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Ali Haghi

dblp:40/9225 · DBLP profile ↗
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7ranked-venue papers
7as first author
2since 2021 · last 2021
0000-0003-2824-021XORCID · corroborated

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

Theory of computation · 4 · 4 first-author · 2 since 2021Applied, interdisciplinary, general and emerging computing · 3 · 3 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.

Theoretical computer science
3 papers
Information theory · 89% Coding theory · 11%
Computer networks
1 paper
Physical-layer communications · 100%

Topics — the 16 heaviest of 16, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information theory › network information theory › interference channel
gaussian interference channel
1.022021
Boundary of the Gaussian Han-Kobayashi Rate Region · IEEE Trans. Inf. Theory 2021
Rate Splitting and Successive Decoding for Gaussian Interference Channels · IEEE Trans. Inf. Theory 2021
Information theory › network information theory
interference channel
1.022021
Boundary of the Gaussian Han-Kobayashi Rate Region · IEEE Trans. Inf. Theory 2021
Rate Splitting and Successive Decoding for Gaussian Interference Channels · IEEE Trans. Inf. Theory 2021
Information theory › network information theory › interference channel
han-kobayashi region
0.512021
Boundary of the Gaussian Han-Kobayashi Rate Region · IEEE Trans. Inf. Theory 2021
Information theory › network information theory
rate region
0.512021
Boundary of the Gaussian Han-Kobayashi Rate Region · IEEE Trans. Inf. Theory 2021
Information theory › network information theory › interference channel
rate splitting
0.512021
Rate Splitting and Successive Decoding for Gaussian Interference Channels · IEEE Trans. Inf. Theory 2021
Coding theory › error-correcting codes › decoding › channel decoding
successive decoding
0.512021
Rate Splitting and Successive Decoding for Gaussian Interference Channels · IEEE Trans. Inf. Theory 2021
Physical-layer communications › MIMO
interference channel
0.412019
Delay in Cooperative Communications: Achieving Higher Multiplexing Gain in Gaussian Interference Channels With Full-Duplex Transmitters · IEEE Trans. Inf. Theory 2019
Physical-layer communications › MIMO
multiplexing gain
0.412019
Delay in Cooperative Communications: Achieving Higher Multiplexing Gain in Gaussian Interference Channels With Full-Duplex Transmitters · IEEE Trans. Inf. Theory 2019
Physical-layer communications
power allocation
0.412019
Delay in Cooperative Communications: Achieving Higher Multiplexing Gain in Gaussian Interference Channels With Full-Duplex Transmitters · IEEE Trans. Inf. Theory 2019
Physical-layer communications › power allocation
water-filling
0.412019
Delay in Cooperative Communications: Achieving Higher Multiplexing Gain in Gaussian Interference Channels With Full-Duplex Transmitters · IEEE Trans. Inf. Theory 2019
Information theory › network information theory › multiuser capacity
sum-rate
0.112021
Boundary of the Gaussian Han-Kobayashi Rate Region · IEEE Trans. Inf. Theory 2021
Information theory › network information theory › multiuser capacity
sum-rate capacity
0.112021
Rate Splitting and Successive Decoding for Gaussian Interference Channels · IEEE Trans. Inf. Theory 2021
Information theory › channel capacity
fading channel
0.112011
The Capacity Region of p -Transmitter/ q -Receiver Multiple-Access Channels With Common Information · IEEE Trans. Inf. Theory 2011
Information theory › network information theory
multiple-access channel
0.112011
The Capacity Region of p -Transmitter/ q -Receiver Multiple-Access Channels With Common Information · IEEE Trans. Inf. Theory 2011
Physical-layer communications › modulation › multicarrier modulation
OFDM
0.112019
Delay in Cooperative Communications: Achieving Higher Multiplexing Gain in Gaussian Interference Channels With Full-Duplex Transmitters · IEEE Trans. Inf. Theory 2019
Information theory › communication channels
channel state information
0.012011
The Capacity Region of p -Transmitter/ q -Receiver Multiple-Access Channels With Common Information · IEEE Trans. Inf. Theory 2011

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

time-sharing · 0.5successive decoding · 0.5rate splitting · 0.5power splitting · 0.5information-theoretic analysis · 0.4convex optimization · 0.4conferencing encoders · 0.1coding theorem · 0.1
YearPublicationVenuePosition
2021 Rate Splitting and Successive Decoding for Gaussian Interference Channels
abstract
Most coding schemes proposed for the interference channel take advantage of joint decoding to enlarge rate region. However, decoding complexity escalates considerably when joint decoding is used. This paper studies the achievable sum-rate of the two-user Gaussian interference channel when joint decoding is replaced by successive decoding. First, the strong interference class is examined, and it is proved that if transmitters' powers satisfy certain conditions, successive decoding is optimal and achieves the sum-capacity. The number of the required splits, the amount of power allocated to each split, and the order of decoding at receivers are explicitly determined. Second, the weak interference class is examined. A novel rate-splitting scheme is proposed that does not use joint decoding. The number of required splits and the amount of power allocated to each split are expressed in closed forms. It is shown that, for a wide range of transmitters' powers, this scheme achieves the sum-rate of the Gaussian Han-Kobayashi scheme. Moreover, it is proved that the difference between the sum-rate of this scheme and that of the Gaussian Han-Kobayashi scheme is bounded, for all values of transmitters' powers.
Ali Haghi, Amir K. Khandani
IEEE Trans. Inf. Theory1
2021 Boundary of the Gaussian Han-Kobayashi Rate Region
abstract
The best-known achievable rate region for the two-user Gaussian interference channel corresponds to the Han-Kobayashi scheme. However, mathematical expressions that characterize the Han-Kobayashi rate region are complicated. This complexity hinders a comprehensive understanding of the rate region. For instance, when interference is weak, the maximum achievable sum-rate of the Han-Kobayashi scheme has been unknown. This paper studies the sum-rate of the Han-Kobayashi scheme with Gaussian inputs and fully characterizes the maximum achievable sum-rate, when no time sharing is used. The optimal power-splitting variables and the corresponding maximum achievable sum-rate are explicitly expressed in closed forms. With the same approach, the maximum weighted sum-rate is expressed that characterizes the boundary of the Han-Kobayashi region without time sharing. Moreover, when time sharing is used, the boundary is expressed in terms of the upper concave envelope of a function of transmitters' powers.
Ali Haghi, Amir K. Khandani
IEEE Trans. Inf. Theory1
2019 Delay in Cooperative Communications: Achieving Higher Multiplexing Gain in Gaussian Interference Channels With Full-Duplex Transmitters
abstract
Delay, guaranteeing causality, is inevitable in cooperative communication systems. Traditionally, delay granularity has been limited to one symbol; however, channel delay is in fact governed by channel memory and can be shorter. For example, the delay requirement in orthogonal frequency-division multiplexing, captured in the cyclic prefix, is typically much shorter than the symbol itself. This perspective is used to study the two-user Gaussian interference channel with full-duplex transmitters. By superimposing the signal from the other node onto its own signal, each transmitter cancels the interference at its receiver. Among other results, it is proved that under a mild condition, the maximum multiplexing gain of this channel is in fact two, rather than the limit of one, previously shown under the traditional constraint of causal delay. Further, the optimal power allocation among orthogonal sub-carriers, which maximizes the achievable sum-rate, is shown to be a generalization of the well-known water filling. Simulation results are included to demonstrate the improvement in the achievable sum-rate when full-duplex transmitters are used.
Ali Haghi, Neda Mohammadizadeh, Amir K. Khandani
IEEE Trans. Inf. Theory1
2016 The maximum Han-Kobayashi sum-rate for Gaussian interference channels
abstract
The best known achievable rate region for the two-user Gaussian interference channel is due to the Han-Kobayashi (HK) scheme. The HK achievable region includes the regions achieved by all other known schemes. However, mathematical expressions that characterize the HK region are complicated and involve a time sharing variable and two arbitrary power splitting variables. Accordingly, the boundary points of the HK region, and in particular the maximum HK sum-rate, are not known in general. This paper studies the sum-rate of the HK scheme with Gaussian inputs. For the weak interference class, this study fully characterizes the maximum achievable sum-rate and shows that the weak interference class is partitioned into five regions. For each region, the optimal power splitting and the corresponding maximum achievable sum-rate are expressed in closed forms. Moreover, we show that the same approach can be adopted to characterize all boundary points.
Ali Haghi, Amir K. Khandani
ISIT1
2014 The separability and ergodic sum-rate of parallel Gaussian interference channels
abstract
The achievable region of parallel Gaussian interference channels is investigated. The known coding schemes proposed for the the two-user Gaussian interference channel are extended to parallel Gaussian interference channels. The optimality of separate coding for two coding schemes namely, time division with power control and treat as noise, is proved. Moreover, the necessity of joint coding for simultaneous non-unique decoding and Han-Kobayashi coding is demonstrated. For all mentioned schemes, the optimal covariance matrix is shown to be diagonal. In addition, the ergodic fading interference channel is studied. The ergodic achievable sum-rate is investigated for different coding schemes and the optimality of diagonal covariance matrices is shown. It is proved that for time division with power control and simultaneous non-unique decoding, uniform power allocation over all sub-channels is sum-rate optimal.
Ali Haghi, Amir K. Khandani
ISIT1
2011 The Capacity Region of p -Transmitter/ q -Receiver Multiple-Access Channels With Common Information
abstract
This paper investigates the capacity problem for some multiple-access scenarios with cooperative transmitters. First, a general Multiple-Access Channel (MAC) with common information, i.e., a scenario where p transmitters send private messages and also a common message to q receivers and each receiver decodes all of the messages, is considered. The capacity region of the discrete memoryless channel is characterized. Then, the general Gaussian fading MAC with common information wherein partial Channel State Information (CSI) is available at the transmitters (CSIT) and perfect CSI is available at the receivers (CSIR) is investigated. A coding theorem is proved for this model that yields an exact characterization of the throughput capacity region. Finally, a two-transmitter/one-receiver Gaussian fading MAC with conferencing encoders with partial CSIT and perfect CSIR is studied and its capacity region is determined. For the Gaussian fading models with CSIR only (transmitters have no access to CSIT), some numerical examples and simulation results are provided for Rayleigh fading.
Ali Haghi, Reza Khosravi-Farsani, Mohammad Reza Aref, Farrokh Marvasti
IEEE Trans. Inf. Theory1
2010 The capacity region of fading Multiple Access Channels with cooperative encoders and partial CSIT
abstract
In this paper, we study the two-user Gaussian fading Multiple Access Channel (MAC) with cooperative encoders. Two different scenarios are studied: the Gaussian fading MAC with a common message, and the Gaussian fading MAC with conferencing encoders. The throughput capacity region of these channels with partial Channel State Information (CSI) at the transmitters (CSIT) and perfect CSI at the receiver (CSIR) is established. For the Gaussian fading systems with only CSIR (transmitters have no access to CSIT), some numerical examples and simulation results are provided for Rayleigh fading models.
Ali Haghi, Reza Khosravi-Farsani, Mohammad Reza Aref, Farrokh Marvasti
ISIT1