Cognitive Radio (CR) is currently being seen as the future for wireless communications. Fundamental to the operation of a CR is the detection of presence of legacy communication. Energy detector (ED) is a simple and effective signal sensing method. However, the ED requires accurate estimation of the noise power. Any error in the estimation, which is common in practice, affects its performance. In this study we have looked at the detection problem using an antenna array. Under noise only case, the array covariance matrix has reasonably equal eigenvalues. On the other hand when a signal is present, the strongest eigenvalue is dissimilar to the rest. To measure the equality of the eigenvalues we use the sphericity test. We have found that under realistic assumptions about noise uncertainty and signal correlation the array based sphericity method of signal detection can perform better than the ED. Also, unlike the ED the sphericity test does not require any estimation of the noise power.

In low-power VLSI design good amount of power can be saved by using coding scheme such as Bus-Invert (BI). Such a coding scheme looks at successive words on a data bus and applies transformation to minimize the number of transitions. In this paper we propose Bus-Shift (BS) coding scheme that circularly shifts the data to minimize transitions. Power saving of BI is poor on average cases, and even that deteriorates with wider bus width. In comparison the proposed BS scheme performs better in both maximum and average cases. For wide bus the savings from BS gets slightly worse, but still performs better than BI. Simulation results show a saving margin of 14% in average cases for a 32 bit bus. Comparison is also made with Shift-Invert (SINV), another reported coding scheme. An implementation of BS in Cadence is presented.

Abstract-Signal detection problems are traditionally viewed as statistical hypothesis testing. In absence of the a priori probabilities, such as in radar, the Neyman-Pearson criterion is used where a certain false alarm probability is set, and the probability of detection is maximised. In signal sensing problems of cognitive radio, the main constraint is to avoid the interference with the primary user. Once this constraint is met, a cognitive radio can maximise its own chance of finding an empty spectrum. In this paper we emphasise this view of the signal sensing problem and modify the criterion such that a maximum miss-detection rate is specified. We have reformulated the energy detector showing that the sensing results have more meaningful explanations under the modified criterion. The effects of measurement errors are also considered.

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