arXiv subjects

Costas N. Georghiades

Publications and source records attributed to Costas N. Georghiades.

12 recordsLinked to original sources

arXiv2023

Scalable Cell-Free Massive MIMO Unsourced Random Access System

Cell-Free Massive MIMO systems aim to expand the coverage area of wireless networks by replacing a single high-performance Access Point (AP) with multiple small, distributed APs connected to a Central Processing Unit (CPU) through a fronthaul. Another novel wireless approach, known as the unsourced random access (URA) paradigm, enables a large number of devices to communicate concurrently on the uplink. We consider a quasi-static Rayleigh fading channel paired to a scalable cell-free system, wherein a small number of receive antennas in the distributed APs serve devices equipped with a single antenna each. The goal of the study is to extend previous URA results to more realistic channels by examining the performance of a scalable cell-free system. To achieve this goal, we construct a coding scheme that adapts the URA paradigm to various cell-free scenarios. Empirical evidence suggests that using a cell-free architecture can improve the performance of a URA system, especially when taking into account large-scale attenuation and fading.

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arXiv2023

PolarAir: A Compressed Sensing Scheme for Over-the-Air Federated Learning

We explore a scheme that enables the training of a deep neural network in a Federated Learning configuration over an additive white Gaussian noise channel. The goal is to create a low complexity, linear compression strategy, called PolarAir, that reduces the size of the gradient at the user side to lower the number of channel uses needed to transmit it. The suggested approach belongs to the family of compressed sensing techniques, yet it constructs the sensing matrix and the recovery procedure using multiple access techniques. Simulations show that it can reduce the number of channel uses by ~30% when compared to conveying the gradient without compression. The main advantage of the proposed scheme over other schemes in the literature is its low time complexity. We also investigate the behavior of gradient updates and the performance of PolarAir throughout the training process to obtain insight on how best to construct this compression scheme based on compressed sensing.

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arXiv2022

FASURA: A Scheme for Quasi-Static Massive MIMO Unsourced Random Access Channels

This article considers the massive MIMO unsourced random access problem on a quasi-static Rayleigh fading channel. Given a fixed message length and a prescribed number of channel uses, the objective is to construct a coding scheme that minimizes the energy-per-bit subject to a fixed probability of error. The proposed scheme differs from other state-of-the-art schemes in that it blends activity detection, single-user coding, pilot-aided and temporary decisions-aided iterative channel estimation and decoding, minimum-mean squared error (MMSE) estimation, and successive interference cancellation (SIC). We show that an appropriate combination of these ideas can substantially outperform state-of-the-art coding schemes when the number of active users is more than 100, making this the best performing scheme known for this regime.

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arXiv2021

Approximate Support Recovery using Codes for Unsourced Multiple Access

We consider the approximate support recovery (ASR) task of inferring the support of a $K$-sparse vector ${\bf x} \in \mathbb{R}^n$ from $m$ noisy measurements. We examine the case where $n$ is large, which precludes the application of standard compressed sensing solvers, thereby necessitating solutions with lower complexity. We design a scheme for ASR by leveraging techniques developed for unsourced multiple access. We present two decoding algorithms with computational complexities $\mathcal{O}(K^2 \log n+K \log n \log \log n)$ and $\mathcal{O}(K^3 +K^2 \log n+ K \log n \log \log n)$ per iteration, respectively. When $K \ll n$, this is much lower than the complexity of approximate message passing with a minimum mean squared error denoiser% (AMP-MMSE) ,which requires $\mathcal{O}(mn)$ operations per iteration. This gain comes at a slight performance cost. Our findings suggest that notions from multiple access %such as spreading, matched filter receivers and codes can play an important role in the design of measurement schemes for ASR.

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arXiv2019

Asymptotic Performance Analysis of Generalized User Selection for Interference-Limited Multiuser Secondary Networks

We analyze the asymptotic performance of a generalized multiuser diversity scheme for an interference-limited secondary multiuser network of underlay cognitive radio systems. Assuming a large number of secondary users and that the noise at each secondary user's receiver is negligible compared to the interference from the primary transmitter, the secondary transmitter transmits information to the $k$-th best secondary user, namely, the one with the $k$-th highest signal-to-interference ratio (SIR). We use extreme value theory to show that the $k$-th highest SIR converges uniformly in distribution to an inverse gamma random variable for a fixed $k$ and large number of secondary users. We use this result to derive asymptotic expressions for the average throughput, effective throughput, average bit error rate and outage probability of the $k$-th best secondary user under continuous power adaptation at the secondary transmitter, which ensures satisfaction of the instantaneous interference constraint at the primary receiver caused by the secondary transmitter. Numerical simulations show that our derived asymptotic expressions are accurate for different values of system parameters.

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arXiv2018

On the Secrecy Performance of Generalized User Selection for Interference-Limited Multiuser Wireless Networks

We investigate the secrecy performance of a multiuser diversity scheme for an interference-limited wireless network with a base-station (BS), $N$ legitimate users and an eavesdropper, in the presence of a single dominant interferer. Assuming interference dominates noise power at the eavesdropper and at each legitimate user's receiver, the BS transmits information to the legitimate user with the $k$-th best (highest) signal-to-interference ratio. We derive a closed-form expression for the secrecy outage probability for an arbitrary $N$ and an asymptotic expression for a fixed $k$ and large $N$. Furthermore, we derive a closed form asymptotic expression for the ergodic secrecy capacity of the $k$-th best user and show that it scales like $O\left(\log(N)\right)$ for a fixed $k$ and large $N$.

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arXiv2018

On the Asymptotic Throughput of the k-th Best Secondary User Selection in Cognitive Radio Systems

We analyze the asymptotic average and effective throughputs of a multiuser diversity scheme for a secondary multiuser network consisting of multiple secondary users (transmitters) and one secondary receiver. Considering a transmit power adaptation strategy at the secondary users to satisfy the instantaneous interference constraint at the primary receiver, the secondary receiver selects the $k$-th best secondary user for transmission, namely, the one with the $k$-th highest signal-to-noise ratio (SNR). We use extreme value theory to show that the $k$-th highest SNR converges uniformly in distribution to an inverse gamma random variable for a fixed $k$ and large number of secondary users. We use this result to derive closed-form asymptotic expressions for the average and effective throughputs of the $k$-th best secondary user.

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arXiv2014

On Asymptotic Statistics for Geometric Routing Schemes in Wireless Ad-Hoc Networks

In this paper we present a methodology employing statistical analysis and stochastic geometry to study geometric routing schemes in wireless ad-hoc networks. In particular, we analyze the network layer performance of one such scheme, the random $\frac{1}{2}$disk routing scheme, which is a localized geometric routing scheme in which each node chooses the next relay randomly among the nodes within its transmission range and in the general direction of the destination. The techniques developed in this paper enable us to establish the asymptotic connectivity and the convergence results for the mean and variance of the routing path lengths generated by geometric routing schemes in random wireless networks. In particular, we approximate the progress of the routing path towards the destination by a Markov process and determine the sufficient conditions that ensure the asymptotic connectivity for both dense and large-scale ad-hoc networks deploying the random $\frac{1}{2}$disk routing scheme. Furthermore, using this Markov characterization, we show that the expected length (hop-count) of the path generated by the random $\frac{1}{2}$disk routing scheme normalized by the length of the path generated by the ideal direct-line routing, converges to $3π/4$ asymptotically. Moreover, we show that the variance-to-mean ratio of the routing path length converges to $9π^2/64-1$ asymptotically. Through simulation, we show that the aforementioned asymptotic statistics are in fact quite accurate even for finite granularity and size of the network.

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arXiv2013

On the Random 1/2-Disk Routing Scheme in Wireless Ad Hoc Networks

Random 1/2-disk routing in wireless ad-hoc networks is a localized geometric routing scheme in which each node chooses the next relay randomly among the nodes within its transmission range and in the general direction of the destination. We introduce a notion of convergence for geometric routing schemes that not only considers the feasibility of packet delivery through possibly multi-hop relaying, but also requires the packet delivery to occur in a finite number of hops. We derive sufficient conditions that ensure the asymptotic \emph{convergence} of the random 1/2-disk routing scheme based on this convergence notion, and by modeling the packet distance evolution to the destination as a Markov process, we derive bounds on the expected number of hops that each packet traverses to reach its destination.

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arXiv2013

Large Overlaid Cognitive Radio Networks: From Throughput Scaling to Asymptotic Multiplexing Gain

We study the asymptotic performance of two multi-hop overlaid ad-hoc networks that utilize the same temporal, spectral, and spatial resources based on random access schemes. The primary network consists of Poisson distributed legacy users with density λ^{(p)} and the secondary network consists of Poisson distributed cognitive radio users with density λ^{(s)} = (λ^{(p)})^β (β>0, β\neq 1) that utilize the spectrum opportunistically. Both networks are decentralized and employ ALOHA medium access protocols where the secondary nodes are additionally equipped with range-limited perfect spectrum sensors to monitor and protect primary transmissions. We study the problem in two distinct regimes, namely β>1 and 0<β<1. We show that in both cases, the two networks can achieve their corresponding stand-alone throughput scaling even without secondary spectrum sensing (i.e., the sensing range set to zero); this implies the need for a more comprehensive performance metric than just throughput scaling to evaluate the influence of the overlaid interactions. We thus introduce a new criterion, termed the asymptotic multiplexing gain, which captures the effect of inter-network interferences with different spectrum sensing setups. With this metric, we clearly demonstrate that spectrum sensing can substantially improve primary network performance when β>1. On the contrary, spectrum sensing turns out to be unnecessary when β<1 and setting the secondary network's ALOHA parameter appropriately can substantially improve primary network performance.

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arXiv2013

On Randomized Sensing and Access Schemes in Wireless Ad-Hoc Cognitive Networks

Over the past decade we have witnessed a rapid growth and development in wireless communication systems, to the point that conventional spectrum allocation policies may not be able to fulfill them all. Federal Communications Commission (FCC) licenses certain frequency segments to a particular user in a particular geographic area. Industrial, Scientific and Medical (ISM) radio bands have also been envisioned for all other unlicensed user to share, as long as they follow certain power regulations. But with the recent boom in the wireless technologies, these open channels have become overcrowded with everything from wireless networks to wireless controllers. Therefore, the regulatory and standardization agencies have been working on new spectrum regulation policies for wireless communication systems. The underlying idea is to let unlicensed users to use the licensed band as long as they can guarantee low interference to the licensed users. Though seemingly simple, sophisticated interference management protocols are needed to meet the expected level of transparency accepted by licensed users. In this report we adopt the dynamic spectrum access approach to limit the interference to primary users and analyze the performance of the cognitive MAC protocols based on randomized sensing and access schemes.

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arXiv2008

On the Index Coding Problem and its Relation to Network Coding and Matroid Theory

The \emph{index coding} problem has recently attracted a significant attention from the research community due to its theoretical significance and applications in wireless ad-hoc networks. An instance of the index coding problem includes a sender that holds a set of information messages $X=\{x_1,...,x_k\}$ and a set of receivers $R$. Each receiver $ρ=(x,H)\in R$ needs to obtain a message $x\in X$ and has prior \emph{side information} comprising a subset $H$ of $X$. The sender uses a noiseless communication channel to broadcast encoding of messages in $X$ to all clients. The objective is to find an encoding scheme that minimizes the number of transmissions required to satisfy the receivers' demands with \emph{zero error}. In this paper, we analyze the relation between the index coding problem, the more general network coding problem and the problem of finding a linear representation of a matroid. In particular, we show that any instance of the network coding and matroid representation problems can be efficiently reduced to an instance of the index coding problem. Our reduction implies that many important properties of the network coding and matroid representation problems carry over to the index coding problem. Specifically, we show that \emph{vector linear codes} outperform scalar linear codes and that vector linear codes are insufficient for achieving the optimum number of transmissions.

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