Maximum-likelihood diversity combining in partial-band noise

Li, G.; Wang, Q.; Bhargava, V.K.; Mason, L.J.

doi:10.1109/26.737392

Cited by 29 publications

(34 citation statements)

References 9 publications

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“…Both techniques are equivalent although performing the combining before the turbo decoder is more convenient. As shown in [1], we can approximate log (I o (x)) as follows:…”

Section: Llr For Ncbfskmentioning

confidence: 99%

“…In early works, repetition diversity was used to mitigate the effect of partial-band interference (PBI) and various techniques were proposed for diversity combining at the receiver. Most of the effective combining techniques for uncoded systems are summarized in [1]. The Maximum-Likelihood (ML) diversity combining technique was derived for non-coherent binary frequency shift keying (NCBFSK) in [2] in the absence of background noise as a lower bound for performance, and in [1] was derived in the presence of both background noise and PBI.…”

Section: Introductionmentioning

confidence: 99%

“…Most of the effective combining techniques for uncoded systems are summarized in [1]. The Maximum-Likelihood (ML) diversity combining technique was derived for non-coherent binary frequency shift keying (NCBFSK) in [2] in the absence of background noise as a lower bound for performance, and in [1] was derived in the presence of both background noise and PBI. Furthermore, error control coding was used to mitigate the effect of PBI in [3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

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Diversity Combining and SNR Estimation for Turbo-Coded Frequency-Hopped Spread-Spectrum in Partial-Band Interference and Fading Channels

Elezabi

Gomaa

2008

Wireless Pers Commun

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We compare different combinations of the repetition diversity order L and code rate R for turbo-coded Frequency-Hopped Spread-Spectrum (FH/SS) communication systems in the presence of fading and partial-band Gaussian interference. For a fixed overall channel code rate R/L we show that using the lowest code rate and no repetition diversity always performs better than using a higher code rate and some repetition for both coherent and non-coherent schemes. We then propose a simple maximum-likelihood-based method for signal-to-noise-ratio (SNR) estimation in Non-Coherent Binary Frequency Shift Keying (NCBFSK) without training symbols. Except for impractically small hop sizes of 8 bits or less we obtain performance virtually equal to that of perfect SNR knowledge but with much less complexity than iterative schemes previously proposed. For the case of Coherent Binary Phase Shift Keying (CBPSK) we derive the Expectation Maximization (EM) estimate of the SNR without training symbols and iteratively feed the estimator with the extrinsic information from the turbo decoder. The performance for CBPSK is near that of perfect SNR knowledge for hop sizes of 64 bits or more. Unlike previously proposed methods for CBPSK the EM estimate of SNR does not require knowledge of the noise and interference variance, received bit energy, or the fading channel model.

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“…Both techniques are equivalent although performing the combining before the turbo decoder is more convenient. As shown in [1], we can approximate log (I o (x)) as follows:…”

Section: Llr For Ncbfskmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Diversity Combining and SNR Estimation for Turbo-Coded Frequency-Hopped Spread-Spectrum in Partial-Band Interference and Fading Channels

Elezabi

Gomaa

2008

Wireless Pers Commun

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“…In the FFH/MFSK system, in a large number of diversity combining, we consider the maximum likelihood combined with [3,4] for the best diversity combining if the diversity number is L. In the fast frequency hopping system, in order to achieve diversity, a symbol is required to repeat the transmission L times, reducing the probability of partial band interference. In the receiver, detection frequency diversity, a symbol of all jump frequency envelope detection output sampling value can be through the maximum likelihood method with together, the implementation of anti interference of frequency diversity combining in Figure 1.…”

Section: Simplified Maximum Likelihood Diversity Combining Algorithmsmentioning

confidence: 99%

“…Which symbol is transmitted through the selection of the value of the maximum Considering realization, we can approximate maximum-likelihood technology and find out the performance of two changing ML method is not very weak and approaches to optimum diversity combining, so we regarded it as sub-optimum. In reference [3] and [4], the performance of the optimum combining scheme was evaluated and the optimum structure of a maximum-likelihood (ML) receiver for a fast frequency-hopped binary frequency-shift-keying (FFH/BFSK) spread-spectrum (SS) communication system was derived.…”

Section: Simplified Maximum Likelihood Diversity Combining Algorithmsmentioning

confidence: 99%

Realization of Simplified Diversity Combining Algorithms for Fast Frequency Hopping System

Xie¹,

Lv²,

Wang³

et al. 2017

dtcse

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Abstract. In the fast frequency hopping system, the diversity combining technique of the receiver can effectively restrain the partial band interference, and it is the key to improve the anti-jamming capability. For the computation and complexity of the maximum likelihood diversity combining algorithm, we allow the reduction of the SNR to a smaller level, then we can use the sum of squares to simplify the approximation. The several maximum likelihood diversity combining algorithms are compared and analysized. It gives the realization process of the simplified diversity combining algorithm, the complexity of the algorithm is greatly reduced, and it is easier to implement on hardware.

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Performance analysis of FFH/MFSK receivers with noise‐normalisation combining over Nakagami‐m fading channels with partial‐band jamming

Zhou

Cheng

2010

Trans Emerging Tel Tech

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SUMMARYThe performance of a fast frequency-hopped M-ary orthogonal frequency-shift-keying (FFH/MFSK) receiver with noise-normalisation combining over Nakagami-m fading channels with partial-band noise jamming and additive white Gaussian noise (AWGN) is analysed. Instead of numerical integration, a closed-form error probability expression is obtained. The analytical results validate the simulation results. It is shown that there is an optimum diversity order and the corresponding best-case performance is investigated. Copyright

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Maximum-likelihood diversity combining in partial-band noise

Cited by 29 publications

References 9 publications

Diversity Combining and SNR Estimation for Turbo-Coded Frequency-Hopped Spread-Spectrum in Partial-Band Interference and Fading Channels

Diversity Combining and SNR Estimation for Turbo-Coded Frequency-Hopped Spread-Spectrum in Partial-Band Interference and Fading Channels

Realization of Simplified Diversity Combining Algorithms for Fast Frequency Hopping System

Performance analysis of FFH/MFSK receivers with noise‐normalisation combining over Nakagami‐m fading channels with partial‐band jamming

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