Computation Over Multiple-Access Channels

By Bobak Anthony Nazer, Michael C. Gastpar. IEEE Transactions on Information Theory, 2007

776 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/63c97a47dec8f96a1d0b3a4d2342a6212456aa47

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Citations in the corpus

Federated Learning via Over-the-Air Computation (2018, methodology): “In consideration of both computation and communication, we shall propose a co-design approach for fast model aggregation by leveraging the principles of over-the-air computation (AirComp) [22].”
Broadband Analog Aggregation for Low-Latency Federated Edge Learning (2018, background): “The idea of AirComp can be traced back to the pioneering work studying functional computation in sensor networks [14].”
The Approximate Capacity of the Many-to-One and One-to-Many Gaussian Interference Channels (2008, background): “…many-user interference channel (with all the signal-to-noise ratios equal to SNR and all interference-to-noise ratios equal to INR = SNR α ) is independent of the number of users and is identical to the 2-user case except for a singularity at α = 1 where the degrees of freedom per user is 1 K .”
Communication-Efficient Edge AI: Algorithms and Systems (2020, methodology): “…data partition based training systems are listed as follows: • Fast aggregation via over-the-air computation: Over-the-air computation is an efﬁcient approach to compute a function of distributed data by exploiting the signal superposition property of the wireless multiple access channel [189].”
Joint Physical Layer Coding and Network Coding for Bidirectional Relaying (2008, methodology): “E xamples of schemes were structured codes outperform random codes have been given in Korner and Marton [8] and more rec ntly by Nazer and Gastpar in [9], [10].”
Convergence of Edge Computing and Deep Learning: A Comprehensive Survey (2019, background): “Aiming to accelerate the global aggregation in FL, [214] takes advantage of over-the-air computation [215]–[217], of”
Optimized constellations for two-way wireless relaying with physical network coding (2009, background): “The usage of structured codes and lattices in the scenarios for two–way relaying with per–codeword denoising at the relay has been investigated in [21, 22].”
Robust Analog Function Computation via Wireless Multiple-Access Channels (2012, background): “In particular, the information-theoretic results in [8] suggest that the superposition property of the wireless channel can be beneficially exploited if the W-MAC is matched in some mathematical sense to the function of interest.”
Capacity of the Gaussian Two-Way Relay Channel to Within ${1\over 2}$ Bit (2009, methodology): “By using nested lattice codes for the uplink, we can exploit the structural gain of computation coding [15], which corresponds to a kind of combined channel and network coding.”
Compute-and-Forward: Harnessing Interference Through Structured Codes (2009, background): “In previous work, we have shown how to build network codes for finite field and Gaussian multiple-access networks [19], [27], [28].”
A Tutorial on Fluid Antenna System for 6G Networks: Encompassing Communication Theory, Optimization Methods and Hardware Designs (2024, neutral): “Hence, communication-while-computing is possible [311].”
Cyber–Physical Systems: A Perspective at the Centennial (2012, background): “Related information theoretic problems are studied in [240].”
Physical-layer network coding: Tutorial, survey, and beyond (2011, background): “However, it can achieve the symmetric exchange information capacity of TRWC at the low SNR region [33,34] (also see Sections 4.1.1 and 4.1.2 of this paper); the symmetric exchange information capacity is defined as the information-theoretic capacity when nodes 1 and 2 want to transmit equal amounts…”
Channel coding and decoding in a relay system operated with physical-layer network coding (2008, background): “In [8-11], it was proved that CNC1 and CNC2 can reliably transmit S1 ⊕ S2 to the relay with a rate approaching the capacity in low and high SNR regions, respectively.”