Comparing RLS and LMS adaptive equalizers for nonstationary wireless channels in mobile ad hoc networks

Wang, R.; Jindal, Nihar; Bruns, Th; Bahai, A.; Cox, D.C.

doi:10.1109/pimrc.2002.1045204

Cited by 10 publications

(5 citation statements)

References 8 publications

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“…As such equalizer structures suffer from several principal disadvantages (such as the additional time the prewhitening filter requires for convergence and the suboptimum solution in presence of additive Gaussian noise). It has been proven that, RLS will always outperform LMS [19]. As a result, the performance of EVA is close to RLS but better than LMS as obtained in our study.…”

supporting

confidence: 79%

Performance of multilevel‐turbo codes with blind/non‐blind equalization over WSSUS multipath channels

Uçan

Buyukatak

Gose

et al. 2005

Int J Communication

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SUMMARYIn this paper, in order to improve error performance, we introduce a new type of turbo codes, called 'multilevel-turbo codes (ML-TC)' and we evaluate their performance over wide-sense stationary uncorrelated scattering (WSSUS) multipath channels. The basic idea of ML-TC scheme is to partition a signal set into several levels and to encode each level separately by a proper component of the turbo encoder. In the considered structure, the parallel input data sequences are encoded by our multilevel scheme and mapped to any modulation type such as MPSK, MQAM, etc. Since WSSUS channels are very severe fading environments, it is needed to pass the received noisy signals through non-blind or blind equalizers before turbo decoders. In ML-TC schemes, noisy WSSUS corrupted signal sequence is first processed in equalizer block, then fed into the first level of turbo decoder and the first sequence is estimated from this first Turbo decoder. Subsequently, the other following input sequences of the frame are computed by using the estimated input bit streams of previous levels. Here, as a ML-TC example, 4PSK 2 level-turbo codes (2L-TC) is chosen and its error performance is evaluated in WSSUS channel modelled by COST 207 (Cooperation in the field of Science & Technology, Project #207). It is shown that 2L-TC signals with equalizer blocks exhibit considerable performance gains even at lower SNR values compared to 8PSK-turbo trellis coded modulation (TTCM). The simulation results of the proposed scheme have up to 5.5 dB coding gain compared to 8PSK-TTCM for all cases. It is interesting that after a constant SNR value, 2L-TC with blind equalizer has better error performance than non-blind filtered schemes. We conclude that our proposed scheme has promising results compared to classical schemes for all SNR values in WSSUS channels.

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supporting

confidence: 79%

Performance of multilevel‐turbo codes with blind/non‐blind equalization over WSSUS multipath channels

Uçan

Buyukatak

Gose

et al. 2005

Int J Communication

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“…RLS-based algorithms have good performance when applied in non-stationary channel models [26] but at the costs of increased computational complexity and possible instability [27]. Since the optical fiber channel changes only very slowly, we choose the LMS algorithm.…”

Section: Training and Decision Modesmentioning

confidence: 99%

Modified Nonlinear Decision Feedback Equalizer for Long-Haul Fiber-Optic Communications

Maiti

Brandt-Pearce

2015

J. Lightwave Technol.

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In a long-haul optical fiber communication system, fiber attenuation, dispersion and nonlinearity combined with nondeterministic noise from optical amplifiers used for periodic regeneration cause adverse effects on system performance. Several optical and electrical signal processing techniques have been proposed and implemented to extract the transmitted data; some provide better performance than others, but at a cost of higher computational complexity. We present a modified nonlinear decision feedback equalizer designed for use in a legacy optical communication system with periodic dispersion compensation. The effects of noise and nonlinearity on the equalizer coefficients are investigated, and a suboptimal convergence algorithm to reduce such effects is proposed and verified. Our equalizer provides performance comparable to that obtained using digital backpropagation while being computationally simpler, compensating linear and nonlinear physical impairment effects effectively even at high power levels where fiber nonlinearity is significant. Performance prediction of the designed DFE is also discussed, using a numerical method, with and without error propagation.

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“…As the NVIS channel shows multipath at some parts of the day and a high doppler spread as we can see in Orga et al, the recursive least squares (RLS) equalizer has been adopted for all the modulation schemes, as suggested in Wang et al

P_{S} = \frac{\sum_{f = f m false/ 2 - B W false/ 2}^{f m false/ 2 + B W false/ 2} X_{S} {false(f false)}^{2}}{B W}

P_{N} = \frac{\sum_{f = f m false/ 2 - B W false/ 2}^{f m false/ 2 + B W false/ 2} X_{N} {false(f false)}^{2}}{B W}

S N R = \frac{P_{S} - P_{N}}{P_{N}}

{E_{b} false/ N_{0}}_{d B} = S N R_{d B} + B W_{d B} - {E_{b}}_{d B} .

…”

Section: Resultsmentioning

confidence: 99%

Design, implementation, and test of an SDR for NVIS communications

Porte

Maso

Pijoan

et al. 2019

Circuit Theory & Apps

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Summary Although many physical layer solutions have appeared for remote sensors and Internet of things during the recent years, none of them is suited to very remote sensors in areas away from any mobile operator coverage. In that case, a solution on the basis of near vertical incidence skywave (NVIS) with reflection in the ionosphere may be very attractive. Using NVIS, no line of sight is needed and the coverage is much bigger than any other system operating in either the very high frequency (VHF) or ultra high frequency (UHF) band. In this paper, we present a new transmission scheme for very remote sensors using the NVIS transmission technique.

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Comparing RLS and LMS adaptive equalizers for nonstationary wireless channels in mobile ad hoc networks

Cited by 10 publications

References 8 publications

Performance of multilevel‐turbo codes with blind/non‐blind equalization over WSSUS multipath channels

Performance of multilevel‐turbo codes with blind/non‐blind equalization over WSSUS multipath channels

Modified Nonlinear Decision Feedback Equalizer for Long-Haul Fiber-Optic Communications

Design, implementation, and test of an SDR for NVIS communications

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