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Unraveling power spectra mixtures and finding the directions of the constituent sources can enable effective spatial occupancy prediction by location-dependent combining of the recovered source power spectra; and it is also useful for primary interference avoidance. Such unmixing and direction-finding is a challenging leap beyond ordinary ‘aggregate’ spectrum sensing. This paper presents a promising...
In real-world applications such as those for speech and audio, there are signals that are nonstationary but can be modeled as being stationary within local time frames. Such signals are generally called quasi-stationary or locally stationary signals. This paper considers the problem of direction-of-arrival (DOA) estimation of quasi-stationary signals. Specifically, in our problem formulation we assume:...
This paper addresses the problem of direction-of-arrival (DOA) estimation of quasi-stationary signals, which finds applications in array processing of speech and audio. By studying the subspace structures of the local second-order statistics (SOSs) of quasi-stationary signals, we develop a Khatri-Rao (KR) subspace approach that has two notable advantages. First, the approach can operate in underdetermined...
In this paper, a block-by-block blind channel estimation algorithm is proposed for a multiuser orthogonal frequency division multiplexing (OFDM) system with an antenna array at the base station and a single antenna at each mobile unit. Provided that the channel is static within an OFDM block (i.e., block fading channel), based on the subcarrier averaging the proposed channel estimation algorithm can...
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