<p>The extensive growth in wireless communications leads to spectrum scarcity. Since the spectrum is limited spectrum usage is clogged. The best possible solution is usage of cognitive radio. A cognitive radio network with sender, receiver and intermediate devices as relays is analyzed. The channel is modelled with noise considerations, path loss and variance. The system is defined with one primary sender and one primary receiver, in between them five secondary users and two active users. The signals from all these paths are estimated and analyzed to draw the best signal with good signal to noise ratio (SNR). To improve the channel efficiency and quality, we have considered various diversity techniques for which the fading problem of channel can be eliminated. In view of this, we concentrated on improving the system performance with various diversity techniques and optimum weight adaptation concept.</p>
In this paper, we consider the case where two communicating cognitive radio users are not near to each other or have no direct line of sight(LOS). Some secondary users don't need the entire spectrum available to them because of their traffic demand being low. If we are able to use this unused spectrum to relay the data of other secondary users through these rich nodes, the performance of the system can be improved. In cognitive systems, that are based on OFDM channel, the different resources such as subcarrier pairing, relays to be selected for pairing and powers allocated to relays must be optimized in a way to minimize the induced interference to primary users and maximum throughput is achieved. We propose an algorithm that allocates jointly the different resources with less complexity. Performance of the system, by using the rich nodes as relays, over the OFDM channel after allocating the resources is discussed through the simulation.Index terms-Non line of sight cognitive radio system; rich nodes; cooperative relaying; OFDM; underlay; resource allocation.
Spectrum sensing is the mission of finding the licensed user signal situation, i.e. to determine the existence and deficiency of primary (licensed) user signal, the recent publications random matrix theory algorithms performs better-quality in spectrum sensing. The RMT fundamental nature is to make use of the distributed extremal eigenvalues of the arrived signal sample covariance matrix (SMC), specifically, Tracy-Widom (TW) distribution which is useful to certain extent in spectrum sensing but demanding for numerical evaluations because there is absence of closed-form expression in it. The sample covariance matrix determinant is designed for two novel volume-based detectors or signal existence and deficiency cases are differentiated by using volume. Under the Gaussian noise postulation one of the detectors theoretical decision thresholds is perfectly calculated by using Random matrix theory. The volume-based detectors efficiency is shown in simulation results.
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