PreRAKE diversity combining in time-division duplex CDMA mobile communications

Esmailzadeh, Riaz; Sourour, E.; Nakagawa, Masao

doi:10.1109/25.764996

Cited by 117 publications

(42 citation statements)

References 12 publications

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“…In recent years transmitter preprocessing techniques have received wide research attention [1]- [4], since the DownLink (DL) multiuser interference (MUI) may be mitigated by carrying out the required signal processing at the base-station (BS), where the associated complexity increase is less critical than at the mobile. Consequently, power-efficient and low-complexity mobile terminals (MTs) may be implemented.…”

Section: Introductionmentioning

confidence: 99%

“…In contrast to [1]- [4], where ideal knowledge of the DL CIRs was assumed, in this contribution we consider the more realistic transmitter preprocessing scenario, when the BS has limited and possibly channel-infested knowledge about the downlink CIRs, which are conveyed through noise feedback channels experiencing fading. When transmitter preprocessing is carried out under the above-mentioned realistic conditions, it is important to design efficient CIR-signalling schemes and to investigate the impact of the recovered imperfect CIR knowledge on the achievable performance.…”

Section: Introductionmentioning

confidence: 99%

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Performance of SDMA Systems Using Transmitter Preprocessing Based on Noisy Feedback of Vector-Quantized Channel Impulse Responses

Yang

Hanzo

2007

2007 IEEE 65th Vehicular Technology Conference - VTC2007-Spring

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Abstract-In this contribution we investigate the performance of Spatial Division Multiple Access (SDMA) multiple-input multiple-output (MIMO) systems using transmitter preprocessing, when the channel knowledge required for preprocessing is acquired by the receiver and conveyed to the transmitter via noise feedback channels that may also conflict fading. Specifically, in our system the MIMO channel impulse responses (CIRs) are vector quantized. Then, the CIR magnitudes and phases are conveyed to the transmitter via a feedback channel, which is noise contaminated and may also experience Rayleigh fading. At the transmitter, the CIRs used for transmit preprocessing are recovered using a soft estimator, which is optimum in the minimum mean-square error (MMSE) sense, and is implemented based on the so-called Hadamard soft-decoding principles. Our study and simulation results demonstrate that vector quantization combined with soft-decoding constitutes an efficient technique of feeding back the CIRs from the receiver to the transmitter. However, it is also known that the performance of the zero-forcing (ZF) or MMSE transmit preprocessing schemes is highly sensitive to the effect of quantization errors as well as to the feedback channel induced errors.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance of SDMA Systems Using Transmitter Preprocessing Based on Noisy Feedback of Vector-Quantized Channel Impulse Responses

Yang

Hanzo

2007

2007 IEEE 65th Vehicular Technology Conference - VTC2007-Spring

View full text Add to dashboard Cite

show abstract

“…Hence, one is only interested in their variances. Similar to the methodology given by Esmail-zadeh 8 , et al the variances of S and A and are evaluated conditioned on {b 1, l } and the final results are averaged over {b 1, l }.…”

Section: Performance Analysis Of Pre-rake Systemmentioning

confidence: 99%

“…Each rake finger despreads the spread spectrum (SS) signal on its assigned channel path. Using rake combining, the despread signals on all fingers are multiplied with the time-reversed complex conjugate of the path gains and all outputs are then added 8 . Hence, the receiver in both BS and MUs must be equipped with sufficient rake fingers and the corresponding channel estimation process.…”

Section: Performance Analysis Of Pre-rake Systemmentioning

confidence: 99%

“…Multiuser pre-rake estimates are available before transmission. Esmailzadeh 8 , et al and Song 9 , et al have shown that the performance of the pre-rake receiver (pre-rake function in transmitter and single-finger correlator in the receiver) is comparable to the rake receiver when orthogonal spreading codes are used, while it outperforms the rake receiver when nonorthogonal codes are used. Wan 10 , et al have shown that the pre-rake with generalised orthogonal (GO) codes outperforms the one with other spreading codes.…”

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confidence: 99%

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