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IEEE International Symposium on Information Theory (ISIT 2009)

作者： Ravanbakhsh, Mohammad Barbero, Angela I. Ytrehus, Oyvind Univ Bergen Dept Informat N-5020 Bergen Norway Univ Valladolid Dept Appl Math Toyoake Aichi 47011 Japan

ISBN: (纸本)9781424443123

Consider a lossy communication channel for unicast with zero-delay feedback. For this communication scenario, a simple retransmission scheme is optimum with respect to delay. An alternative approach is to use random linear coding in automatic repeat-request (ARQ) mode. We extend the work of Shrader and Ephremides in [1], by deriving an expression for the delay of random linear coding over a field of infinite size. Simulation results for various field sizes are also provided.

关键词： random linear coding Feedback channel Erasure channel ARQ Bulk service Delay

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Reliable Communications over Lossy Wireless Channels by means of the Combination of UDP and random linear coding 19

Reliable Communications over Lossy Wireless Channels by mean...

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IEEE Symposium on Computers and Communication (ISCC)

作者： Gomez, David Rodriguez, Eduardo Agueero, Ramon Munoz, Luis Univ Cantabria E-39005 Santander Spain

ISBN: (纸本)9781479942763

It goes without saying that TCP is the de-facto transport protocol to ensure reliable communications (for instance, in file transfers). On the other hand, and despite the growing relevance of wireless networks, the behavior of TCP over such technologies is well-known to present clear limitations. Several approaches have been made so as to overcome these problems. In this work we propose a different approach to ensure reliable transmissions over wireless links, based on an random linear coding (RLC) scheme, operating together with UDP. We provide a model of the expected performance of the new scheme. Furthermore, based on an extensive simulation campaign over the ns-3 simulation framework, we assess the validity of this model and we compare its performance with that exhibited by the legacy TCP. The results show that, in particular for lossy links, the proposed scheme clearly outperforms TCP.

关键词： TCP performance UDP random linear coding Wireless Networks

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Combination of random linear coding and Cross-Layer Opportunistic Routing: Performance over Bursty Wireless Channels 26

Combination of Random Linear Coding and Cross-Layer Opportun...

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26th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

作者： Garrido, Pablo Gomez, David Aguero, Ramon Serrat, Joan Univ Cantabria E-39005 Santander Spain Univ Politecn Cataluna Barcelona Spain

ISBN: (纸本)9781467367820

In this work we focus on the application of an intra-flow linear random coding scheme over wireless mesh networks. We propose a cross-layer technique to balance the load between relaying nodes, considering the quality of the wireless links. We assess the performance of our proposal by means of an extensive simulation campaign carried out over the ns-3 platform, exploiting a channel model based on a Hidden Markov Process, which accurately mimics the bursty behavior that is observed over real indoor channels. The results show the benefits of the proposed cross-layer technique. In addition, we also discuss the trade-off (between accuracy and overhead) that needs to he considered when obtaining the information that such scheme rely on. Our simulations yield a 10% performance gain when exploiting the link quality information, as it is already obtained by various routing protocols.

关键词： random linear coding Opportunistic Routing Cross-Layer Wireless Mesh Networks Simulation Bursty Channel Models

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A random linear network coding approach to multicast

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IEEE TRANSACTIONS ON INFORMATION THEORY 2006年第10期52卷 4413-4430页

作者： Ho, Tracey Medard, Muriel Koetter, Ralf Karger, David R. Effros, Michelle Shi, Jun Leong, Ben MIT LIDS Cambridge MA 02139 USA Univ Illinois Coordinated Sci Lab Urbana IL 61801 USA MIT CSAIL Cambridge MA 02139 USA

We present a distributed random linear network coding approach for transmission and compression of information in general multisource multicast networks. Network nodes independently and randomly select linear mappings from inputs onto output links over some field. We show that this achieves capacity with probability exponentially approaching I with the code length. We also demonstrate that random linear coding performs compression when necessary in a network, generalizing error exponents for linear Slepian-Wolf coding in a natural way. Benefits of this approach are decentralized operation and robustness to network changes or link failures. We show that this approach can take advantage of redundant network capacity for improved success probability and robustness. We illustrate some potential advantages of random linear network coding over routing in two examples of practical scenarios: distributed network operation and networks with dynamically varying connections. Our derivation of these results also yields a new bound on required field size for centralized network coding on general multicast networks.

关键词： distributed compression distributed networking multicast network coding random linear coding

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Notes on "Exact Decoding Probability Under random linear Network coding"

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IEEE COMMUNICATIONS LETTERS 2012年第5期16卷 720-721页

作者： Zhao, Xubo Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China China Univ Petr Coll Sci Qingdao Peoples R China

In a recent letter, Trullols-Cruces et al. derived the exact decoding probability P-ns(K, N) that a receiver node obtained N linearly independent coded packets among K (K >= N) received coded packets, when the source node uses a random linear coding scheme over a Galois Field GF(q). They discussed P-ns(K, N) both in the case of the source node sending the random linear combination of the original packets, including all-zero combinations, as well as the case of excluding all-zero combinations. However, their derivations are a bit complicated. In this note, we demonstrate simple derivations of the exact decoding probability P-ns(K, N) in both cases. Furthermore, we point out that there is a more succinct expression of P-ns(K, N) for the latter case.

关键词： random linear coding wireless networks decoding probability

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Exploiting Sparse coding: A Sliding Window Enhancement of a random linear Network coding Scheme

Exploiting Sparse Coding: A Sliding Window Enhancement of a ...

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IEEE International Conference on Communications (ICC)

作者： Garrido, Pablo Gomez, David Lanza, Jorge Aguero, Ramon Univ Cantabria Santander Spain

ISBN: (纸本)9781479966646

random linear Network coding (RLNC) is a technique that provides several benefits. For instance, when applied over wireless mesh networks, it can be exploited to ease routing solutions as well as to increase the robustness against packet losses. Nevertheless, the complexity of the decoding process and the required overhead might jeopardize its performance. There is a trade-off when deciding the field and block sizes;larger values decrease the probability of transmitting linearly dependent packets, but they also increase both the required overhead and the decoding complexity. In order to overcome these limitations, we propose a sliding window enhancement;a fixed number of packets (fewer than the block size) is combined within every transmission, and the decoding process can therefore take advantage of the algebra with sparse matrices. The paper presents an analytical model, which is first validated and later broaden by means of an extensive simulation campaign carried out over the ns-3 simulator.

关键词： random linear coding Sparse Matrices Simulation Wireless Networks

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Exploiting Sparse coding: A Sliding Window Enhancement of a random linear Network coding Scheme

Exploiting Sparse Coding: A Sliding Window Enhancement of a ...

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Ad-Hoc and Sensor Networks Symposium

作者： Pablo Garrido David Gomez Jorge Lanza Ramon Aguero Universidad de Cantabria

ISBN: (纸本)9781479966653

关键词： random linear coding Sparse Matrices Simulation Wireless Networks

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Enhanced Opportunistic random linear Source/Network coding with Cross-Layer Techniques over Wireless Mesh Networks 7

Enhanced Opportunistic Random Linear Source/Network Coding w...

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IFIP Wireless Days (WD)

作者： Gomez, David Garrido, Pablo Rodriguez, Eduardo Aguero, Ramon Munoz, Luis Univ Cantabria Santander Spain

ISBN: (纸本)9781479966066

In this paper we thoroughly study, by means of simulation, the combination of source and network random linear coding to provide reliable communications over wireless mesh networks. We assume that intermediate nodes code the packets they have previously stored before forwarding them. We also analyze the possibilities that are brought about by opportunistic listening and forwarding, combining them with the use of cross-layer information. We study the performance of the proposed scheme by means of an extensive simulation campaign carried out over the ns-3 platform;the results show that the coding functionality at the intermediate nodes leads to additional performance enhancements. In addition, they also demonstrate the potential benefits of integrating cross-layer techniques.

关键词： random linear coding Network coding Source coding Cross-Layer Wireless Mesh Networks

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Binary linear Multicast Network coding on Acyclic Networks: Principles and Applications in Wireless Communication Networks

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2009年第5期27卷 738-748页

作者： Li, Xiangming Jiang, Tao Zhang, Qian Wang, Lan Huazhong Univ Sci & Technol Elect & Informat Engn Dept Wuhan 430074 Peoples R China Beijing Inst Technol Sch Informat & Elect Engn Beijing 100081 Peoples R China Wuhan Natl Lab Optoelect Wuhan 430074 Peoples R China Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Kowloon Hong Kong Peoples R China France Telecom R&D Beijing Orange Labs Beijing 100080 Peoples R China

Conventional linear multicast can be constructed on any acyclic network by increasing the order of the finite field to a sufficiently large amount over which the multicast is defined. In this paper, we first discuss the reciprocal theorem of the conventional linear multicast and design a linear multicast on any give acyclic network with constant finite field by extending the multicast dimension and relaxing the constraint on the information storage. In particular, we propose the binary linear multicast network coding and the linear multicast with binary coefficients. With the proposed method, the computation complexity for network coding at the intermediate nodes can be significantly reduced;therefore cheap network nodes can be deployed in a large scale due to their low cost for wireless communications. In addition, some applications of the proposed binary linear multicast network coding in wireless communication networks are illustrated and validated.

关键词： Binary linear multicast random linear coding network coding wireless communication networks

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Federated Learning Over Wireless Device-to-Device Networks: Algorithms and Convergence Analysis

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2021年第12期39卷 3723-3741页

作者： Xing, Hong Simeone, Osvaldo Bi, Suzhi Shenzhen Univ Coll Elect & Informat Engn Shenzhen 518060 Peoples R China Kings Coll London Dept Engn Kings Commun Learning & Informat Proc KCLIP Lab London WC2R 2LS England Peng Cheng Lab Shenzhen 518066 Peoples R China

The proliferation of Internet-of-Things (IoT) devices and cloud-computing applications over siloed data centers is motivating renewed interest in the collaborative training of a shared model by multiple individual clients via federated learning (FL). To improve the communication efficiency of FL implementations in wireless systems, recent works have proposed compression and dimension reduction mechanisms, along with digital and analog transmission schemes that account for channel noise, fading, and interference. The prior art has mainly focused on star topologies consisting of distributed clients and a central server. In contrast, this paper studies FL over wireless device-to-device (D2D) networks by providing theoretical insights into the performance of digital and analog implementations of decentralized stochastic gradient descent (DSGD). First, we introduce generic digital and analog wireless implementations of communication-efficient DSGD algorithms, leveraging random linear coding (RLC) for compression and over-the-air computation (AirComp) for simultaneous analog transmissions. Next, under the assumptions of convexity and connectivity, we provide convergence bounds for both implementations. The results demonstrate the dependence of the optimality gap on the connectivity and on the signal-to-noise ratio (SNR) levels in the network. The analysis is corroborated by experiments on an image-classification task.

关键词： Wireless communication Device-to-device communication Convergence Data models Protocols Topology Stochastic processes Federated learning distributed learning D2D networks decentralized stochastic gradient descent over-the-air computation random linear coding

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