Lele Wang

On the capacity region for index coding

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).

Polar coding for interference networks

A polar coding scheme for interference networks is introduced. The scheme builds on Arikans monotone chain rules for multiple access channels and a method by Hassani and Urbanke to “align” two incompatible polarization processes. It achieves the Han-Kobayashi inner bound for two-user interference channels and generalizes to interference networks.

Sliding-Window Superposition Coding for Interference Networks

Superposition coding with successive cancellation decoding for interference channels is investigated as a low-complexity alternative to the rate-optimal simultaneous decoding. It is shown that regardless of the number of superposition layers and the code distribution of each layer, the standard rate-splitting scheme by Grant, Rimoldi, Urbanke, and Whiting for multiple access channels fails to achieve the simultaneous decoding inner bound on the capacity region for interference channels. A new coding scheme is proposed that uses coding over multiple blocks and sliding-window decoding. With at most two superposition layers, this scheme achieves the simultaneous decoding inner bound for any two-user-pair interference channels without using high-complexity simultaneous multiuser sequence detection. The proposed coding scheme can be also extended to achieve the performance of simultaneous decoding for general interference networks, including the Han-Kobayashi inner bound.

A comparison of superposition coding schemes

There are two variants of superposition coding schemes. Covers original superposition coding scheme has code clouds of identical shape, while Bergmanss 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, Covers scheme achieves a larger rate region than Bergmanss scheme in general.

Sum-capacity of multiple-write noisy memory

Motivated by the emerging interests in non-volatile solid-state computer memories such as flash memories, this paper studies the problem of repeatedly storing information on memory cells with noise and state. The goal is to reliably convey t messages by writing X<inf>j</inf>^j on an n-cell noisy memory p(y<inf>j</inf> |x<inf>j</inf>, y<inf>j−1</inf>), which stores Y <inf>j</inf>ⁿ at the j-th write. We model this problem as a channel with state and introduce the multiple-write noisy memory model, which includes the write-once memory and flash memory models as special cases. The t-write sum-capacity for the multiple-write noisy memory is established as equation where the maximum is over all pmfs p(x<inf>1</inf>) П<inf>j</inf>^t=2 p(u<inf>j</inf> |y<inf>j−1</inf>) and functions xj(u<inf>j</inf>, y<inf>j−1</inf>), j = 2, …, t. We derive three outer bounds on the capacity region and discuss their extension to other classes of memory models. These results extend Wolf, Wyner, Ziv, and Körners work on the binary write-once memory and Fu and Vincks work on the generalized write-once memory to noisy memories.

Interference management via sliding-window superposition coding

The sliding-window superposition coding scheme achieves the performance of simultaneous decoding with point-to-point channel codes and low-complexity decoding. This paper provides a case study of how this conceptual coding scheme can be transformed to a practical coding technique for two-user Gaussian interference channels. Simulation results demonstrate that sliding-window superposition coding can sometimes double the performance of the conventional method of treating interference as noise, still using the standard LTE turbo codes.

Polar coding for relay channels

Polar coding schemes are developed for the decode-forward relaying (digital-to-digital interface) and the compress-forward relaying (analog-to-digital interface) in the three-node relay channel. For decode-forward, a technique based on the recent universal polarization method is applied to create the desired nested structure. For compress-forward, existing methods are generalized to allow arbitrary input distributions and channel statistics. Both schemes achieve full theoretical rates in general relay channels.

Adaptive Sliding-Window Coded Modulation in Cellular Networks

The sliding-window superposition coding scheme aims to mitigate intercell interference at the physical layer by achieving the simultaneous decoding performance with point-to-point channel codes, low- complexity decoding, and minimal coordination overhead. The associated sliding-window coded modulation (SWCM) scheme can be readily implemented using standard off-the-shelf codes, such as the standard LTE turbo code, and tracks the information-theoretical performance guarantee of sliding-window superposition coding. This paper investigates how the basic SWCM scheme performs for the Ped-B fading interference channel model and proposes several improvements in transceiver design, such as soft decoding, input bit-mapping and layer optimization, and power control. Our enhanced SWCM scheme achieves the rates higher than those of the basic SWCM scheme by 10% to 20%, which already shows a significant gain over existing schemes that ignore modulation or coding information of interfering signals. This result confirms the potential of SWCM as a basic building block for physical-layer interference management in 5G and subsequent generations of cellular networks.

WOM with retained messages

Write-once memory (WOM) is a binary storage medium in which each memory cell is initially in state 0 and can be irreversibly programmed to state 1. This paper studies the problem of writing multiple messages into a WOM. Instead of writing a new message (and obliterating old ones) as in the traditional setup, the user wishes to retain access to some of the previously written messages. The capacity region is studied and code constructions are proposed for three canonical cases.

Linear code duality between channel coding and Slepian-Wolf coding

We study the duality between channel coding and Slepian-Wolf coding in the linear coding framework. We show how a code (both its encoder and decoder) for a symmetric channel coding problem can be used to design a code for a general Slepian-Wolf problem. Conversely, we show how a code for a symmetric Slepian-Wolf problem can be used to design a code for a general channel coding problem. The exact relations between the rates and the probability of errors of the two codes are established.