12,157 research outputs found

    Reduced complexity sequence detection

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    The paper deals with the design of suboptimal receivers for data transmission over frequency selective channels. The complexity of the optimum detector, that is the maximum likelihood sequence detector (MLSD), turns out be exponential in the channel memory. Hence, when dealing with channels with long memory, suboptimal receiver structures must be considered. Among suboptimal methods, a technique that allows reduction of the complexity is the delayed decision feedback sequence detector (DDFSD). This receiver is based on a Viterbi processor where the channel memory is truncated. The memory truncation is compensated by a per-survivor decision feedback equalizer. In order to achieve good performance, it is crucial to operate an appropriate prefiltering of the received sequence before the DDFSD. Our contribution is to extend the principles of MLSD and DDFSD to the case where the prefilter is the feedforward filter of a minimum mean-square error decision feedback equalizer (MMSE-DFE). Moreover performance evaluation of the MMSE prefiltered DDFSD is addressed. The union upper bound is used to evaluate the probability of first-event error. Simulation results show that our proposed design of the MMSE-DDFSD gives substantial benefits when a severe frequency selective channel is considered

    Doppler-corrected differential detection system

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    Doppler in a communication system operating with a multiple differential phase-shift-keyed format (MDPSK) creates an adverse phase shift in an incoming signal. An open loop frequency estimation is derived from a Doppler-contaminated incoming signal. Based upon the recognition that, whereas the change in phase of the received signal over a full symbol contains both the differentially encoded data and the Doppler induced phase shift, the same change in phase over half a symbol (within a given symbol interval) contains only the Doppler induced phase shift, and the Doppler effect can be estimated and removed from the incoming signal. Doppler correction occurs prior to the receiver's final output of decoded data. A multiphase system can operate with two samplings per symbol interval at no penalty in signal-to-noise ratio provided that an ideal low pass pre-detection filter is employed, and two samples, at 1/4 and 3/4 of the symbol interval T sub s, are taken and summed together prior to incoming signal data detection

    Analysis and equalization of data-dependent jitter

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    Data-dependent jitter limits the bit-error rate (BER) performance of broadband communication systems and aggravates synchronization in phase- and delay-locked loops used for data recovery. A method for calculating the data-dependent jitter in broadband systems from the pulse response is discussed. The impact of jitter on conventional clock and data recovery circuits is studied in the time and frequency domain. The deterministic nature of data-dependent jitter suggests equalization techniques suitable for high-speed circuits. Two equalizer circuit implementations are presented. The first is a SiGe clock and data recovery circuit modified to incorporate a deterministic jitter equalizer. This circuit demonstrates the reduction of jitter in the recovered clock. The second circuit is a MOS implementation of a jitter equalizer with independent control of the rising and falling edge timing. This equalizer demonstrates improvement of the timing margins that achieve 10/sup -12/ BER from 30 to 52 ps at 10 Gb/s

    Diffusive MIMO Molecular Communications: Channel Estimation, Equalization and Detection

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    In diffusion-based communication, as for molecular systems, the achievable data rate is low due to the stochastic nature of diffusion which exhibits a severe inter-symbol-interference (ISI). Multiple-Input Multiple-Output (MIMO) multiplexing improves the data rate at the expense of an inter-link interference (ILI). This paper investigates training-based channel estimation schemes for diffusive MIMO (D-MIMO) systems and corresponding equalization methods. Maximum likelihood and least-squares estimators of mean channel are derived, and the training sequence is designed to minimize the mean square error (MSE). Numerical validations in terms of MSE are compared with Cramer-Rao bound derived herein. Equalization is based on decision feedback equalizer (DFE) structure as this is effective in mitigating diffusive ISI/ILI. Zero-forcing, minimum MSE and least-squares criteria have been paired to DFE, and their performances are evaluated in terms of bit error probability. Since D-MIMO systems are severely affected by the ILI because of short transmitters inter-distance, D-MIMO time interleaving is exploited as countermeasure to mitigate the ILI with remarkable performance improvements. The feasibility of a block-type communication including training and data equalization is explored for D-MIMO, and system-level performances are numerically derived.Comment: Accepted paper at IEEE transaction on Communicatio

    Computing the feedback filter of the decision feedback equalizer at the FFT speed

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    Performance evaluation of the MMSE delayed decision feedback sequence detector

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    Bound-intersection detection for multiple-symbol differential unitary space-time modulation

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    This paper considers multiple-symbol differential detection (MSD) of differential unitary space-time modulation (DUSTM) over multiple-antenna systems. We derive a novel exact maximum-likelihood (ML) detector, called the bound-intersection detector (BID), using the extended Euclidean algorithm for single-symbol detection of diagonal constellations. While the ML search complexity is exponential in the number of transmit antennas and the data rate, our algorithm, particularly in high signal-to-noise ratio, achieves significant computational savings over the naive ML algorithm and the previous detector based on lattice reduction. We also develop four BID variants for MSD. The first two are ML and use branch-and-bound, the third one is suboptimal, which first uses BID to generate a candidate subset and then exhaustively searches over the reduced space, and the last one generalizes decision-feedback differential detection. Simulation results show that the BID and its MSD variants perform nearly ML, but do so with significantly reduced complexity
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