Beamforming using the relevance vector machine
Proceedings of the 24th international conference on Machine learning
Cluster Characteristics in a MIMO Indoor Propagation Environment
IEEE Transactions on Wireless Communications
Cognitive radio: brain-empowered wireless communications
IEEE Journal on Selected Areas in Communications
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While regulations exist (or will exist) to guarantee that whitespace devices do not interfere with primary devices, how these devices will coexist with each other itself is typically left unspecified. In this paper we take a first step towards tackling the coexistence problem. Our approach is to build a wideband low power device which uses the entire available whitespace spectrum for transmission; and due to its low power nature causes minimal interference to other whitespace devices. To achieve reasonable speeds in spite of the low power transmission, we use spatial beamforming to steer away from harmful interference and achieve high throughput. In this paper we present a key building block towards this vision, an accurate and efficient detector to estimate what spatial degrees of freedom are occupied by other whitespace devices. We leverage the empirical observation that multipath channels are typically sparse, i.e., they usually have only a few paths where most of the signal energy is concentrated. We exploit this observation to build a compressive sensing based spatial DoF detector, and demonstrate via simulation that it significantly outperforms traditional approaches