T.E. Biedka, "Subspace Constrained SCORE Algorithms," Proc. of Asilomar Conf. on Signals, Systems, and Computers, November 1993, pp. 716-720.  Home/Search   Document Not in Database   Summary   Related Articles   Check

.... training sequences introduce additional overhead, several blind interference cancellation techniques have recently MARCH 1999 IEEE SIGNAL PROCESSING MAGAZINE 27 been developed for time division multiple access (TDMA) and code division multiple access (CDMA) cellular systems [4] 9] 15] [29], 97] 207] 231] 300] Multiple criteria for blindly adapting the receiving pattern of an antenna array have been proposed over the last decade. The choice among these criteria depends on a priori knowledge of the signal of interest (SOI) Each proposed algorithm essentially exploits ....

....1 T o . For example, phase SCORE can separate sources of the same type, having the same symbol rate, symbol waveform, and finite alphabet. In order to accelerate the convergence rate of phase SCORE while achieving the optimum SINR, a subspace constrained phase SCORE algorithm was proposed in [29], which constrains the beamformer weights to lie in a lower dimensional subspace. Another class of blind adaptive beamforming algorithms for linearly modulated digital communication signals exploits the known finite alphabet of the transmitted signal. Examples include the iterative least squares ....

T.E. Biedka, "Subspace-constrained SCORE algorithms," Proc. 27th Asilomar Conf. on Signals, Systems, and Computers, Pacific Grove, CA, pp. 716-720, Nov. 1993.

....interferer was set at 14 ffi , and SER performance was computed as a function of the number of bauds used to train the beamformer weights of several blind adaptive algorithms. In addition to the DD approach, the constant modulus array (CMA) phase SCORE, and principle components (PC) phase SCORE [19] algorithms were tested. The CMA algorithm was implemented as described in [8] with p = 2 and = 0:0075 (the value of was chosen to be as large as possible while still yielding convergence) and both the CMA and DD approaches were initialized using a classical delay and sum beamformer steered ....

T. Biedka, "Subspace-Constrained SCORE Algorithms", In Proc. 27 th Asilomar Conference on Signals, Systems, and Computers, Asilomar, CA., November 1993.

....performance improvement, measured using either interference rejection capability or mean squared error. In addition, for simple additive unstructured calibration errors, the MAP approach is shown in certain cases to yield a beamformer similar to the subspace corrected algorithms described in [44, 45, 46, 47, 48, 49]. Before moving on to a description of the MAP techniques described above, some additional background information is given in the next two sections. Section 2 outlines the mathematical model that will be assumed throughout this work, and introduces some important notation. A description of some ....

T. Biedka, "Subspace-Constrained SCORE Algorithms", In Proc. 27 th Asilomar Conference on Signals, Systems, and Computers, pages 716--720, Asilomar, CA., November 1993.

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T.E. Biedka, "Subspace Constrained SCORE Algorithms," Proc. of Asilomar Conf. on Signals, Systems, and Computers, November 1993, pp. 716-720.

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T.E. Biedka. Subspace-constrained SCORE algorithms. In Proceedings of the Asilomar Conference on Signals, Systems and Computers, pages 716 -- 720, November 1993.

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