This paper proposes FlashLinQ-a synchronous peer-to-peer wireless PHY/MAC network architecture. FlashLinQ leverages the fine-grained parallel channel access offered by OFDM and incorporates an analog energy-level-based signaling scheme that enables signal-to-interference ratio (SIR)-based distributed scheduling. This new signaling mechanism, and the concomitant scheduling algorithm, enables efficient channel-aware spatial resource allocation, leading to significant gains over a CSMA/CA system using RTS/CTS. FlashLinQ is a complete system architecture including: 1) timing and frequency synchronization derived from cellular spectrum; 2) peer discovery; 3) link management; and 4) channel-aware distributed power, data rate, and link scheduling. FlashLinQ has been implemented for operation over licensed spectrum on a digital signal processor/field-programmable gate array (DSP/FPGA) platform. In this paper, we present FlashLinQ performance results derived from both measurements and simulations.

We present a novel method for superposition coding applicable to OFDM systems in which the receivers being transmitted to are one high SNR receiver and one low SNR receiver. The degradation of the high SNR receiver, however, results primarily from channel uncertainty. Thus, we consider the effect of imperfect channel estimates, a ubiquitous problem in mobile wireless, and show that the new scheme performs much better than traditional schemes in such a setting.

Multiuser diversity is a form of diversity inherent in a wireless network, provided by independent time-varying channels across the different users. The diversity benefit is exploited by tracking the channel fluctuations of the users and scheduling transmissions to users when their instantaneous channel quality is near the peak. The diversity gain increases with the dynamic range of the fluctuations and is thus limited in environments with little scattering and/or slow fading. In such environments, we propose the use of multiple transmit antennas to induce large and fast channel fluctuations so that multiuser diversity can still be exploited. The scheme can be interpreted as opportunistic beamforming and we show that true beamforming gains can be achieved when there are sufficient users, even though very limited channel feedback is needed. Furthermore, in a cellular system, the scheme plays an additional role of opportunistic nulling of the interference created on users of adjacent cells. We discuss the design implications of implementing. this scheme in a complete wireless system.

The trellis-based scalar-vector quantizer (TB-SVQ) can achieve the rate-distortion performance bound for memoryless sources. This paper extends the scope of this quantizer to coding of sources with memory. First considered is a simple extension, called the predictive TB-SVQ, which applies a closed-loop predictive coding operation in each survivor path of the Viterbi codebook search algorithm. Although the predictive TB-SVQ outperforms all other known structured fixed-rate vector quantizers, due to practical reasons, it may not approach the rate-distortion limit. A new quantization scheme motivated by the precoding idea of Laroia et al. (1993), called the precoded TB-SVQ, is also considered; the granular gain is realized by the underlying trellis code while the combination of the precoder and the SVQ structure provides the boundary gain. This new quantization scheme is asymptotically optimal and can, in principle, approach the rate-distortion bound for Markov sources.

This paper develops coding and signal processing approaches for a novel optical recording channel that arises from electron-trapping phosphor materials. The recording medium allows multiple reads and writes, and one important feature is that the read process serves to erase the disk. This feature would enable vendors of prerecorded video to provide customers with one-time services. For applications where this feature is not desirable, the data can be immediately rewritten. From a communications viewpoint, the most important feature of this new channel is that, subject to a peak constraint, it supports a continuum of recording levels. The combination of read and write processes creates a partial-response channel, and the ability to write a continuum of levels makes it possible to employ precoding techniques, such as the one developed by Tomlinson (1971) and by Miyakawa and Harashima (1969). This is fundamentally different from magnetic data storage, where the read/write process creates a partial-response channel but where it is only possible to write two levels at the input to that channel. This paper shows that the use of precoding and coset codes can significantly improve upon the recording densities (and recording rates) that can be achieved by using M-ary run length constrained codes to eliminate intersymbol interference (ISI) at the output of the read/write process. The approach presented is applicable to any optical recording channel that supports a continuum of recording levels.

This paper describes a new coding scheme for transmission over intersymbol interference (ISI) channels. This scheme, called ISI coding, combines trellis coding with precoding (used to combat ISI). Like the recently introduced precoding scheme of Laroia, Tretter, and Farvardin (LTF), the ISI coder makes it possible to achieve both shaping and coding gains over ISI channels. By combining coding and precoding, however, the ISI coder makes the "precoding loss" independent of the number of coset partitions used to generate the trellis code. At high rates (large signal-to-noise ratio (SNR)), this makes it possible to approach the Shannon capacity of an ISI channel. The V.34 (formerly V.fast) international modem standard for high-speed (up to 28.8 kb/s) communication over voice-band telephone lines uses the version of the ISI coder described in Section IV of this paper.

The discrete-time additive Gaussian intersymbol interference (ISI) channel with i.i.d. (not necessarily Gaussian) input signals is considered. Several new and old lower bounds on the capacity are derived in a unified manner by assuming different front-end receiver filters, in particular the sampled whitened matched filter (SWMF) and the minimum mean-squared error-decision feedback equalizer (MMSE-DFE) filter. The features of the bounds are demonstrated and compared in several examples with binary and quaternary input signals. It is also shown that the effect of an ideal post-cursor or tail cancellation, in an information-preserving context, depends primarily on the front-end filter. While, as is well known, ideal post-cursor cancellation at the output of the SWMF decreases the information, the opposite trend is seen when an MMSE-DFE front filter is considered. This observation reflects the basic theoretical obstacles in precoding, i.e., ideal post-cursor cancellation in the presence of a pre-cursor. It is used to assess the inherent loss (in terms of information rates as compared to the rates achievable with the hypothetical ideal post-cursor cancellation) associated with any post-cursor cancellation technique such as precoding, DFE, or other variants, when operating in synergy with the MMSE-DFE front-end filter. The effect of the front-end filter on an ideally interleaved, precoded coded-modulation system is also addressed.

Describes a speech coder based on the intersymbol interference coded quantizer (ICQ). The ICQ is a structured vector quantizer that can realize both boundary and granular gains for sources with memory. It is the quantization dual of the intersymbol interference coder-a transmission scheme for channels with memory. The authors have studied two different suboptimal ICQ codebook search algorithms for speech coding and find that the performance of the ICQ based speech coder is very good at rates over 13 kbps but degrades rapidly at lower rates.

Considers an application of a structured, fixed-length vector quantizer, called the scalar-vector quantizer, to image coding. The scalar-vector quantizer, while using fixed-length codewords, achieves a rate-distortion performance close to that of the optimum variable-length encoded scalar quantizer. In the paper, an adaptive 2D DCT coding system is developed in which the DCT coefficients are quantized by scalar-vector quantizers. It is shown that performance comparable to variable-length coding systems can be achieved while maintaining a fixed encoding rate. Preliminary results on the performance of the proposed system when employed over a noisy channel, along with a simple error mitigation mechanism are also provided.>

We present a new motion compensated DCT based video coding scheme. The quantization of DCT coefficients is done using trellis based-scalar vector quantizer (TB-SVQ) introduced by Laroia and Farvardin (see IEEE Transactions on Information Theory, vol.39, no.5, p.851-868, 1993). TB-SVQ is fixed rate and for memoryless sources is known to asymptotically achieve all gains over uniform scalar quantizers. Our coding scheme does not require buffering or variable length coding to reach its target bit rate. Thus the resulting coding delay is minimal, while the performance is very good. Furthermore since no variable length coding is necessary, our coder is robust in the presence of channel errors. Hence it is suitable for video teleconferencing.>

Testing of high-speed voiceband modems has revealed a significant increase in distortion for points near the perimeter of a QAM signal constellation. This distortion increases with distance from the center of the constellation and limits performance at data rates above 19.2 kb/s. The perimeter distortion can be reduced by transforming the signal constellation so that points near the center are closer together, and points near the perimeter are further apart. When the channel SNR is high, such a transformation reduces immunity to Gaussian noise because points near the center of the transformed constellation are closer together than in a uniformly spaced constellation with the same average power. This paper demonstrates theoretically that for channel SNRs of practical interest. There is actually a small gain in immunity to Gaussian noise. In fact, an appropriate coded modulation scheme can produce gains of about 0.25 dB.>

The paper describes a structured vector quantization approach for stationary memoryless sources that combines the scalar-vector quantizer (SVQ) ideas (Laroia and Farvardin, 1993) with trellis coded quantization (Marcellin and Fischer, 1990). The resulting quantizer is called the trellis-based scalar-vector quantizer (TB-SVQ). The SVQ structure allows the TB-SVQ to realize a large boundary gain while the underlying trellis code enables it to achieve a significant portion of the total granular gain. For large block-lengths and powerful (possibly complex) trellis codes the TB-SVQ can, in principle, achieve the rate-distortion bound. As indicated by the results obtained, even for reasonable block-lengths and relatively simple trellis codes, the TB-SVQ outperforms all other fixed-rate quantizers at reasonable complexity.>

A scheme for the optimal shaping of multidimensional constellations is proposed. This scheme is motivated by a type of structured vector quantizer for memoryless sources, and results in N-sphere shaping of N-dimensional cubic lattice-based constellations. Because N-sphere shaping is optimal in N dimensions, shaping gains higher than those of N-dimensional Voronoi constellations can be realized. While optimal shaping for a large N can realize most of the 1.53 dB total shaping gain, it has the undesirable effect of increasing the size and the peak-to-average power ratio of the constituent 2D constellation. This limits its usefulness for many real world channels which have nonlinearities. The proposed scheme alleviates this problem by achieving optimal constellation shapes for a given limit on the constellation expansion ratio or the peak-to-average power ratio of the constituent 2D constellation. Results of Calderbank and Ozarow (1990) on nonequiprobable signaling are used to reduce the complexity of this scheme and make it independent of the data rate with essentially no effect on the shaping gain. Comparisons with Forney's (1989) trellis shaping scheme are also provided.>

A precoding scheme for noise whitening on intersymbol interference (ISI) channels is presented. This scheme is compatible with trellis-coded modulation and, unlike Tomlinson precoding, allows constellation shaping. It can be used with almost any shaping scheme, including the optimal SVQ shaping, as opposed to trellis precoding, which can only be used with trellis shaping. The implementation complexity of this scheme is minimal-only three times that of the noise prediction filter, hence effective noise whitening can be achieved by using a high-order predictor.>

A low-complexity, fixed-rate structured vector quantizer for memoryless sources is described. This quantizer is referred to as the scalar-vector quantizer (SVQ), and the structure of its codebook is derived from a variable-length scalar quantizer. Design and implementation algorithms for this quantizer are developed and bounds on its performance are provided. Simulation results show that performance close to that of the optimal entropy-constrained scalar quantizer is possible with the fixed-rate quantizer. The SVQ is also robust against channel errors and outperforms both Lloyd-Max and entropy-constrained scalar quantizers for a wide range of channel error probabilities.>

For Pt.I see ibid., vol.39, no.3, p.851-67 (1993). The fixed-rate scalar-vector quantizer (SVQ) for quantizing stationary memoryless sources is extended to a specific type of vector source in which each component is a stationary memoryless scalar subsource independent of the other components. Algorithms for the design and implementation of the original SVQ are modified to apply to this case. The resulting SVQ, referred to as the extended SVQ (ESVQ), is then used to quantize stationary sources with memory (with known autocorrelation function). Numerical results are presented for the quantization of first-order Gauss-Markov sources using this scheme. It is shown that the ESVQ-based scheme performs very close to entropy-coded transform quantization while maintaining a fixed-rate output and outperforms the fixed-rate scheme that uses scalar Lloyd-Max quantization of the transform coefficients. It is also shown that this scheme performs better than implementable vector quantizers, especially at high rates. >

Three robust algorithms based on the recently proposed concept of structured vector quantization have been developed for quantization of speech LSP (line spectrum pair) parameters. The first algorithm exploits interframe correlation of the LSP parameters and requires 24 bits per LSP vector to achieve 1 dB average spectral distortion. The second and third algorithms quantize each LSP vector independently and for 1 dB distortion require 29 and 25 bits per vector, respectively. The last two algorithms result in a considerably smaller fraction of frames with distortions greater than 2 dB as compared to other schemes proposed so far.>

The intraframe and interframe correlation properties are used to develop two efficient encoding algorithms for speech line spectrum pair (LSP) parameters. The first algorithm (2-D DCT), which requires relatively large coding delays, is based on two-dimensional (time and frequency) discrete cosine transform coding techniques; the second algorithm (DCT-DPCM), which does not need any coding delay, uses one-dimensional discrete cosine transform in the frequency domain and DPCM (differential pulse-code modulation) in the time domain. The performances of these systems for different bit rates and delays are studied, and appropriate comparisons are made. It is shown that an average spectral distortion of approximately 1 dB/sup 2/ can be achieved with 21 and 25 bits/frame using the 2-D DCT and DCT-DPCM schemes, respectively. This is a noticeable improvement over the previously reported bit rates of 32 bits/frame and above.>