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Showing 1 to 3 of 3 for “"Beamformer Design"”.

  1. Structure-based learning via graph neural networks for multi-group multicast beamforming

    … multicast beamforming solution, they are designed under perfect channel state information (CSI) and need to be performed each time channel state information is updated. Due to the complexity involved in solving the problem, they lead to high computational run-time for largescale …

    uoit Repository record for Structure-based learning via graph neural networks for multi-group multicast beamforming (opens in a new tab)

  2. Array Signal Processing Algorithms for Beamforming and Direction Finding

    … direction of arrival (DOA) estimation. In the beamformer design, we employ the constrained minimum variance (CMV) and the constrained constant modulus (CCM) criteria to propose full-rank and reduced-rank adaptive algorithms. Specifically, for the full-rank algorithms, we present two …

    whiterose Repository record for Array Signal Processing Algorithms for Beamforming and Direction Finding (opens in a new tab)

  3. Successive convex approximation: analysis and applications

    The block coordinate descent (BCD) method is widely used for minimizing a continuous function f of several block variables. At each iteration of this method, a single block of variables is optimized, while the remaining variables are held fixed. To ensure the convergence of the BCD method, the …

    umn Repository record for Successive convex approximation: analysis and applications (opens in a new tab)