27 accepted papers
Leveraging one-bit analog-to-digital converter (ADC) instead of high resolution ADC has been introduced as a promising solution for reducing the power consumption and hardware cost of massive millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems. However, performance loss caused by…
This paper addresses the problem of quickest change detection of an unknown mean-shift in multiple Gaussian data streams. We propose a novel extension of the window-limited CuSum (WL-CuSum) test which utilizes the James-Stein estimator to improve detection performance. Compared to traditional maximu…
This paper considers resource allocation problems for integrated sensing and communications (ISAC) systems operating in dynamic shared spectrum scenarios. Specifically, the paper proposes a new Model-Based Online Learning (MBOL) method that accounts for partial observability caused by noisy observat…
This paper considers waveform optimization problems for managing and mitigating interference in integrated sensing and communications (ISAC) systems. In particular, we consider dynamic shared spectrum scenarios where channel and interference statistics are nonstationary. The focus is on allocating f…
A wireless sensor network performs spatial inference on a physical phenomenon of interest. The areas in which this phenomenon exhibits interesting or anomalous behavior are identified whilst controlling false positives. We expand our previous work based on multiple hypothesis testing (MHT) and local…
Integrated Sensing and Communication Systems (ISAC) that are capable of functioning both as radars and communication systems have a tremendous potential to provide significant performance gains and cost savings and facilitate the sharing of the same energy, spectral, and hardware resources. Managing…
A spatial signal is monitored by a large-scale sensor network. We propose a novel method to identify areas where the signal behaves interestingly, anomalously, or simply differently from what is expected. The sensors pre-process their measurements locally and transmit a local summary statistic to a…
The ever-increasing congestion in the radio spectrum has made coexistence and co-design for radar and communication systems an important problem to address. The radio spectrum is a rapidly time-frequency-space varying resource, and learning is required to use the spectrum and mitigate the interferen…
Detection of multiple spatial events in parallel is of wide interest in many modern applications, such as Internet of Things, environmental monitoring, and wireless communication. Sensor networks can be used for acquiring data and performing inference. In this paper, we take a Bayesian approach and…
We propose a novel three-stage delay-Doppler-angle estimation algorithm for a MIMO-OFDM radar in the presence of inter-carrier interference (ICI). First, leveraging the observation that spatial co-variance matrix is independent of target delays and Dopplers, we perform angle estimation via the MUSIC…
This paper investigates the problem of secret key generation from correlated Gaussian random variables in the short block-length regime. Inspired by the state-of-the-art performance provided by polar codes in the short blocklength regime for channel coding, we propose an explicit protocol based on p…
Several modern applications involve large-scale sensor networks for statistical inference. For example, such sensor networks are of significant interest for Internet of Things applications. In this paper, we consider Bayesian multiple changepoint detection using a sensor network in which a fusion ce…
We consider the problem of secret key generation from correlated Gaussian random variables in the finite blocklength regime. Such keys could be used to encrypt communication in IoT networks, and have provable secrecy guarantees in contrast to classic cryptographic approaches. We investigate the perf…
Sparse arrays can resolve vastly more scatterers than the number of sensors in tasks such as coherent source localization. This entails significant cost reductions compared to conventional arrays with uniformly spaced elements. In this paper, we introduce a parametric sparse linear array configurati…
RF convergence where the same transceiver is used for communications and sensing purposes is taking place. In this paper, a dual-use radar-communications multicarrier waveform is proposed, where different subcarriers are assigned to different subsystems. Two algorithms for subcarrier assignment and…
In this paper we propose a genie-aided strategy to optimize the use of renewable energy (RE) in a community of households with shared access to storage and RE generation facilities. The households are spread over a limited geographical area, and are subject to different time-varying power consumptio…
In this work, a distributed Kalman filtering and clustering framework for sensor networks tasked with tracking multiple state vector sequences is developed. This is achieved through recursively updating the likelihood of a state vector estimation from one agent offering valid information about the s…
In this paper we propose a novel coalitional game theory based optimization method for minimizing the cost of the electricity consumed from the power grid by a community of smart households. A smart household may own both a renewable energy source and an energy storage system (ESS), or only an ESS.…
Geometrical maps of the indoor environment are vital to many applications such as indoor localization and robot navigation. In this paper, a method for three-dimensional indoor mapping using multipath delay and direction estimates is developed. Required high-resolution estimates of multipath propaga…
Learning-based sensing policies for multi-band flexible spectrum use, in particular cognitive radios operating in non-stationary radio environments are proposed. The proposed policies stem from the stochastic non-stationary restless multi-armed bandit formulation of opportunistic spectrum access. Th…
In this paper a novel algorithm is proposed for joint synchronization and localization in ad hoc networks. The proposed algorithm is based on broadcast messaging, with number of messages linear to the number of nodes, versus quadratic for techniques based on two-way message exchange. The identifiabi…
MIMO radars use multiple waveforms in order to resolve more targets and achieve gains in target detection, parameter estimation and recognition, for example. In this paper, we propose a method for optimizing multiple waveforms with low peak sidelobe and peak cross-correlation levels for MIMO radar.…
A joint radar/communication system is considered, where the radar adaptively designs the transmitted waveform such that the interference caused to the cellular systems is strictly controlled. In this paper, different Mutual Information based criteria for radar waveform optimization are proposed and…
In blind equalization (BE) a cost function based on the fit between the equalizer outputs and the signaling constellation is generally defined. To minimize such a cost function, standard gradient descent learning is commonly used. We exploit the idea of relative gradient (RG) learning to modify such…
In indoor wireless localization, navigation and communications, knowledge of the floor plan is valuable side information and provides more reliable performance. Such information may not be available. Estimating indoor maps using sensor networks and time delay measurements, i.e., without angular info…
Radar systems commonly require use of waveforms with low sidelobes and also low cross-correlation if multiple waveforms are being used. It is possible to decrease the apparent peak sidelobe and cross-correlation levels at the receiver by employing a mismatched filter. In this paper, we propose misma…
This paper proposes a new method for scheduling the charging of plug-in electric vehicle's (PEV) battery. The method is employed in the demand side management of smart grids and has the goal of reducing the cost of charging over a long time horizon. The problem of scheduling the PEV battery charging…