Chair: Gregory W. Wornell, MIT, USA
Venceslav Kafedziski, Arizona State University (U.S.A.)
Darryl Morrell, Arizona State University (U.S.A.)
We investigate joint source channel coding for channels with intersymbol interference (ISI) where the source coder is a vector quantizer. In our previous work we used a block MAP equalizer, which takes into account the residual correlation between the VQ outputs and also provides for soft decisions to improve the performance. In this paper we propose the use of a vector channel approach and discrete multitone modulation for joint source channel coding on channels with ISI. Using these modulation procedures, intersymbol interference can be eliminated and the problem of joint source channel coding for ISI channels is reduced to the problem of coding for vector Gaussian channels. Optimization of the signal set is performed through optimal power allocation to the subchannels. Simulation results are presented for both vector and discrete multitone channels and compared to the results obtained by using the block MAP equalizer and to the OPTA (optimum performance theoretically attainable) bound.
Hasan H Otu, University of Nebraska (U.S.A.)
Khalid Sayood, University of Nebraska (U.S.A.)
Joint source/channel coders obtained using MAP decoders tend to fail at low probability of error. In this paper we propose a modification of the standard approach which provides protection at low error rates as well.
Hamid Jafarkhani, AT&T Labs (U.S.A.)
Nariman Farvardin, University of Maryland (U.S.A.)
We propose algorithms to design channel-optimized vector quantizers in the presence of channel mismatch. We consider two cases: (i) no information about the statistics of the channel bit error rate is available and (ii) the probability density function of the channel bit error rate is known. We also consider the use of an estimate of the channel signal-to-noise ratio to improve performance. Simulation results demonstrate the advantages of new design algorithms.
Vasileios Megalooikonomou, University of Maryland Baltimore County (U.S.A.)
Yaacov Yesha, University of Maryland Baltimore County (U.S.A.)
We consider the problem of quantizer design in a distributed estimation system with communication constraints at the channels in the case where the observation statistics are unknown and one must rely on a training set. The method that we propose applies a variation of the Cyclic Generalized Lloyd Algorithm (CGLA) on every point of the training set and then uses a neural network for each quantizer to represent the training points along with their associated codewords. The codeword of every training point is initialized using a regression tree approach. Simulations show that the combined approach i.e. building the regression tree system and using its quantizers to initialize the neural networks provides an improvement over the regression tree approach except in the case of high noise variance.
Masoud Khansari, Hewlett-Packard Labs (U.S.A.)
Predictive coding methods such as DPCM used for lossless coding of images or motion compensated hybrid video coders MPEG family are shown to compress the input signals well with a reasonable complexity. The performance of these coders, however, degrades considerably when the transmission channel is not error-free. This is due to the error propagation at the decoder where a single error can have catastrophic consequences. A low-rate feedback channel is shown to improve the overall performance. In this paper, we consider two such methods and provide the analysis and investigate different trade-offs.
Hui Liu, University of Virginia (U.S.A.)
Kemin Li, University of Virginia (U.S.A.)
Differential coding allows signal demodulation without carrier phase estimation, and thus is commonly used to cope with phase ambiguity and residual carriers. In a wireless scenario where the system transfer function is FIR due to multipath reflections, channel estimation and equalization is usually required. Inspired by the recent work by Tong on blind sequence estimation, we propose a vector differential coding scheme that allows instantaneous signal detection at the receiver without knowledge of the channel. The new technique can be regarded as a generalization of the standard differential coding method for removing convolutional ambiguities.
German S Feyh, Cirrus Logic (U.S.A.)
The nonlinear write process of magnetic recording allows to write the symbols +1/-1 only. The magnetic channel is a differentiating channel. The locations of the transitions from +1 to -1 and vice versa in the input signal to the magneticchannel are important for the received waveform. This paper defines a noise enhancement constrained, finite dimensional equalizer. This equalizer trades some misequalization of the data signal for less noise enhancement after the equalizer. Additionally the misequalization is decreased by precoding. Precoding shapes the signal before entering the channel. Since precoding in magnetic channels is limited to shifting the positions of the transitions around, precoding does not allow for full equalization at the receiver. Therefore the equalizer in the receiver and the precoder are optimized. In order to find the optimal transition positions a linearized representation of the transition shift is produced. This representation leads to a constraint optimization problem.
Mark E Halpern, University of Melbourne (Australia)
Murk Bottema, Flinders University (Australia)
William Moran, Flinders University (Australia)
Soura Dasgupta, University of Iowa (U.S.A.)
This paper contains results on the design of optimum equalizers to eliminate intersymbol interference in linear non-minimum phase channels conveying binary signals. The optimization is with respect to an open eye condition with a given delay. For causal stable channels with non-minimum phase zeros, we argue that this problem requires only the consideration of theFIR modified channel that has all the non-minimum phase zeros of the original channel. We show that if this modified channel can be equalized to yield an equalized system that is open eye with a specified delay, then the optimizing equalizer is, in fact FIR with all zeros outside the unit circle, and the impulse response of the equalised channel does not extend beyond the delay. We also give a simple necessary and sufficient condition to determine if for a particular delay, a given channel can be equalized to achieve an equalized response that is open eye.
Alper T Erdogan, Stanford University (U.S.A.)
Babak Hassibi, Stanford University (U.S.A.)
Thomas Kailath, Stanford University (U.S.A.)
As an alternative to existing techniques and algorithms, we investigate the merit of the H-infinity approach to the equalization of communication channels. We first look at causal H-infinity equalization problem and then look at the improvement due to finite delay. By introducing the risk sensitive property, we compare the average performance of the central H-infinity Equalizer with the MMSE equalizer in equalizing minimum phase channels.
Ian J Fevrier, Purdue University (U.S.A.)
Saul B Gelfand, Purdue University (U.S.A.)
Michael P Fitz, Ohio State University (U.S.A.)
Decision feedback equalization (DFE) structures have recently been proposed for the efficient equalization of wireless channels with long postcursor response, which is a bottleneck problem for high speed communications over multipath channels with large delay spreads. These structures are equivalent to the conventional DFE, but remove postcursor intersymbol interference (ISI) prior to feedforward filtering. We investigate the relationship between these structures and fast equalizer coefficient computation. Based on this relationship, we obtain a fast algorithm for computing optimal DFE settings which has significantly lower complexity than other known approaches for these high speed wireless channels. An example is given for data rates and channel profiles of the type considered for the proposed North American high definition television (HDTV) terrestrial broadcast mode.