Compute-and-Forward: Harnessing Interference Through Structured Codes
Bobak Nazer,Michael Gastpar +1 more
TLDR
In this article, the authors proposed a new strategy, compute-and-forward, that exploits interference to obtain significantly higher rates between users in a network by decoding linear functions of transmitted messages according to their observed channel coefficients rather than ignoring the interference as noise.Abstract:
Interference is usually viewed as an obstacle to communication in wireless networks. This paper proposes a new strategy, compute-and-forward, that exploits interference to obtain significantly higher rates between users in a network. The key idea is that relays should decode linear functions of transmitted messages according to their observed channel coefficients rather than ignoring the interference as noise. After decoding these linear equations, the relays simply send them towards the destinations, which given enough equations, can recover their desired messages. The underlying codes are based on nested lattices whose algebraic structure ensures that integer combinations of codewords can be decoded reliably. Encoders map messages from a finite field to a lattice and decoders recover equations of lattice points which are then mapped back to equations over the finite field. This scheme is applicable even if the transmitters lack channel state information.read more
Citations
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Journal ArticleDOI
Federated Learning in Mobile Edge Networks: A Comprehensive Survey
Wei Yang Bryan Lim,Nguyen Cong Luong,Dinh Thai Hoang,Yutao Jiao,Ying-Chang Liang,Qiang Yang,Dusit Niyato,Chunyan Miao +7 more
TL;DR: The concept of federated learning (FL) as mentioned in this paperederated learning has been proposed to enable collaborative training of an ML model and also enable DL for mobile edge network optimization in large-scale and complex mobile edge networks, where heterogeneous devices with varying constraints are involved.
Posted Content
Federated Learning in Mobile Edge Networks: A Comprehensive Survey
Wei Yang Bryan Lim,Nguyen Cong Luong,Dinh Thai Hoang,Yutao Jiao,Ying-Chang Liang,Qiang Yang,Dusit Niyato,Chunyan Miao +7 more
TL;DR: In a large-scale and complex mobile edge network, heterogeneous devices with varying constraints are involved, this raises challenges of communication costs, resource allocation, and privacy and security in the implementation of FL at scale.
Book
Interference Alignment: A New Look at Signal Dimensions in a Communication Network
TL;DR: This monograph introduces to the reader the idea of interference alignment, traces its origins, reviews a variety of interference aligned schemes, summarizes the diverse settings where the idea is applicable and highlights the common principles that cut across these diverse applications.
Journal ArticleDOI
Making Cell-Free Massive MIMO Competitive With MMSE Processing and Centralized Implementation
Emil Björnson,Luca Sanguinetti +1 more
TL;DR: In this paper, the uplink spectral efficiencies of four different cell-free implementations are analyzed, with spatially correlated fading and arbitrary linear processing, and it is shown that a centralized implementation with optimal minimum mean-square error (MMSE) processing not only maximizes the SE but largely reduces the fronthaul signaling compared to the standard distributed approach.
Patent
Network architecture, methods, and devices for a wireless communications network
Stefan Parkvall,Janne Peisa,Gunnar Mildh,Robert Baldemair,Stefan Wager,Jonas Kronander,Karl Werner,Richard Abrahamsson,Ismet Aktas,Peter Alriksson,Junaid Ansari,Ashraf Shehzad Ali,Henrik Asplund,Fredrik Athley,Håkan Axelsson,Joakim Axmon,Johan Axnäs,Kumar Balachandran,Gunnar Bark,Jan-Erik Berg,Andreas Bergström,Håkan Björkegren,Nadia Brahmi,Cagatay Capar,Anders Carlsson,Andreas Cedergren,Mikael Coldrey,Icaro L. J. da Silva,Erik Dahlman,Ali El Essaili,Ulrika Engström,Mårten Ericson,Erik Eriksson,Mikael Fallgren,Fan Rui,Gabor Fodor,Pål Frenger,Jonas Fridén,Jonas Fröberg Olsson,Anders Furuskär,Johan Furuskog,Virgile Garcia,Ather Gattami,Fredrik Gunnarsson,Ulf Gustavsson,Bo Hagerman,Fredrik Harrysson,Ning He,Martin Hessler,Kimmo Hiltunen,Song-Nam Hong,Dennis Hui,Jörg Huschke,Tim Irnich,Sven Jacobsson,Niklas Jaldén,Simon Järmyr,Zhiyuan Jiang,Martin Johansson,Niklas Johansson,Du Ho Kang,Eleftherios Karipidis,Patrik Karlsson,Ali S. Khayrallah,Caner Kilinc,Göran N. Klang,Sara Landström,Christina Larsson,Gen Li,Lars Lindbom,Robert Lindgren,Bengt Lindoff,Fredrik Lindqvist,Liu Jinhua,Thorsten Lohmar,Qianxi Lu,Lars Manholm,Ivana Maric,Jonas Medbo,Qingyu Miao,Reza Moosavi,Walter Müller,Elena Myhre,Karl Norrman,Bengt-Erik Olsson,Torgny Palenius,Sven Petersson,Jose Luis Pradas,Mikael Prytz,Olav Queseth,Pradeepa Ramachandra,Edgar Ramos,Andres Reial,Thomas Rimhagen,Emil Ringh,Patrik Rugeland,Johan Rune,Joachim Sachs,Henrik Sahlin,Vidit Saxena,Nima Seifi,Yngve Selén,Eliane Semaan,Sachin Sharma,Shi Cong,Johan Sköld,Magnus Stattin,Anders Stjernman,Dennis Sundman,Lars Sundström,Miurel Isabel Tercero Vargas,Claes Tidestav,Sibel Tombaz,Johan Torsner,Hugo Tullberg,Jari Vikberg,Peter von Wrycza,Thomas Walldeen,Pontus Wallentin,Wang Hai,Ke Wang Helmersson,Wang Jianfeng,Yi-Pin Eric Wang,Niclas Wiberg,Wittenmark Emma,Osman Nuri Can Yilmaz,Ali A. Zaidi,Zhang Zhan,Zhang Zhang,Zheng Yanli +129 more
TL;DR: In this article, the uplink access configuration index is used to identify an uplink AP from among a predetermined plurality of AP configurations, and then the AP is transmitted to the wireless communications network according to the identified AP.
References
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Book
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Thomas M. Cover,Joy A. Thomas +1 more
TL;DR: The author examines the role of entropy, inequality, and randomness in the design of codes and the construction of codes in the rapidly changing environment.
Journal ArticleDOI
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Journal ArticleDOI
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Thomas M. Cover,Abbas El Gamal +1 more
TL;DR: In this article, the capacity of the Gaussian relay channel was investigated, and a lower bound of the capacity was established for the general relay channel, where the dependence of the received symbols upon the inputs is given by p(y,y) to both x and y. In particular, the authors proved that if y is a degraded form of y, then C \: = \: \max \!p(x,y,x,2})} \min \,{I(X,y), I(X,Y,Y,X,Y
Capacity theorems for the relay channel
Thomas M. Cover,A. El Gamal +1 more
TL;DR: An achievable lower bound to the capacity of the general relay channel is established and superposition block Markov encoding is used to show achievability of C, and converses are established.