User/relay selection is a simple technique that achieves spatial diversity in multiuser networks. However, for user/relay selection algorithms to make a selection decision, channel state information (CSI) from all cooperating users/relays is usually required at a central node. This requirement poses two important challenges. Firstly, CSI acquisition generates a great deal of feedback overhead (air-time) that could result in significant transmission delays. Secondly, the fed-back channel information is usually corrupted by additive noise. This could lead to transmission outages if the central node selects the set of cooperating relays based on inaccurate feedback information. Motivated by the aforementioned challenges, we propose a limited feedback user/relay selection scheme that is based on the theory of compressed sensing. Firstly, we introduce a limited feedback relay selection algorithm for a multicast relay network. The proposed algorithm exploits the theory of compressive sensing to first obtain the identity of the “strong” relays with limited feedback air-time. Following that, the CSI of the selected relays is estimated using minimum mean square error estimation without any additional feedback. To minimize the effect of noise on the fed-back CSI, we introduce a back-off strategy that optimally backs-off on the noisy received CSI. In the second part of the thesis, we propose a feedback reduction scheme for full-duplex relay-aided multiuser networks. The proposed scheme permits the base station (BS) to obtain channel state information (CSI) from a subset of strong users under substantially reduced feedback overhead. More specifically, we cast the problem of user identification and CSI estimation as a block sparse signal recovery problem in compressive sensing (CS). Using existing CS block recovery algorithms, we first obtain the identity of the strong users and then estimate their CSI using the best linear unbiased estimator (BLUE). Moreover, we derive the error covariance matrix of the post-detection noise to be used in the back-off strategy. In addition to this, we provide exact closed form expressions for the average maximum equivalent SNR at the destination user. The last part of the thesis treats the problem of user selection in a network MIMO setting. We propose a distributed user selection strategy that is based on a well known technique called semi-orthogonal user selection when the zero-forcing beamforming (ZFBF) is adopted. Usually this technique requires perfect channel state information at the transmitter (CSIT) which might not be available or need large feedback overhead. Instead, we propose a distributed user selection technique where no communication between base stations is needed. In order to reduce the feedback overhead, each user set a timer that is inversely proportional to his channel quality indicator (CQI). This technique will allow only the user with the highest CQI to feedback provided that the transmission time is shorter than the difference between his timer and the second strongest user timer, otherwise a collision will occur. In the case of collision, we propose another feedback strategy that is based on the theory of compressive sensing, where collision is allowed and each user encode its feedback using Gaussian codewords and feedback the combination at the same time with other users. We prove that the problem can be formulated as a block sparse recovery problem and that this approach is agnostic on the transmission time, thus it could be a good alternative to the timer approach when collision is dominant. Simulation results show that the proposed CS-based selection algorithms yield a rate performance that is close to the ones achieved when perfect CSI is available while consuming a small amount of feedback.

Cooperative and cognitive radio systems have been proposed as a solution to improve the quality-of-service (QoS) and spectrum efficiency of existing communication systems. The objective of this dissertation is to propose and analyze schemes for cooperative and cognitive radio systems considering real world scenarios and to make these technologies implementable. In most of the research on cooperative relaying, it has been assumed that the communicating nodes have perfect channel state information (CSI). However, in reality, this is not the case and the nodes may only have an estimate of the CSI or partial knowledge of the CSI. Thus, in this dissertation, depending on the amount of CSI available, novel receivers are proposed to improve the performance of amplify-and forward relaying. Specifically, new coherent receivers are derived which do not perform channel estimation at the destination by using the received pilot signals directly for decoding. The derived receivers are based on new metrics that use distribution of the channels and the noise to achieve improved symbol-error-rate (SER) performance. The SER performance of the derived receivers is further improved by utilizing the decision history in the receivers. In cases where receivers with low complexity are desired, novel non-coherent receiver which detects the signal without knowledge of CSI is proposed. In addition, new receivers are proposed for the situation when only partial CSI is available at the destination i.e. channel knowledge of either the source-relay link or the relay-destination link but not both, is available. These receivers are termed as `half-coherent receivers' since they have channel-state-information of only one of the two links in the system. In practical systems, the CSI at the communicating terminals becomes outdated due to the time varying nature of the channel and results in system performance degradation. In this dissertation, the impact of using outdated CSI for relay selection on the performance of a network where two sources communicate with each other via fixed-gain amplify-and-forward relays is studied and for a Rayleigh faded channel, closed-form expressions for the outage probability (OP), moment generating function (MGF) and SER are derived. Relay location is also taken into consideration and it is shown that the performance can be improved by placing the relay closer to the source whose channel is more outdated. Some practical issues encountered in cognitive radio systems (CRS) are also investigated. The QoS of CRS can be improved through spatial diversity which can be achieved by either using multiple antennas or exploiting the independent channels of each user in a multi-user network. In this dissertation, both approaches are examined and in multi-antenna CRS, transmit antenna selection (TAS) is proposed where as in a multi-user CRS, user selection is proposed to achieve performance gains. TAS reduces the implementation cost and complexity and thus makes CRS more feasible. Additionally, unlike previous works, in accordance with real world systems, the transmitter is assumed to have limited peak transmit power. For both these schemes, considering practical channel models, closed-form expression for the OP performance, SER performance and ergodic capacity (EC) are obtained and the performance in the asymptotic regimes is also studied. Furthermore, the OP performance is also analyzed taking into account the interference from the primary network on the cognitive network.

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