Randomized Resource Allocation in Decentralized Wireless Networks

Moshksar, Kamyar; Bayesteh, Alireza; Khandani, Amir K.

doi:10.1109/tit.2011.2112030

Cited by 9 publications

(10 citation statements)

References 76 publications

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“…Authors in [22] consider a decentralized network of several users sharing a finite number of unlicensed frequency sub-bands. Each user randomly selects a subset of the sub-bands in order to transmit a number of symbols in its Gaussian codeword.…”

Section: B Contributionsmentioning

confidence: 99%

“…This procedure is repeated independently from transmission slot to transmission slot. The analysis presented in [22] applies to a scenario where the number of interfering users remains unchanged. The current paper is in a sense an extension of the randomized resource allocation proposed in [22] to a decentralized network where the number of interferers is variable during the communication period of interest.…”

Section: B Contributionsmentioning

confidence: 99%

“…We need the following lemma [22]: We have the thread of inequalities in (170), as shown at the top of the next page, where (a) follows by the fact that conditioning reduces differential entropy, (b) is by entropy power inequality and (c) is due to h(h 0 u 0 ) = log(πe |h 0 | 2 P θ ) and the fact that by Lemma 5, h(h 1 ξ 1 u 1 + z) ≤ θ log(πe(1 + |h 1 | 2 P θ )) + (1 − θ) log(πe) + h b (θ ). Next, let us show that the lower bounds developed on I (ξ 0 u 0 ; h 0 ξ 0 u 0 + z) and I (ξ 0 u 0 ; h 0 ξ 0 u 0 + h 1 ξ 1 u 1 + z) have the same SNR scaling as these quantities.…”

Section: Appendix F Proof Of Lemmamentioning

confidence: 99%

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Decentralized Wireless Networks With Asynchronous Users and Burst Transmissions

Moshksar

Khandani

2015

IEEE Trans. Inform. Theory

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This paper studies a decentralized wireless network of asynchronous transmitter-receiver pairs with burst transmissions. Each receiver learns about the number of active users, channel coefficients, and mutual delays based on locally available measurements. The estimates for the mutual delays are not perfect, however, they are reliable enough to guarantee successful decoding. Two signalling schemes are addressed, namely, randomized masking (RM) and reduced cycle transmission (RCT). Under RM, the n symbols of a codeword are generated according to a Bernoulli-Gaussian distribution with activity factor 0 < θ ≤ 1. This is in contrast to RCT where each codeword consists of θ n Gaussian symbols followed by n − θ n zeros. Assuming the transmitters are unaware of the number of users, channel coefficients, and mutual delays, the probability of outage under RM is considerably lower compared with RCT if the signal-to-noise ratio (SNR) is sufficiently large. A generalized RCT scheme is also examined where the n − θ n zero symbols are not necessarily located at the end of a codeword. In the asymptote of large SNR, the outage probability becomes vanishingly small under RM, however, it is bounded away from zero for generalized RCT regardless of the value of SNR.

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Section: B Contributionsmentioning

confidence: 99%

Section: B Contributionsmentioning

confidence: 99%

Section: Appendix F Proof Of Lemmamentioning

confidence: 99%

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Decentralized Wireless Networks With Asynchronous Users and Burst Transmissions

Moshksar

Khandani

2015

IEEE Trans. Inform. Theory

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“…Following the randomized resource allocation scenarios proposed in [4], we adopt a strategy where each user trans mits its Gaussian signal with a probability of () and quits transmitting with a probability of 1 -() independently from transmission slot to transmission slot. We call this scheme the randomized masking strategy with activity factor ().…”

Section: B Our Contributionmentioning

confidence: 99%

“…Assuming limT ---+ oo TAT (a) exists, we let lim TAT (a) = a T ---+ oo (4) for which necessarily a ::::; a ::::; � as assumed before. If a = a, there is no overlap between the codewords of the users.…”

Section: T ---+ Oomentioning

confidence: 99%

Randomized on-off signaling for asynchronous interference channels

Moshksar

Khandani

2010

2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers

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Ahstract-This paper addresses a Gaussian interference chan nel consisting of two active users. The channel from each transmitter to each receiver is modeled with quasi-static and non-frequency selective Rayleigh fading. Users are asynchronous, meaning there exists a mutual delay between their transmitted codes. Due to the randomness of delay, no user is aware of the location of the interference burst along its code. As such, no interference cancellation is performed, i.e., users treat each other as noise. By the same token, interference has a mixed Probability Density Function (PDF) as a result of ambiguity on the start of the interference bursts. A stationary model for interference is considered by assuming the starting point of an interferer's codeword is uniformly distributed along the codeword of any user. Due to non-ergodicity of the model, outage analysis is an appropriate tool to study the network. All users follow a locally Randomized Masking (RM) signaling scheme where each transmitter quits transmitting its Gaussian signals independently from transmission to transmission with a certain probability. An upper bound on the probability of outage per user is developed using entropy power inequality and a key upper bound on the differential entropy of a mixed Gaussian random variable. It is shown that by adopting the RM scheme, the probability of outage is strictly lower than that of a scenario where both users keep transmitting their Gaussian signals known as continuous transmission.

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Energy efficiency enhancement of cell‐free massive multiple‐input multiple‐output network employing threshold‐based beamforming

Khodkar

Abouei

2020

Trans Emerging Tel Tech

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The downlink of cell‐free massive multiple‐input multiple‐output network is considered. It is assumed that both access points (APs) and users are equipped with multiple antennas. A heuristic threshold‐based‐beamforming (TBF) protocol is proposed, which performs an AP selection algorithm to significantly improve the total energy efficiency (EE) of the network. The beamforming method that fits the model is the maximum eigenmode beamforming (MEB). The threshold level is determined in such a way that the strongest channel eigenmodes contribute in the downlink transmissions. Indeed, power control coefficients are chosen in such a way that the number of users served by each AP is limited according to the TBF‐based AP selection scheme. The spectral efficiency of the proposed method is investigated considering both perfect and imperfect knowledge of the channel state information at transmitters. Simulation results show that the proposed TBF protocol greatly enhances the total EE of the network compared to the MEB, conjugate beamforming, and zero‐force precoding techniques. Furthermore, a modification algorithm is proposed to obtain the minimum per‐user quality of service requirement, which prevents the dramatic reduction in the EE caused by high inter‐user interference levels.

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Randomized Resource Allocation in Decentralized Wireless Networks

Cited by 9 publications

References 76 publications

Decentralized Wireless Networks With Asynchronous Users and Burst Transmissions

Decentralized Wireless Networks With Asynchronous Users and Burst Transmissions

Randomized on-off signaling for asynchronous interference channels

Energy efficiency enhancement of cell‐free massive multiple‐input multiple‐output network employing threshold‐based beamforming

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