arXiv subjects

Jinwen Shi

Publications and source records attributed to Jinwen Shi.

4 recordsLinked to original sources

arXiv2021

Polar Lattices for Lossy Compression

Polar lattices, which are constructed from polar codes, have recently been proved to be able to achieve the capacity of the additive white Gaussian noise (AWGN) channel. In this work, we propose a new construction of polar lattices to solve the dual problem, i.e., achieving the rate-distortion bound of a memoryless Gaussian source, which means that polar lattices can also be good for the lossy compression of continuous sources. The structure of the proposed polar lattices enables us to integrate the post-entropy coding process into the lattice quantizer, which simplifies the quantization process. The overall complexity of encoding and decoding complexity is $O(N \log^2 N)$ for a sub-exponentially decaying excess distortion. Moreover, the nesting structure of polar lattices further provides solutions for some multi-terminal coding problems. The Wyner-Ziv coding problem for a Gaussian source can be solved by an AWGN capacity-achieving polar lattice nested in a rate-distortion bound achieving one, and the Gelfand-Pinsker problem can be solved in a reversed manner.

cs.IT↗

arXiv2018

Coded Computation Against Distributed Straggling Channel Decoders in the Cloud for Gaussian Uplink Channels

The uplink of a Cloud Radio Access Network (CRAN) architecture is studied, where decoding at the cloud takes place at distributed decoding processors. To mitigate the impact of straggling decoders in the cloud, the cloud re-encodes the received frames via a linear code before distributing them to the decoding processors. Focusing on Gaussian channels, and assuming the use of lattice codes at the users, in this paper the maximum user rate is derived such that all the servers can reliably recover the linear combinations of the messages corresponding to the employed linear code at the cloud. Furthermore, two analytical upper bounds on the frame error rate (FER) as a function of the decoding latency are developed, in order to quantify the performance of the cloud's linear code in terms of the tradeoff between FER and decoding latency at the cloud.

cs.IT↗

arXiv2017

Polar Codes and Polar Lattices for the Heegard-Berger Problem

Explicit coding schemes are proposed to achieve the rate-distortion function of the Heegard-Berger problem using polar codes. Specifically, a nested polar code construction is employed to achieve the rate-distortion function for the doubly-symmetric binary sources when the side information may be absent. The nested structure contains two optimal polar codes for lossy source coding and channel coding, respectively. Moreover, a similar nested polar lattice construction is employed when the source and the side information are jointly Gaussian. The proposed polar lattice is constructed by nesting a quantization polar lattice and a capacity-achieving polar lattice for the additive white Gaussian noise channel.

cs.IT↗

arXiv2016

Extracting Wyner's Common Information Using Polar Codes and Polar Lattices

Explicit constructions of polar codes and polar lattices for both lossless and lossy Gray-Wyner problems are studied. Polar codes are employed to extract Wyner's common information of doubly symmetric binary source; polar lattices are then extended to extract that of a pair of Gaussian sources or multiple Gaussian sources. With regard to the discrete sources, the entire best-known region of the lossless Gray-Wyner problem are achieved by specifying the test channels to construct polar codes without time-sharing. As a result, we are able to give an interpretation that the Wyner's common information remains the same to the lossy case when the distortion is small [1]. Finally, the entire best-known lossy Gray-Wyner region for discrete sources can also be achieved using polar codes. With regard to the Gaussian sources, the best-known lossy Gray-Wyner region for bivariate Gaussian sources with a specific covariance matrix [1] can be achieved by using polar lattices. Moreover, we prove that extracting Wyner's common information of a pair of Gaussian sources is equivalent to implementing the lossy compression for a single Gaussian source, which implies that the common information can be extracted by a polar lattice for quantization. Furthermore, we extend this result to the case of multiple Gaussian sources.

cs.IT↗