Separation of cochannel signals in TDMA mobile radio

Keerthi, A.V.; Shynk, J.J.

doi:10.1109/78.720371

Cited by 24 publications

(7 citation statements)

References 16 publications

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“…al provide a complete solution to the aforementioned asynchronous frame problem. Their decision-feedback based solution is similar to the approaches in [8,74]. The number of separated users is limited by the array size due to the linear beamforming operation.…”

Section: Nonlinear Techniquesmentioning

confidence: 99%

Overloaded array processing with spatially reduced search joint detection

Hicks

Bayram

Tranter

et al. 2001

IEEE J. Select. Areas Commun.

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Section: Nonlinear Techniquesmentioning

confidence: 99%

Overloaded array processing with spatially reduced search joint detection

Hicks

Bayram

Tranter

et al. 2001

IEEE J. Select. Areas Commun.

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“…It is similar to the SB algorithm employed for GSM signals [3], except that it employs different least-squares (LS) constraints. Computer simulations demonstrate that the modified SB algorithm successfully demodulates all the data in the cochannel bursts, and with a computational complexity lower than that of the sequential separation (SQ) algorithm presented in [4], [7]. The signal cancellation step is eliminated, thus avoiding any accumulation of errors that can occur with a series of signal cancellations.…”

Section: Resultsmentioning

confidence: 99%

“…The beamformer weights are computed using a least-squares algorithm, i.e., W H X ( k ) L=S t ( k ) (6) where { t ( k ) } is the training sequence of s or s t , as the case may be. For example, slot 1 is beamformed over the interval [6,161] using weights that satisfy w H x ( k ) % t l ( k ) , k E [14,27] (7) where { t l ( k ) } is the training sequence of slot 1, which is known at the receiver (because of the frame synchronization step). Note that slot 1 is further beamformed over the interval [O, 51 also using the weights in (7).…”

Section: Modified Sb Algorithmmentioning

confidence: 99%

“…For example, slot 1 is beamformed over the interval [6,161] using weights that satisfy w H x ( k ) % t l ( k ) , k E [14,27] (7) where { t l ( k ) } is the training sequence of slot 1, which is known at the receiver (because of the frame synchronization step). Note that slot 1 is further beamformed over the interval [O, 51 also using the weights in (7). Likewise, slot 3 is beamformed over the interval [168,310] (8) is not trained to reject the interference that occurs during these intervals.…”

Section: Modified Sb Algorithmmentioning

confidence: 99%

“…The linear equalizer weights h are chosen to compensate for the IS1 induced by the transmit filter. The training sequences for the beamformer are generated by convolving the original IS-136 synchronization sequences with the SRRC filter impulse response[7]. The training sequences for the linear equalizer are the same as the original IS-136 training sequences.…”

mentioning

confidence: 99%

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A modified sequential beamforming algorithm for cochannel IS-136 signals

Chandrasekaran

Keerthi²,

Shynk³

Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136)

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Cochannel signals in a time-division multiple-access (TDMA) cellular network interfere with each other in an asynchronous manner. I n order to demodulate one of these signals, the receiver must be able to separate the cochannel interferers for a variety of burst overlap scenarios. I n this paper, we present an adaptive beamforming algorithm that separates cochannel IS-136 signals using the known synchronization sequences. It employs constrained least-squares algorithms that process the antenna data in two sequential passes. In this way, the data are accurately beamformed within a burst even when the cochannel scenario changes during the burst.

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