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Abstract-We study the feasibility of cognitive radio (CR) communication in the presence of a K-user multi-input multioutput (MIMO) interference channel as the primary network. Assuming that the primary interference network has unused spatial degrees of freedom (DoFs), we first investigate the sufficient condition on the number of antennas at the secondary transmitter under which the secondary system can communicate while causing no interference to the primary receivers. We show that, to maximize the benefit, the secondary transmitter should have at least the same number of antennas as the spatial DoFs of the primary system. We then derive the secondary precoding and decoding matrices to have zero interference leakage into the primary network while the signal-to-interference plus noise ratio (SINR) at the secondary receiver is maximized. As the success of the secondary communication depends on the availability of unused DoFs, we then propose a fast sensing method based on the eigenvalue analysis of the received signal covariance matrix to determine the availability of unused DoFs or equivalently spatial holes. Since the proposed fast sensing method cannot identify the indices of inactive primary streams, we also provide a fine sensing method based on the generalized likelihood ratio test (GLRT) to decide the absence of individual primary streams. Simulation results show that the proposed CR sensing and transmission scheme can, in practice, provide a significant throughput while causing no interference to the primary receivers, and that the sensing detects the spatial holes of the primary network with high detection probability.Index Terms-Cognitive radio, K-user MIMO interference channel, interference alignment, null space sensing, spatial holes, eigenvalue-based sensing, GLRT detector.

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In this paper, the problems of relay selection and channel allocation in a cognitive two-way relay network are modelled as a classical weighted bipartite graph matching problem and are solved by the Hungarian algorithm. In the proposed radio resource management algorithm, firstly, some of cognitive radio (CR) nodes are selected to establish the primary user connection as a two-way relay scheme. Then, a power updating algorithm is used to give the maximum signal-to-interference-plus-noise ratio (SINR) in the CR nodes, while keeping the minimum SINR level at the primary transceivers and the best channel assignment is done for CR nodes in order to maximize the SINR value of them. Simulation results show that the proposed algorithm improves the performance of the whole network in comparison with conventional power allocation and relay selection algorithms.

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In this work, we consider a uni-directional (one way) relay network with a pair of primary transmitter and receiver which are relay-assisted by multiple cognitive radio (CR) terminals. A CR base station is deployed to sense the absence/presence of the primary user based on the received signal-to-noise ratio (SNR) at the fusion center. The primary network utilizes a two-step one-way amplify-and-forward (AF) relaying scheme and uses the CRs as its relay nodes. In the first step of AF relaying, the primary transmitter sends its signal to the CRs/relays. A distributed beamforming is then performed in the second step of relaying. In this phase, the CR base station sets the beamforming weights of CR terminals to satisfy the SNR requirements at the primary transmitter and at the CR base station. We aim at minimizing the power dissipated in the cognitive (relay) nodes together with ensuring an accurate spectrum sensing process. This optimization problem is efficiently solved by using semidefinite relaxation (SDR) techniques. Simulation results are provided to compare the relay transmit power in our investigated network with that in a conventional AF relay network.Cognitive radio, one-way relaying, convex optimization, distributed beamforming, relay networks, semidefinite relaxation.