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Group detection (GD), the combination of maximum likelihood (ML) decoding and linear processing for multiple antenna systems, has been shown to attain reasonable performance and practical complexity. However, the diversity gain of conventional GD degrades since the degrees of freedom at the receive antennas are exploited for the linear processing before the local ML search. This paper proposes a novel GD with overlapped grouping. The proposed GD employs selection diversity within the overlapped signals by using the likelihood value, after the local ML search. Therefore, the proposed GD can achieve higher diversity gain compared with the conventional GD.

MUSIC (multiple signal classification) has been widely used to estimate the direction of arrivals (DOAs) accurately. However, this method requires a large calculation time for eigen-decomposition of the covariance matrix. This paper presents a high-speed DOA estimation based on the beamspace MUSIC, which can reduce the order of the covariance matrix. The proposed method implements a two-step DOA estimation. The first step is the coarse estimation in which the DOAs are roughly estimated. The second step is the fine estimation in which the result of the coarse estimation is exploited and the DOAs are accurately estimated.

A new adaptive null forming algorithm for phased arrays has been proposed. The algorithm to control phase weights, based on constrained power minimization (CPM), uses only the array output power and does not require the complex baseband signals from individual array elements. The derivation of parameters for the iterative control from the deviation of the array output power by phase weight perturbation is described. Numerical simulations show that the proposed algorithm can direct a null to an interferer while maintaining the gain to the desired signal.