Multiantenna receivers are often deployed in cognitive radio systems for accurate spectrum sensing. However, correlation among signals received by multiple antennas in these receivers is often ignored which yields unrealistic results. In this paper, the effect of this correlation is accurately quantified by deriving analytical expressions for the average probability of detection. Alternative simpler expressions are also derived. These are done for selection combining (SC) and switch and stay combining (SSC) diversity techniques in dual arbitrarily correlated Nakagami-m fading channels. Then, it is repeated for triple exponentially and identically correlated Nakagami-m fading channels with SC diversity technique. Analysis results show that the interbranch correlation impacts the detector performance significantly, especially in deep fading scenarios. Also, SC outperforms SSC as expected. However, the difference between them becomes very small in low fading and highly correlated scenarios, which indicates that the simpler SSC scheme can as well be deployed in such situations.

Increasing number of antennas are closely packed in emerging multiantenna systems and correlation among them can no longer be ignored. In this paper, such a multiantenna spectrum sensing system is investigated considering dual, triple, four and up to infinite number of correlated antenna branches. Constant, arbitrary and exponential correlation among the antenna branches are considered. Closed form expressions for the detection probability, in terms of the confluent hypergeometric function, is derived assuming maximal ratio combining (MRC) and equal gain combining (EGC) diversity techniques in Nakagami-m multipath fading channel. Numerical results quantify the interbranch correlation that impacts the detector performance significantly. However, results also show that this effect could be compensated by employing the appropriate diversity combining technique and by increasing the diversity branches. Furthermore, we find that at high m values (Rician like channel), low false alarm probability and highly correlated environments, EGC which is a simpler scheme performs as good as MRC which is a more complex scheme.

Accurate detection of white spaces is crucial in cognitive radio networks. Initial investigations show that the accurate detection in a multiple primary users environment is challenging, especially under severe multipath conditions. Among many techniques, recently proposed eigenvalue-based detectors that use random matrix theories to eliminate the need of prior knowledge of the signals proved to be a solid approach. In this work, we study the effect of Rayleigh multipath fading channels on spectrum sensing in a multiple primary user environment for a pre-proposed detector called the spherical detector using the eigenvalue approach. Simulation results show interesting outcomes.

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In this work, we analyse the performance of Cognitive Radio Spectrum Sensing (CRSS) systems with multiple receiving antennas considering the effect of correlation among fading branches. Exact closed-form expressions for the average detection probabilities (P D ) are derived employing Probability Density Functions (PDF) approach for n.i.i.d.-L number of diversity branches over Nakagami-m fading channels with Maximal Ratio Combining (MRC) diversity. Performance analysis reveals the detrimental effect of the correlation on detection performance thus decreasing detection probability. However, results also show that this effect could be compensated through employing diversity combining technique and by increasing the diversity branches.