2 research outputs found

    Throughput Maximization of Cognitive Radio Multi Relay Network with Interference Management

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    In this paper, an Orthogonal Frequency Division Multiplexing (OFDM) based cognitive multi relay network is investigated to maximize the transmission rate of the cognitive radio (CR) with enhanced  fairness among CR users  with interference to the primary users (PUs) being managed below a certain threshold level. In order to improve the transmission rate of the CR, optimization of the subcarrier pairing and power allocation is to be carried out simultaneously. Firstly joint optimization problem is formulated and Composite Genetic and Ordered Subcarrier Pairing (CGOSP) algorithm is proposed to solve the problem. The motivation behind merging genetic and OSP algorithm is to reduce the complexity of Genetic Algorithm (GA). Further, to have a fair allocation of resources among CR users, the Round Robin allocation method is adopted so as to allocate subcarrier pairs to relays efficiently. The degree of fairness of the system is calculated using Jain’s Fairness Index (JFI). Simulation results demonstrate the significant improvement in transmission rate of the CR, low computational complexity and enhanced fairness

    Resource Allocation in OFDM-Based Cognitive Two-Way Relay Networks

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    Cognitive radio (CR), nowadays, is considered as one of the most promising techniques which introduce the flexible usage of radio spectrum and improve the spectral efficiency by enabling unlicensed users to exploit the licensed spectrum in an opportunistic manner. Moreover, the two-way relay communication has attracted a great attention as it introduces a relaying scheme with a bidirectional transmission to exchange information between two nodes. This strategy assumed to improve the overall capacity, since less time slots are needed than the one-way strategy, besides extending the radio coverage range of networks. Another common technique that improves the bandwidth efficiency and spectrum utilization is the orthogonal frequency division multiplexing (OFDM) technique which exhibits a distinctive efficiency in mitigating inter-symbol interference (ISI) and combating frequency selective fading. Therefore, two-way relay CR communication among OFDM terminals can take advantage of these three techniques to boost up the capacity together with the networks quality. In this thesis, an OFDM-based amplify and forward (AF), cognitive two-way multiple-relay network is considered where two transceiver nodes exchange information via relay nodes. The full transmission happens in two time slots. In the first time slot, multiple access phase (MA), the transceiver nodes send their signals to the relay nodes while in the second time slot, broadcast phase (BC), the relay nodes broadcast the received signals to the transceivers. In this dissertation, the problem to jointly optimize the network resources is considered. The first is the transmission power of transceivers and relay nodes to ensure suitable allocated power for best signals transmission besides ensuring no harmful interference is caused to the primary system. The other important resource to be optimized is the subcarrier pairing where the first and second time slots subcarriers have to be matched such that the subcarriers with the best conditions is reserved. The final tuned resource, in this work, is the relay selection where the relay node that assures the best transition of the received signal is selected. The dual decomposition technique is applied to get the optimal resource allocation. Moreover, suboptimal algorithms are proposed to perform the resource allocation reducing, significantly, the computational complexity compared with the optimal solution with small performance degradation. Finally, simulation results of the suggested AF OFDM cognitive relaying network are shown to compare the performance gain of the different algorithms which reveals that the proposed suboptimal algorithm achieves good performance with much less computational complexity than the optimal one
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