arXiv subjects

Cong Ling

Publications and source records attributed to Cong Ling.

98 records · Page 6Linked to original sources

arXiv2012

Orthogonal symmetric Toeplitz matrices for compressed sensing: Statistical isometry property

Recently, the statistical restricted isometry property (RIP) has been formulated to analyze the performance of deterministic sampling matrices for compressed sensing. In this paper, we propose the usage of orthogonal symmetric Toeplitz matrices (OSTM) for compressed sensing and study their statistical RIP by taking advantage of Stein's method. In particular, we derive the statistical RIP performance bound in terms of the largest value of the sampling matrix and the sparsity level of the input signal. Based on such connections, we show that OSTM can satisfy the statistical RIP for an overwhelming majority of signals with given sparsity level, if a Golay sequence used to generate the OSTM. Such sensing matrices are deterministic, Toeplitz, and efficient to implement. Simulation results show that OSTM can offer reconstruction performance similar to that of random matrices.

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arXiv2011

Wyner-Ziv Coding Based on Multidimensional Nested Lattices

Distributed source coding (DSC) addresses the compression of correlated sources without communication links among them. This paper is concerned with the Wyner-Ziv problem: coding of an information source with side information available only at the decoder in the form of a noisy version of the source. Both the theoretical analysis and code design are addressed in the framework of multi-dimensional nested lattice coding (NLC). For theoretical analysis, accurate computation of the rate-distortion function is given under the high-resolution assumption, and a new upper bound using the derivative of the theta series is derived. For practical code design, several techniques with low complexity are proposed. Compared to the existing Slepian-Wolf coded nested quantization (SWC-NQ) for Wyner-Ziv coding based on one or two-dimensional lattices, our proposed multi-dimensional NLC can offer better performance at arguably lower complexity, since it does not require the second stage of Slepian-Wolf coding.

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arXiv2010

A New Noncoherent Decoder for Wireless Network Coding

This work deals with the decoding aspect of wireless network coding in the canonical two-way relay channel where two senders exchange messages via a common relay and they receive the mixture of two messages. One of the recent works on wireless network coding was well explained by Katti \textit{et al.} in SIGCOMM'07. In this work, we analyze the issue with one of their decoders when minimum-shift keying (MSK) is employed as the modulation format, and propose a new noncoherent decoder in the presence of two interfering signals.

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arXiv2010

Variants of the LLL Algorithm in Digital Communications: Complexity Analysis and Fixed-Complexity Implementation

The Lenstra-Lenstra-Lovász (LLL) algorithm is the most practical lattice reduction algorithm in digital communications. In this paper, several variants of the LLL algorithm with either lower theoretic complexity or fixed-complexity implementation are proposed and/or analyzed. Firstly, the $O(n^4\log n)$ theoretic average complexity of the standard LLL algorithm under the model of i.i.d. complex normal distribution is derived. Then, the use of effective LLL reduction for lattice decoding is presented, where size reduction is only performed for pairs of consecutive basis vectors. Its average complexity is shown to be $O(n^3\log n)$, which is an order lower than previously thought. To address the issue of variable complexity of standard LLL, two fixed-complexity approximations of LLL are proposed. One is fixed-complexity effective LLL, while the other is fixed-complexity LLL with deep insertion, which is closely related to the well known V-BLAST algorithm. Such fixed-complexity structures are much desirable in hardware implementation since they allow straightforward constant-throughput implementation.

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arXiv2010

On the Proximity Factors of Lattice Reduction-Aided Decoding

Lattice reduction-aided decoding features reduced decoding complexity and near-optimum performance in multi-input multi-output communications. In this paper, a quantitative analysis of lattice reduction-aided decoding is presented. To this aim, the proximity factors are defined to measure the worst-case losses in distances relative to closest point search (in an infinite lattice). Upper bounds on the proximity factors are derived, which are functions of the dimension $n$ of the lattice alone. The study is then extended to the dual-basis reduction. It is found that the bounds for dual basis reduction may be smaller. Reasonably good bounds are derived in many cases. The constant bounds on proximity factors not only imply the same diversity order in fading channels, but also relate the error probabilities of (infinite) lattice decoding and lattice reduction-aided decoding.

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arXiv2010

On the Universality of Sequential Slotted Amplify and Forward Strategy in Cooperative Communications

While cooperative communication has many benefits and is expected to play an important role in future wireless networks, many challenges are still unsolved. Previous research has developed different relaying strategies for cooperative multiple access channels (CMA), cooperative multiple relay channels (CMR) and cooperative broadcast channels (CBC). However, there lacks a unifying strategy that is universally optimal for these three classical channel models. Sequential slotted amplify and forward (SSAF) strategy was previously proposed to achieve the optimal diversity and multiplexing tradeoff (DMT) for CMR. In this paper, the use of SSAF strategy is extended to CBC and CMA, and its optimality for both of them is shown. For CBC, a CBC-SSAF strategy is proposed which can asymptotically achieve the DMT upper bound when the number of cooperative users is large. For CMA, a CMA-SSAF strategy is proposed which even can exactly achieve the DMT upper bound with any number of cooperative users. In this way, SSAF strategy is shown to be universally optimal for all these three classical channel models and has great potential to provide universal optimality for wireless cooperative networks.

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arXiv2010

Wireless Network Coding with Imperfect Overhearing

Not only is network coding essential to achieve the capacity of a single-session multicast network, it can also help to improve the throughput of wireless networks with multiple unicast sessions when overheard information is available. Most previous research aimed at realizing such improvement by using perfectly overheard information, while in practice, especially for wireless networks, overheard information is often imperfect. To date, it is unclear whether network coding should still be used in such situations with imperfect overhearing. In this paper, a simple but ubiquitous wireless network model with two unicast sessions is used to investigate this problem. From the diversity and multiplexing tradeoff perspective, it is proved that even when overheard information is imperfect, network coding can still help to improve the overall system performance. This result implies that network coding should be used actively regardless of the reception quality of overheard information.

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arXiv2006

Complex Lattice Reduction Algorithm for Low-Complexity MIMO Detection

Recently, lattice-reduction-aided detectors have been proposed for multiple-input multiple-output (MIMO) systems to give performance with full diversity like maximum likelihood receiver, and yet with complexity similar to linear receivers. However, these lattice-reduction-aided detectors are based on the traditional LLL reduction algorithm that was originally introduced for reducing real lattice bases, in spite of the fact that the channel matrices are inherently complex-valued. In this paper, we introduce the complex LLL algorithm for direct application to reduce the basis of a complex lattice which is naturally defined by a complex-valued channel matrix. We prove that complex LLL reduction-aided detection can also achieve full diversity. Our analysis reveals that the new complex LLL algorithm can achieve a reduction in complexity of nearly 50% over the traditional LLL algorithm, and this is confirmed by simulation. It is noteworthy that the complex LLL algorithm aforementioned has nearly the same bit-error-rate performance as the traditional LLL algorithm.

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