Adaptive minimum bit-error rate beamforming

Chen, Sheng; Ahmad, Nazihah; Hanzo, Lajos

doi:10.1109/twc.2004.842981

Cited by 95 publications

(122 citation statements)

References 28 publications

(40 reference statements)

Supporting

Mentioning

122

Contrasting

Order By: Relevance

“…As recognised by Chen et al [13], the best strategy is to choose w by directly minimising the system's BER. Following the notations used in [13,20] …”

Section: Minimum Bit Error Rate Designmentioning

confidence: 99%

“…The BER of the beamformer for the desired user 1 with the weight vector w can be shown to be [13,20] …”

Section: Minimum Bit Error Rate Designmentioning

confidence: 99%

“…For a communication system, however, it is the bit error rate (BER) that really matters. Adaptive beamforming based on directly minimising the system's BER has been proposed for binary phase shift keying (BPSK) and quadrature phase shift keying modulation schemes [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

“…Since the RV-MSE criterion is quadratic, the RV-MMSE design admits a closed-form solution just as the case of the CV-MMSE solution. In this aspect, the RV-MMSE solution is better than the minimum BER (MBER) design [13], which requires a numerical solution. The MBER beamforming design however is the true optimal solution and it generally outperforms the RV-MMSE solution.…”

Section: Introductionmentioning

confidence: 99%

“…[18]) for the general LMS algorithm also applies to this RV-LMS algorithm. An adaptive implementation of the MBER solution is known as the least bit error rate (LBER) algorithm [13]. Because the BER criterion is highly complicated and certainly nonquadratic, convergence analysis of the LBER algorithm is a difficult task.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Adaptive beamforming for binary phase shift keying communication systems

2007

Self Cite

View full text Add to dashboard Cite

The paper revisits adaptive beamforming assisted receiver for multiple antenna aided multiuser systems that employ binary phase shift keying (BPSK) modulation. The standard minimum mean square error (MMSE) design is based on the criterion of minimising the mean square error (MSE) between the beamformer's desired output and complex-valued beamformer's output. Since the desired output for BPSK systems is real-valued, minimising the MSE between the beamformer's desired output and real-part of the beamformer's output can significantly improve the bit error rate (BER) performance, and we refer to this alternative MMSE design as the real-valued MMSE (RV-MMSE) to contrast to the standard complex-valued MMSE (CV-MMSE) design. The minimum BER (MBER) design however still outperforms the RV-MMSE solution, particularly for overloaded systems where degree of freedom of the antenna array is smaller than the number of BPSK users. Adaptive implementation of this RV-MMSE beamforming design is realised using a least mean square (LMS) type adaptive algorithm, which we refer to as the RV-LMS, in comparison to the standard CV-LMS algorithm. The RV-LMS adaptive beamformer is shown to have a similar computational complexity as the adaptive MBER beamforming implementation known as the least bit error rate (LBER), imposing only half of the computational requirements of the CV-LMS algorithm. r

show abstract

“…As recognised by Chen et al [13], the best strategy is to choose w by directly minimising the system's BER. Following the notations used in [13,20] …”

Section: Minimum Bit Error Rate Designmentioning

confidence: 99%

“…The BER of the beamformer for the desired user 1 with the weight vector w can be shown to be [13,20] …”

Section: Minimum Bit Error Rate Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Adaptive beamforming for binary phase shift keying communication systems

2007

Self Cite

View full text Add to dashboard Cite

show abstract

MinimumBERAdaptive Detection and Beamforming

2018

Simplified Robust Adaptive Detection and Beamforming for Wireless Communications

View full text Add to dashboard Cite

Three novel simple beamforming algorithms for CDMA communication systems

Tavassoli

Abolhassani

Oraizi

et al. 2012

Int J Communication

View full text Add to dashboard Cite

SUMMARYTo apply a beamforming algorithm with a linear array of N antennas in real wireless communication systems, two main issues should be addressed: Algorithm complexity and number of antennas. In this paper, we propose three simple beamforming algorithms for direct sequence code division multiple access systems. We first propose a new framework to obtain the updating equation for the weight vector using PCA. Then, using this framework, four different objective functions are used as examples to illustrate how to obtain new adaptive algorithms. We demonstrate that these objective functions lead to three novel blind algorithms, with two of them resulting in the same algorithm. Moreover, they have considerably low complexities, requiring only 2N–1 complex additions and either 2N+1 or 2N complex multiplications for a single run. We evaluate the performances of these algorithms in estimating the angle‐of‐arrival of the desired signal and in producing the array beam pattern, and in alleviating the BER in Rayleigh fading and AWGN channels. In summary, these new beamforming algorithms obtained based on the proposed framework operate as blind algorithms, have low computational complexities, and offer desirable performances even if N is restricted.Copyright © 2012 John Wiley & Sons, Ltd.

show abstract

Adaptive minimum bit-error rate beamforming

Cited by 95 publications

References 28 publications

Adaptive beamforming for binary phase shift keying communication systems

Adaptive beamforming for binary phase shift keying communication systems

MinimumBERAdaptive Detection and Beamforming

Three novel simple beamforming algorithms for CDMA communication systems

Contact Info

Product

Resources

About