Inaki Estella Aguerri

Expected Distortion with Fading Channel and Side Information Quality

We consider the joint source-channel coding problem of sending a Gaussian source over a single input-single output (SISO) fading channel when the decoder has additional correlated side information whose quality is also time-varying. We assume a block fading model for both the channel and side information qualities, and assume perfect state information at the receiver, while the transmitter has only a statistical knowledge. We are interested in the expected squared-error distortion for this system. We study separate source-channel coding,uncoded transmission and a joint source-channel transmission scheme based on joint decoding at the receiver. We then extend joint decoding scheme technique to hybrid digital-analog and multi-layer schemes. We provide numerical results in the finite SNR regime, and derive closed form expressions for the distortion exponent in the high SNR regime.

Hybrid Digital-Analog Transmission for the Gaussian One-Helper Problem

The one-helper joint source-channel coding problem, in which a main source is to be reconstructed with minimum distortion with the help of a correlated helper source, is studied. Focusing on the case of Gaussian sources and a Gaussian multiple access channel (MAC), a generalized hybrid digital-analog scheme is proposed, in which each user allocates its available power among the analog and digital signals and transmits a superposition of the two. It is shown that this generalized hybrid scheme reduces to pure analog or pure digital transmission depending on the system parameters. Finally, the optimal hybrid transmission strategy is identified analytically in certain special scenarios modeling legacy systems.

Distortion exponent in fading MIMO channels with time-varying side information

The joint source-channel coding problem of sending a Gaussian source over a multiple input-multiple output (MIMO) fading channel with time-varying correlated side information at the decoder is studied. A block fading model for both the channel and the side information qualities is considered, and perfect (channel and side information) state information at the receiver is assumed, while the transmitter has only a statistical knowledge. In particular, the high SNR performance is studied by deriving the distortion exponent of various transmission schemes. An upper bound on the distortion exponent is derived by providing the channel state to the encoder while the side information state remains unknown. Separate source and channel coding is considered as well as joint decoding at the receiver. The joint decoding scheme is extended to multiple digital layers. Finally, a hybrid digital-analog (HDA) scheme is analyzed. While the optimal distortion exponent is completely characterized for MISO/SIMO channels, for general MIMO channels, the optimal distortion exponent is characterized in the small bandwidth ratio regime.

Capacity of a class of relay channels with state

The class of orthogonal relay channels with state in which the source and the relay are connected through a channel that depends on a state sequence is considered. It is assumed that the state sequence is fully known at the destination while it is not known at the source or the relay. The source and the relay are connected to the destination through orthogonal channels. The capacity of this class of relay channels is characterized and it is shown to be achieved by the partial decode-compress-and-forward (pDCF) scheme. To the best of our knowledge, this is the first single relay channel model for which the capacity is achieved by pDCF, while partial decode-and-forward (pDF) and compress-and-forward (CF) schemes are suboptimal in general.

Zero-delay joint source-channel coding

In zero-delay joint source-channel coding each source sample is mapped to a channel input, and the samples are directly estimated at the receiver based on the corresponding channel output. Despite its simplicity, uncoded transmission achieves the optimal end-to-end distortion performance in some communication scenarios, significantly simplifying the encoding and decoding operations, and reducing the coding delay. Three different communication scenarios are considered here, for which uncoded transmission is shown to achieve either optimal or near-optimal performance. First, the problem of transmitting a Gaussian source over a block-fading channel with block-fading side information is considered. In this problem, uncoded linear transmission is shown to achieve the optimal performance for certain side information distributions, while separate source and channel coding fails to achieve the optimal performance. Then, uncoded transmission is shown to be optimal for transmitting correlated multivariate Gaussian sources over a multiple-input multiple-output (MIMO) channel in the low signal to noise ratio (SNR) regime. Finally, motivated by practical systems a peak-power constraint (PPC) is imposed on the transmitters channel input. Since linear transmission is not possible in this case, nonlinear transmission schemes are proposed and shown to perform very close to the lower bound.

Capacity of a Class of State-Dependent Orthogonal Relay Channels

The class of orthogonal relay channels in which the orthogonal channels connecting the source terminal to the relay and the destination, and the relay to the destination, depend on a state sequence, is considered. It is assumed that the state sequence is fully known at the destination, while it is not known at the source or the relay. The capacity of this class of relay channels is characterized, and shown to be achieved by the partial decode-compress-and-forward (pDCF) scheme. Then, the capacity of certain binary and Gaussian state-dependent orthogonal relay channels are studied in detail, and it is shown that the compress-and-forward (CF) and partial-decode-and-forward (pDF) schemes are suboptimal in general. To the best of our knowledge, this is the first single relay channel model for which the capacity is achieved by pDCF, while pDF and CF schemes are both suboptimal. Furthermore, it is shown that the capacity of the considered class of state-dependent orthogonal relay channels is in general below the cut-set bound. The conditions under which pDF or CF suffices to meet the cut-set bound, and hence, achieve the capacity, are also derived.

Systematic lossy source transmission over Gaussian time-varying channels

Systematic lossy transmission of a Gaussian source over a time-varying Gaussian channel is considered. A noisy version of the source is transmitted in an uncoded fashion to the destination through a time-varying Gaussian “base channel”, constituting the systematic part of the transmission. A second time-varying Gaussian channel, called the “enhancement channel”, orthogonal to the first one, is available for coded transmission of the source sequence. A block fading model for both channels is considered, and the average end-to-end distortion is studied assuming perfect channel state information only at the receiver. It is shown that if the enhancement channel is static and the base channel gain has a discrete or continuous-quasiconcave distribution, then the separation theorem applies. However, when both channels are block fading, separation theorem does not hold anymore. A lower bound is obtained by providing the enhancement channel state to the encoder, and it is shown that uncoded transmission is exactly optimal for certain base channel fading distributions, while the enhancement channel fading has arbitrary distribution. A joint decoding scheme is also presented and is shown to outperform uncoded transmission and separate source and channel coding for other base channel distributions.

Distortion Exponent in MIMO Fading Channels With Time-Varying Source Side Information

Transmission of a Gaussian source over a time-varying multiple-input multiple-output (MIMO) channel is studied under strict delay constraints. Availability of a correlated side information at the receiver is assumed, whose quality, i.e., its correlation with the source signal, also varies over time. A block-fading model is considered for the states of the time-varying channel and side information; perfect state information at the receiver is assumed, while the transmitter knows only the statistics. The high signal to noise ratio performance, characterized by the distortion exponent, is studied for this joint source-channel coding problem. An upper bound is derived and compared with several lower bounds based on list decoding (LD), hybrid digital-analog transmission, as well as multi-layer schemes, which transmit successive refinements of the source, relying on progressive or superposition transmission with LD. The optimal distortion exponent is characterized for the single-input multiple-output and multiple-input single-output scenarios by showing that the distortion exponent achieved by multi-layer superposition encoding with joint decoding meets the proposed upper bound. In the MIMO scenario, the optimal distortion exponent is characterized in the low bandwidth ratio regime, and it is shown that the multi-layer superposition encoding performs very close to the upper bound in the high bandwidth ratio regime.

Distortion exponent with side-information diversity

The joint source-channel coding problem of sending a Gaussian source with minimum average end-to-end distortion over a time-varying fading channel with time-varying correlated side information at the decoder is studied. A block fading model for both the channel and the side information qualities is considered. Perfect state information of the channel and the side information states is assumed at the receiver, while the transmitter has only a statistical knowledge. The performance is measured in terms of the distortion exponent, which quantifies the exponential decay rate of the expected distortion at high SNR. The effects on the distortion exponent of the bandwidth ratio, the side information quality and the side information diversity are analysed. Two upper bounds on the distortion exponent are derived by providing different channel state information to the encoder, and lower bounds are presented based on separate source and channel coding, joint decoding, uncoded transmission and hybrid digital-analog transmission schemes. In particular, the optimal distortion exponent is characterized in certain regimes by showing that hybrid analog-digital transmission or joint decoding schemes meet the optimal performance.

Wireless source transmission with time-varying side information

Many applications in wireless networks require the transmission of an analog source over a fading channel to be reconstructed with the minimum distortion possible, i.e. multimedia signals over cellular networks or the accumulation of local measurements at a fusion center in sensor networks. In many practical scenarios, the destination receives additional correlated side information either form other transmitters in the network or through its own sensing devices. For example, signals from repeaters in digital TV broadcasting or relay signals in future mobile networks. However, similar to the channel state information at the transmitter, it is costly to provide an estimate of the available source side information to the transmitter.