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Babak Mamandipoor

dblp:119/3837 · DBLP profile ↗
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4ranked-venue papers
3as first author
0since 2021 · last 2019
0000-0002-0135-0059ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-authorTheory of computation · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Physical-layer communications · 100%
Theoretical computer science
1 paper
Information theory · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications › multiple access › multiple access channel
capacity region
0.212014
Capacity-Achieving Distributions in Gaussian Multiple Access Channel With Peak Power Constraints · IEEE Trans. Inf. Theory 2014
Physical-layer communications › multiple access
multiple access channel
0.212014
Capacity-Achieving Distributions in Gaussian Multiple Access Channel With Peak Power Constraints · IEEE Trans. Inf. Theory 2014
Physical-layer communications › power constraint
peak power constraint
0.212014
Capacity-Achieving Distributions in Gaussian Multiple Access Channel With Peak Power Constraints · IEEE Trans. Inf. Theory 2014
Information theory › information measures › mutual information
I-MMSE relation
0.112014
Capacity-Achieving Distributions in Gaussian Multiple Access Channel With Peak Power Constraints · IEEE Trans. Inf. Theory 2014

Methods — techniques the papers use, named apart from their topics

orthogonal code division · 0.4discrete distribution optimization · 0.4
YearPublicationVenuePosition
2019 Millimeter wave imaging using sparse arrays
Babak Mamandipoor, Mojtaba Fallahpour, Amin Arbabian, Upamanyu Madhow
Signal Process.1
2014 Capacity-Achieving Distributions in Gaussian Multiple Access Channel With Peak Power Constraints
abstract
This paper addresses a two-user Gaussian multiple access channel (MAC) under peak power constraints at the transmitters. It is shown that generating the code-books of both users according to discrete distributions with a finite number of mass points achieves the largest weighted sum-rate in the network. This verifies that any point on the boundary of the capacity region of a two-user MAC under peak power constraints at both transmitters is achieved by discrete distributions with a finite number of mass points. Although the capacity-achieving distributions are not necessarily unique, it is verified that only discrete distributions with a finite number of mass points can achieve a point on the boundary of the capacity region. It is shown that there exist an infinite number of sum-rate-optimal points on the boundary of the capacity region. In contrast to the Gaussian MAC with average power constraints, we verify that time division (TD) cannot achieve any of the sum-rate-optimal points in the Gaussian MAC with peak power constraints. Using the so-called I-MMSE identity of Guo et al., the largest achievable sum-rate by orthogonal code division (OCD) is characterized where it is shown that Walsh-Hadamard spreading codes of length 2 are optimal. In the symmetric case where the peak power constraints at both transmitters are identical, we verify that OCD can achieve a sum-rate that is strictly larger than the highest sum-rate achieved by TD. Finally, it is demonstrated that there are values for the maximum peak power at the transmitters such that OCD can not achieve any of the sum-rate-optimal points on the boundary of the capacity region.
Babak Mamandipoor, Kamyar Moshksar, Amir K. Khandani
IEEE Trans. Inf. Theory1
2013 On Orthogonal signalling in Gaussian Multiple Access Channel with peak constraints
abstract
This paper is a follow up to [1] on the two-user Gaussian Multiple Access Channel (MAC) with peak constraints at the transmitters. It is shown that there exist an infinite number of sum-rate-optimal points on the boundary of the capacity region. In contrast to the Gaussian MAC with power constraints, we verify that Time Division (TD) can not achieve any of the sum-rate-optimal points in the Gaussian MAC with peak constraints. Using the so-called I-MMSE identity of Guo et.al, the largest achievable sum-rate by Orthogonal Code Division (OCD) is characterized where it is shown that Walsh-Hadamard spreading codes of length 2 are optimal. In the symmetric case where the peak constraints at both transmitters are similar, we verify that OCD can achieve a sum-rate that is strictly larger than the highest sum-rate achieved by TD. Finally, it is demonstrated that there are values for the maximum peak at the transmitters such that OCD can not achieve any of the sum-rate-optimal points on the boundary of the capacity region.
Kamyar Moshksar, Babak Mamandipoor, Amir K. Khandani
ISIT2
2012 On the sum-capacity of Gaussian MAC with peak constraint
abstract
This paper addresses a two-user Gaussian Multiple Access Channel (MAC) under peak constraints at the transmitters. It is shown that generating the code-books of both users according to discrete distributions achieves the largest sum-rate in the network. In other words, sum-capacity achieving input distributions for this channel are discrete with a finite number of mass points. We also demonstrate uniqueness of the input distributions which achieve rates at any of the corner points of the capacity region of the channel.
Babak Mamandipoor, Kamyar Moshksar, Amir K. Khandani
ISIT1