Related papers: Double-Sided Information Aided Temporal-Correlated…

Distributed spectrum access (DSA) is challenging since an individual secondary user often has limited sensing capabilities only. One key insight is that channel recommendation among secondary users can help to take advantage of the inherent…

This thesis is concerned with distributed control and coordination of networks consisting of multiple, potentially mobile, agents. This is motivated mainly by the emergence of large scale networks characterized by the lack of centralized…

In a recent paper, the authors proposed a new class of low-complexity iterative thresholding algorithms for reconstructing sparse signals from a small set of linear measurements \cite{DMM}. The new algorithms are broadly referred to as AMP,…

We consider a cognitive shared access scheme consisting of a high priority primary node and a low priority network with $N$ secondary nodes accessing the spectrum. Assuming bursty traffic at the primary node, saturated queues at the…

A common goal in many research areas is to reconstruct an unknown signal x from noisy linear measurements. Approximate message passing (AMP) is a class of low-complexity algorithms for efficiently solving such high-dimensional regression…

This paper considers an active reconfigurable intelligent surface (RIS)-aided communication system, where an M-antenna base station (BS) transmits data symbols to a single-antenna user via an N-element active RIS. We use two-timescale…

The digital twins (DTs) of physical systems and environments enable real-time remote tracking, control, and learning, but require low-latency transmission of updates and sensory data to maintain alignment with their physical counterparts.…

This paper considers information-theoretic models for integrated sensing and communication (ISAC) over multi-access channels (MAC) and device-to-device (D2D) communication. The models are general and include as special cases scenarios with…

This paper addresses the problem of joint user identification and channel estimation (JUICE) for grant-free access in massive machine-type communications (mMTC). We consider the JUICE under a spatially correlated fading channel model as…

As compared to simple actions, activities are much more complex, but semantically consistent with a human's real life. Techniques for action recognition from sensor generated data are mature. However, there has been relatively little work…

Massive MTC support is an important future market segment, but not yet efficiently supported in cellular systems. In this paper we follow-up on recent concepts combining advanced MAC protocols with Compressed Sensing (CS) based multiuser…

For compressive sensing of dynamic sparse signals, we develop an iterative pursuit algorithm. A dynamic sparse signal process is characterized by varying sparsity patterns over time/space. For such signals, the developed algorithm is able…

Gaussian and quadratic approximations of message passing algorithms on graphs have attracted considerable recent attention due to their computational simplicity, analytic tractability, and wide applicability in optimization and statistical…

This paper addresses distributed average tracking for a group of physical double-integrator agents under an undirected graph with reduced requirement on velocity measurements. The idea is that multiple agents track the average of multiple…

We investigate the distributed multi-agent sharing optimization problem in a directed graph, with a composite objective function consisting of a smooth function plus a convex (possibly non-smooth) function shared by all agents. While…

Internet of things, supported by machine-to-machine (M2M) communications, is one of the most important applications for future 6th generation (6G) systems. A major challenge facing by 6G is enabling a massive number of M2M devices to access…

In this paper we focus on the distributed quantized average consensus problem in open multi-agent systems consisting of dynamic directed communication links among active nodes. We propose three communication-efficient distributed algorithms…

We design a self-decision goal-oriented multiple access scheme, where sensing agents observe a common event and individually decide to communicate the event's attributes as updates to the monitoring agents, to satisfy a certain goal.…

The quick and pervasive infiltration of decision support systems, artificial intelligence, and data mining in consumer electronics and everyday life in general has been significant in recent years. Fields such as UX have been facilitating…

We show how to utilize machine learning approaches to improve sliding window algorithms for approximate frequency estimation problems, under the ``algorithms with predictions'' framework. In this dynamic environment, previous…