The optimal rate region for interference networks is characterized when encoding is restricted to random code ensembles with superposition coding and time sharing. A simple simultaneous nonunique decoding rule, under which each receiver decodes for the intended message as well as the interfering messages, is shown to achieve this optimal rate region regardless of the relative strengths of signal, interference, and noise. This result implies that the Han-Kobayashi bound, the best known inner bound on the capacity region of the two-user pair interference channel, cannot be improved merely by using the optimal maximum likelihood decoder.

We consider the problem of channel state amplification in a Gaussian channel with additive Gaussian channel states, where the encoder observes noncausally a noisy version of these states. A complete characterization is provided for the minimum reconstruction distortion under a transmitter power constraint, and it is shown that a simple analog scheme with power control is optimal. More precisely, if the power available to the encoder is below certain threshold, the analog scheme using full power is optimal, however, when the power available to the encoder is above that threshold, analog transmission using only a fixed amount of the available power is optimal. Furthermore, the problem of simultaneous message transmission and Gaussian state amplification with noisy observations is studied, for which an inner bound and two nontrivial outer bounds to the optimal tradeoff between the transmission rate and the state reconstruction distortion are provided. The coding scheme underlying the inner bound combines analog signaling and Gelfand-Pinsker coding, where the latter deviates from the operating point of Costa's dirty paper coding. The first outer bound is obtained by extending the channel decomposition technique, while the second outer bound requires a strategic analysis of the covariance matrix of the relevant random variables.

Motivated by the broadcast view of the interference channel, the new problem of communication with disturbance constraints is formulated. The rate-disturbance region is established for the single constraint case and the optimal encoding scheme turns out to be the same as the Han-Kobayashi scheme for the two user-pair interference channel. This result is extended to the Gaussian vector (multiple-input and multiple-output) case. For the case of communication with two disturbance constraints, inner and outer bounds on the rate-disturbance region for a deterministic model are established. The inner bound is achieved by an encoding scheme that involves rate splitting, Marton coding, and superposition coding, and is shown to be optimal in several nontrivial cases. This encoding scheme can be readily applied to discrete memoryless interference channels and motivates a natural extension of the Han-Kobayashi scheme to more than two user pairs.

A new inner bound on the capacity region of the general index coding problem is established. Unlike most existing bounds that are based on graph theoretic or algebraic tools, the bound relies on a random coding scheme and optimal decoding, and has a simple polymatroidal single-letter expression. The utility of the inner bound is demonstrated by examples that include the capacity region for all index coding problems with up to five messages (there are 9846 nonisomorphic ones).

The problem of simultaneous message transmission and state amplification in a Gaussian channel with additive Gaussian state is studied when the sender has imperfect non-causal knowledge of the state sequence. Inner and outer bounds to the rate-state-distortion region are provided. The coding scheme underlying the inner bound combines analog signaling and Gelfand-Pinsker coding, where the latter deviates from the operating point of Costa's dirty paper coding.

There are two variants of superposition coding schemes. Cover's original superposition coding scheme has code clouds of identical shape, while Bergmans's superposition coding scheme has code clouds of independently generated shapes. These two schemes yield identical achievable rate regions in several scenarios, such as the capacity region for degraded broadcast channels. This paper shows that under optimal decoding, these two superposition coding schemes can result in different rate regions. In particular, it is shown that for the two-receiver broadcast channel, Cover's scheme achieves a larger rate region than Bergmans's scheme in general.

An achievable rate region for certain noisy three-user-pair interference channels is proposed. The channel class under consideration generalizes the three-pair deterministic interference channel (3-DIC) in the same way as the Telatar - Tse noisy two-pair interference channel generalizes the El Gamal - Costa injective channel. Specifically, arbitrary noise is introduced that acts on the combined interference signal before it affects the desired signal. This class of channels includes the Gaussian case. The rate region includes the best-known inner bound on the 3-DIC capacity region, dominates treating interference as noise, and subsumes the Han - Kobayashi region for the two-pair case.

For a receiver that observes a mixture of desired and interfering multiple-input multiple-output (MIMO) transmissions, not all interference has the same severity: its effect is modulated by the degree of alignment between the eigenspaces of the desired and undesired channel matrices. An analytical channel model is proposed to account for this effect. Two metrics of eigenspace compatibility are studied, and a method to generate channels of a given degree of compatibility is derived. The resulting model is parameterized using radio channel measurement data, and an implementation recipe for immediate use of the model is provided.

The problem of communication with disturbance constraints is introduced. The rate-disturbance region is established for the single constraint case. The optimal encoding scheme turns out to be the same as the Han-Kobayashi scheme for the two user-pair interference channel. For communication with two disturbance constraints, a coding scheme and a corresponding inner bound for the deterministic case are presented. The results suggest a natural way to obtain a new inner bound on the capacity region of the interference channel with more than two user pairs.

In multiple-input multiple-output (MIMO) systems, the propagation channels can be characterized by their spatial structure, described by the (complex-valued) channel correlation. Accordingly, also interference in MIMO systems is likely to occur in a spatially structured, correlated way. We discuss that structured spatial interference affects mutual information under interference, depending on the eigenspace alignment between the channel of the desired signal and the channel carrying the interference. Intuitively, worst-case interference occurs, when the channels from the intended signal and the interference show a similar spatial structure. In contrast, least hurtful interference is encountered when these channels are maximally non-aligned. In this paper, we develop an analytical channel model generating multi-user MIMO channels with a given degree of severity of interference, described by the alignment of the channels' eigenspaces. Using radio channel measurements, we parameterize our model to reflect realistic scenarios.

An inner bound to the capacity region of a class of deterministic interference channels with three user pairs is presented. The key idea is to simultaneously decode the combined interference signal and the intended message at each receiver. It is shown that this interference-decoding inner bound is tight under certain strong interference conditions. The inner bound is also shown to strictly contain the inner bound obtained by treating interference as noise, which includes interference alignment for deterministic channels. The gain comes from judicious analysis of the number of combined interference sequences in different regimes of input distributions and message rates. Finally, the inner bound is generalized to the case where each channel output is observed through a noisy channel.

An inner bound to the capacity region of a class of three user pair deterministic interference channels is presented. The key idea is to simultaneously decode the combined interference signal and the intended message at each receiver. It is shown that this interference-decoding inner bound strictly contains the inner bound obtained by treating interference as noise, which includes interference alignment for deterministic channels. The gain comes from judicious analysis of the number of combined interference sequences in different regimes of input distributions and message rates.

Certain deterministic interference channels have been shown to accurately model Gaussian interference channels in the asymptotic low-noise regime. Motivated by this correspondence, we investigate a K user-pair, cyclically symmetric, deterministic interference channel in which each receiver experiences interference only from its neighboring transmitters (Wyner model). We establish the sum capacity for a large set of channel parameters, thus generalizing previous results for the 2-pair case.

Since multi-antenna (MIMO) systems are becoming more popular thanks to their inherent potential for capacity improvement, interference from MIMO transceivers is an increasingly serious concern. Spatial multiplexing schemes are particularly vulnerable to multi-user interference. Fortunately, this interference can be mitigated, when the channel matrices show a sufficient spatial separation. In this paper, we quantify the separability of multi-user MIMO channels using actual measurements in a scenario where a single outdoor base station transmits to two indoor mobile receivers. To quantify the spatial distance between the two users, we compare the spatial correlation matrices using two simple measures: (i) matrix collinearity, and (ii) the condition number ratio. Both measures are directly linked to MIMO system performance. Our measurement-based evaluations demonstrate that the downlink channels of different users can have a significantly different spatial structure, even when the users are in the same room. This leads to the following conclusions: (i) new multi-user MIMO models are needed to describe the spatial characteristics of different users, and (ii) spatial interference can be well managed by appropriate scheduling and precoding algorithms.

In this paper, an empirical model of the indoor distributed channel is presented. In particular, the shadowing and fading statistics are extracted from experimental data at 2.45 GHz in stationary and mobile scenarios. Highlights of the paper include a separate model for static and dynamic shadowing, a model for shadowing correlation, as well as a single analytical distribution of small-scale fading for various types of indoor node mobility.

In this paper, the capacity of several outdoor-to-indoor relay schemes has been investigated using real-world measurements at 2.45 GHz. The considered scenario encompasses an outdoor base station, possibly using multiple antennas, communicating via two hops to distributed single antenna terminals located inside a building. The single-antenna relays are located along the so-called best wall. Capacity results show that in most cases, relaying techniques increase the capacity, even when constraining the global power expense of the network. Considering a combining scheme using the source-to-destination in addition to the relay link does not bring huge benefits for the measured outdoor-to-indoor channels. The best performance is obtained in a relay-and-forward scheme using multiple cooperative relays.

We consider a wireless downlink system with one transmit base station (BS) and two receive subscriber stations (SS1 and SS2) in full frequency reuse. The primary subscriber (SS1) is served in two hops via a relay station (RS). The second subscriber (SS2) is located relatively close to both BS and RS. In a conventional paradigm, SS2 can not receive its message from BS when either BS or RS serves SSI, since the transmissions for SSI cause strong interference at SS2. To improve system throughput, we propose an interference cancellation scheme at SS2 that allows BS to serve SS2 while RS relays. Exploiting the identity of the interfering messages in the two hops, SS2 overhears the interfering message at its initial transmission and cancels its interference latter. Theoretical analysis and realistic simulations show that the proposed scheme can significantly and practically boost system throughput.

In the multi-user MIMO uplink channel, the presence of multiple receive antennas enables the base station to serve a number of users simultaneously, thus increasing overall system throughput. In practice, users have to be scheduled instead of being served all at once. In this work, a novel scheduling metric is proposed based on ergodic sum capacity. A low-SNR Taylor series of the capacity expression is combined with a receiver-correlation channel model to obtain a robust measure of spatial compatibility. Long-term channel knowledge at the base station is sufficient for metric evaluation, which significantly reduces the amount of required channel sounding, compared to previously proposed schemes.

In this paper, the multi-user MIMO downlink channel is considered, where a single transmitter (base station) sends data to several users within the same resource unit. Assuming perfect channel state information (CSI) at the transmitter, different linear precoding schemes are studied, aiming at mean square error minimizing transmission to all users. The exact MMSE solution can be obtained by exploiting uplink/downlink duality. A suboptimal solution based on necessary conditions for MMSE optimality may also be computed directly in the downlink domain. Our results indicate that the performance difference between the direct and duality-based method that is visible in uncoded BER curves vanishes when channel coding is introduced to the system. We also compare the MMSE-optimal approaches to other existing linear precoding schemes (BD, S-MMSE)