Video transmission on multiuser wireless channels faces manifold challenges in both source- and channel-coding. We propose a framework to analyze three facets of this idea: video distortion, transmit power, and delay. In the scenario considered here, both the transmitter and end-users are equipped with multi-antenna transceivers. The goal is to broadcast video to all users; however, the video is differentiated in quality to match the spatial and temporal variation of the channel. An emerging coding standard that is well-suited to this scenario is the Scalable Video Coding (SVC) extension of H.264. We employ the medium-grain scalability (MGS) feature of SVC, which allows us to generate quality-scalable layers from a single video sequence. For transport, the transmitter employs the block-diagonal zero-forcing (ZF) precoding technique, a well-known technique which yields good performance. With these assumptions, the idea here is to compute a precoder at fixed intervals. Crucially, the cross-layer framework allocates layers of video to the end-users jointly with precoder computation. The framework also ensures that delay and buffer constraints are met, which is necessary for real-time video. In terms of solution approach, the problem turns out to be a difficult mixed-integer nonlinear optimization problem. However, we show that it is tractable via a primal-dual method. We analyze performance in various configurations, gaining insight into the relationship between the main system parameters.

We propose a framework for multicasting layers of scalable video over a broadcast channel to multiple users simultaneously. The framework ensures that all users receive the content, but at differentiated levels of quality depending on channel conditions. A coding scheme well-suited to this purpose is Scalable Video Coding (SVC). In particular, we employ medium-grain scalability (MGS), which allows us to generate quality-scalable layers from a single video sequence. For transport, we assume that both the transmitter and endusers are equipped with multiple-input multiple-output (MIMO) transceivers. The transmitter employs the zero-forcing (ZF) preceding technique, which yields good performance with low complexity. With these assumptions, the scheme proposed here computes a block-diagonal ZF-precoder at fixed intervals, subject to a power constraint at the transmitter. Crucially, the algorithm assigns quality-scalable layers of video to the end-users jointly with precoder computation. The framework also ensures that delay and buffer constraints are met, which is necessary for realtime video. In terms of solution approach, the problem turns out to be a difficult mixed-integer nonlinear optimization problem.

We propose a low-complexity PAM-based transmission scheme that is well suited for channels constrained by inter-symbol interference (ISI) and colored Gaussian noise. The scheme consists of coset-codes constructed on multi-dimensional lattices with a combination of low-density parity-check (LDPC) codes and classical Reed-Solomon (RS) codes. To approach the capacity of an ISI-constrained channel, the code is easy to employ in conjunction with spectral shaping, Tomlinson- Harashima precoding and decision-feedback equalization (DFE). The scheme performs within 2-2.5 dB of un-shaped channel capacity (the sphere-bound) at very low BER's, even with regular LDPC codes of modest block lengths. We investigate dense multidimensional lattices such as the Schlafli, Gosset, Barnes-Wall, and Leech lattices, besides simple one-dimensional lattices. Via the density evolution technique, we show that the lattices reduce the noise threshold of belief-propagation decoders. We investigate the practical application of the proposed schemes to 10G-Base-T, an emerging Ethernet standard over twisted-pairs at 10 Gbit/sec. A simple 1-dimensional scheme improves upon recent proposals by 0.5-1 dB at BER's approaching 10-11, with half the LDPC coding complexity. Multi-dimensional schemes are seen to reduce the complexity further.

Although iterative equalizers are well-known for mitigating inter-symbol interference (ISI), recent results have shown that the schemes perform poorly in the presence of severe ISI, particularly when coding rates are high. Other equalization schemes, such as the non-iterative canonical decision-feedback equalizer (CDFE), have been shown to be asymptotically optimal on any channel. However, the scheme exhibits very high latency. To trade off between performance and latency, we propose an equalizer structure that iterates with both hard- and soft-decisions. In prior works, hard-decision iterative equalizers were seen to perform poorly, chiefly due to error-propagation in the feedback loop. However, the scheme proposed in this paper outperforms the linear turbo equalizer in both strong and weak ISI. On channels with weak ISI, the equalizer outperforms both the CDFE as well as the ideal DFE with perfect feedback. Simulation results on well-known ISI channels support the findings.

We propose a framework to address the problem of broadcasting a multiplicity of video sequences over a multiuser broadcast channel. The approach is intended to be general, without assumptions about specific video-coding or modulation techniques. However, we do assume the channel is Gaussian and exhibits quasi-static Rayleigh fading. Under the proposed framework, the algorithms seek to minimize the total distortion of multiple sequences broadcast simultaneously. To suit different applications, both greedy and long-term distortion metrics are considered. A salient aspect of this work is support for real-time video transport, hence delay and buffer constraints need to be accounted for. Under these constraints, the algorithms compute a jointly optimal source-rate and transmit-power allocation for all users under a power constraint. It turns out that problem can be formulated efficiently as a geometric program, which can be solved in different ways. In particular, we investigate a class of primal-dual convex algorithms. The complexity of the optimization is seen to scale well with the number of users. For the purpose of comparison, an orthogonal multiplexing scheme is also considered. Numerical results with H.264-coded video show that significant coding gains can be obtained.

Video transmitted over fading wireless channels incurs both encoder-induced distortion and distortion caused by transmission errors. To address these problems, we propose a framework to transmit video reliably over a multi-antenna wireless system. No assumptions are made about specific video-coding standards, except that the encoder employs some variation of motion-compensated block-transform coding. To minimize the total distortion, the scheme optimizes the recently- derived diversity and multiplexing trade-off available on multi-antenna systems. Moreover, this is done jointly with loss-aware rate-distortion optimization (LA-RDO) techniques at the video encoder. Besides minimizing distortion, the algorithm also ensures that delay and buffer constraints are satisfied for real-time transport. We show that problem can be modelled as a short sequence of geometric programs. The overall complexity is linear in the number of antennas. Numerical results with H.264-coded video show that the PSNR at the video-decoder can be improved by various amounts, depending on antenna configuration.

We propose a joint power- and rate-control scheme to broadcast a multiplicity of video sequences over a broadcast channel. The formulation is intended to be general in scope, without assumptions about specific coding or modulation schemes. However, we assume the broadcast channel undergoes quasi-static fading, with channel state information available at the transmitters and receivers. With a weighted sum of distortion terms as a metric, the scheme computes a jointly-optimal source-rate and transmit-power allocation under a power constraint. Besides minimizing distortion, the algorithm must also ensure that delay and buffer constraints are satisfied. Although the problem is not convex when formulated directly, it can be reformulated in convex form as a geometric program. We present numerical results via variable bit-rate (VBR) rate-control of H.264-coded video, optimized jointly with power-control of simple idealized broadcast transmitters.

We propose a simple PAM-based coded modulation scheme that combines low-density parity-check (LDPC) codes and classical maximum-distance separable (MDS) codes. To approach the capacity of an ISI-constrained channel, the code is employed in conjunction with spectral shaping, Tomlinson-Harashima preceding and decision- feedback equalization (DFE). The scheme performs within 2-2.5 dB of un-shaped channel capacity (the sphere-bound) at a BER of 10-12, even with regular LDPC codes of modest block lengths (1000-2000 bits). For further improvement, we consider signal sets on dense multi-dimensional lattices. With codes over the well-known Schlafli, Gosset, Barnes-Wall, and Leech lattices, the constructions reduce the gap to the sphere-bound. We consider the practical application of the proposed schemes to 10G- base-T, an emerging Ethernet standard over twisted-pairs at 10 Gbit/sec. A simple 1-dimensional scheme improves upon recent proposals by 0.5 dB at a BER of 10-11, using a (3,6)-regular code of 2000 bits.

High rate transmission over power lines imposes stringent requirements in coding and equalization, the chief impairments being severe signal attenuation and impulsive noise. Yet, transmission requirements over this medium have reached several Mbit/sec to compete with other types of access. In this paper, we propose a novel PAM-based coded modulation scheme that is well suited to meeting such constraints. The proposed scheme combines Low Density Parity Check (LDPC) codes and maximum-distance separable block codes to achieve high spectral efficiency, low decoding complexity, and a high degree of immunity to impulse noise. To achieve better immunity to burst and impulse noise, a novel interleaving scheme is proposed. To achieve good performance in the presence of inter-symbol interference, the proposed coset-coding is combined with Tomlinson-Harashima precoding and spectral shaping at the transmitter.

We propose a simple pulse-amplitude modulation (PAM)-based coded modulation scheme that overcomes two major constraints of power line channels, viz., severe insertion-loss and impulsive noise. The scheme combines low-density parity-check (LDPC) codes, along with cyclic random-error and burst-error correction codes to achieve high-spectral efficiency, low decoding complexity, and a high degree of immunity to impulse noise. To achieve good performance in the presence of intersymbol interference (ISI) on static or slowly time-varying channels, the proposed coset-coding is employed in conjunction with Tomlinson-Harashima precoding and spectral shaping at the transmitter. In Gaussian noise, the scheme performs within 2 dB of unshaped channel capacity at a bit-error rate (BER) of 10/sup -11/, even with (3,6)-regular LDPC codes of modest length (1000-2000 bits). To mitigate errors due to impulse noise (a combination of synchronous and asynchronous impulses), a multistage interleaver is proposed, each stage tailored to the error-correcting property of each layer of the coset decomposition. In the presence of residual ISI, colored Gaussian noise, as well as severe synchronous and asynchronous impulse noise, the gap to Shannon capacity of the scheme to a Gaussian-noise-only channel is 5.5 dB at a BER of 10/sup -7/.