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Sara Shahi

Publications and source records attributed to Sara Shahi.

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On the Capacity of the Slotted Strongly Asynchronous Channel with a Bursty User

In this paper, the trade-off between the number of transmissions (or burstiness) $K_n=e^{nν}$ of a user, the asynchronism level $A_n=e^{nα}$ in a slotted strongly asynchronous channel, and the ability to distinguish $M_n=e^{nR}$ messages per transmission with vanishingly error probability is investigated in the asymptotic regime as blocklength $n$ goes to infinity. The receiver must locate and decode, with vanishing error probability in $n$, all of the transmitted messages. Achievability and converse bounds on the trade-off among $(R,α,ν)$ is derived. For cases where $ν=0$ and $ R=0$, achievability and converse bounds coincide. A second model for a bursty user with random access in which the user may access and transmit a message in each block with probability $e^{-nβ}$ in then considered. Achievability and converse bounds on the trade-off between $(R, α, β)$ is also characterized. For cases where $β=α$ and $R=0$, the achievability and converse bounds match.

cs.IT

The Strongly Asynchronous Massive Access Channel

This paper considers a Strongly Asynchronous and Slotted Massive Access Channel (SAS-MAC) where $K_n:=e^{nν}$ different users transmit a randomly selected message among $M_n:=e^{nR}$ ones within a strong asynchronous window of length $A_n:=e^{nα}$ blocks, where each block lasts $n$ channel uses. A global probability of error is enforced, ensuring that all the users' identities and messages are correctly identified and decoded. Achievability bounds are derived for the case that different users have similar channels, the case that users' channels can be chosen from a set which has polynomially many elements in the blocklength $n$, and the case with no restriction on the users' channels. A general converse bound on the capacity region and a converse bound on the maximum growth rate of the number of users are derived.

cs.IT

On Identifying a Massive Number of Distributions

Finding the underlying probability distributions of a set of observed sequences under the constraint that each sequence is generated i.i.d by a distinct distribution is considered. The number of distributions, and hence the number of observed sequences, are let to grow with the observation blocklength $n$. Asymptotically matching upper and lower bounds on the probability of error are derived.

cs.IT

On the Capacity of the AWGN Channel with Additive Radar Interference

This paper investigates the capacity of a communications channel that, in addition to additive white Gaussian noise, also suffers from interference caused by a co-existing radar transmission. The radar interference (of short duty-cycle and of much wider bandwidth than the intended communication signal) is modeled as an additive term whose amplitude is known and constant, but whose phase is independent and identically uniformly distributed at each channel use. The capacity achieving input distribution, under the standard average power constraint, is shown to have independent modulo and phase. The phase is uniformly distributed in $[0,2π]$. The modulo is discrete with countably infinitly many mass points, but only finitely many in any bounded interval. From numerical evaluations, a proper-complex Gaussian input is seen to perform quite well for weak radar interference. We also show that for very large radar interference, capacity is equal to $1/2\log (1 + S)$ and a proper-complex Gaussian input achieves it. It is concluded that the presence of the radar interference results in a loss of half of the degrees of freedom compared to an AWGN channel without radar interference.

cs.IT