm (PPA), and equal power allocation algorithm (EPA), in terms of average throughput, average ratio of aggregated incentive time in the measurement time, and normalized average power consumption at the BS
Summary
With underutilized time or frequency resources, the Federal Communications Commission (FCC) has recommended that more efficient spectrum utilization could be realized by implementing devices that can coexist with licensed users or PUs [1]. In order to further enhance the performance of the cognitive network, the relay function is actively enabled at the CUs to assist the primary transmission, which may bring the benefits to the CUs, for example, creating more spectrum holes for the cognitive network. (Strictly speaking, this may not be said CR from its original point of view We call it cognitive relaying since CR concept and relay function are combined together.) For instance, rather than a passive approach in CCR, a spectrum leasing algorithm was introduced as an active approach, in which a common control channel was assumed for the CSI exchange and the decision delivery, for example, cooperation parameters and cooperation decision [7]. As a reward for the decode-and-forward (DF) cooperation from CUs, the PU might lease part of its own time slot to the cooperative CUs; a CU that cooperates with a PU is called a cooperative CU, and is the only user that can immediately access the channel in the leased time; this type of CU is called a selfish one
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