A continuously adaptive MLSE receiver for mobile communications: algorithm and performance

Abstract

Abstract-The paper presents a Euclidean distance maximum likelihood sequence estimation (MLSE) receiver, based on the Viterbi algorithm (VA), suitable for fading and noisy communications channels, as that specified by the group spécial mobiles (GSM). In a mobile cellular system, the fast varying channel characteristics, due to the fading and Doppler effects, require adaptive methods to update the channel coefficients to the MLSE receiver. The proposed technique continuously estimates the channel characteristics directly within the metric calculation of the VA. At each step of the VA, the sequence associated to the path with the best metric value (minimum-survivor method) among the survivor paths is used to update the channel estimate (employing conventional adaptive algorithms) throughout the entire informative sequence. However, the detection of the transmitted data sequence is performed by the VA only at the end of each burst.The proposed technique allows simpler receiver implementation and the simulation results show a good performance of this adaptive MLSE receiver in typical GSM environments.

An Adaptive Approach of Semi-blind Data and Channel Estimation for Meteor Burst Communications

“…As shown in the figures, the performances of ASRP for QPSK and 16QAM symbols are degraded by about 0.8dB and 1.5dB, respectively, in comparison with those of PSP. The performance of the MSP[12] is between that of ASRP…”

“…Given the bit rate of 32kbps and 64kbps, the sampling rate of 5 samples per symbol, the carrier frequency of 40MHz, and the noises of AWGN, the system simulations are performed for different r c P , without interleaving and error-correct codes. For comparison, the bit error rate (BER) performances of the PSP, MSP [12] and the full-state Viterbi algorithm with known channel are also depicted in Fig.3 and Fig.4. , whereas its computational complexity grows exponentially with the modulation phase number M. For the proposed ASRP method, the BER of QPSK is less than 3 10 1 − × when E s /N 0 is higher than 10.5dB, and the BER of 16QAM is below 3 10 1 − × when E s /N 0 is higher than 18dB.…”

“…For the variable data transmission, the medium experiences multi-path propagation from a variety of sources, including meteoroid breakup, wind shear, multiple trails, aurora scatter and sporadic-E layer propagation, which introduces intersymbol interference (ISI) and brings difficulties in both data detection and channel estimation at the receiver [1]- [3]. For joint data detection and channel estimation, per-survivor processing (PSP) provides general framework of maximum likelihood sequence detection (MLSD) with superior performance and robustness for time-varying channels [8]- [12]. With L representing the channel memory length and M denoting the modulation signal sets, the computational complexity of PSP is increased by L M , which makes the perfect precise PSP algorithm computationally prohibitive, especially for the adaptive modulations of MBC systems.…”

An adaptive receiver of joint data and channel estimation for meteor burst communications

“…Given the bit rate of 32 and 64 kbps, the sampling rate of 5 samples per symbol, the carrier frequency of 40 MHz, and the noises of AWGN, the system simulations are performed for different P c,r without interleaving and error-correct codes. For comparison, the bit error rate (BER) performances of the PSP, MSP [16] and the full-state VA with known channel are also depicted in Figures 7 and 8.…”

Robust adaptive decoding of space-time trellis code with soft-decision output

“…Model of the STTC system. in Equation 4),ĉðlÞ is obtained from the minimum survivor sequence [10] andĤ Pred ðl þ 1Þ is used in the branch metric computation at time l þ 1; in other words,Ĥðl þ 1Þ 1 H Pred ðl þ 1Þ. The simulation results [5] showed that the SOTSLMS decoder can provide fairly good performance in AWGNbased slowly or moderately fast time-varying wireless channels (denoted as F-TSLMS in Figures 5 and 6 of [5]).…”