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H. Vincent Poor

Publications and source records attributed to H. Vincent Poor.

At least 577 records · Page 32Linked to original sources

Relay-Aided Secure Broadcasting for Visible Light Communications

A visible light communication broadcast channel is considered, in which a transmitter luminaire communicates with two legitimate receivers in the presence of an external eavesdropper. A number of trusted cooperative half-duplex relay luminaires are deployed to aid with securing the transmitted data. Transmitters are equipped with single light fixtures, containing multiple light emitting diodes, and receiving nodes are equipped with single photo-detectors, rendering the considered setting as a single-input single-output system. Transmission is amplitude-constrained to maintain operation within the light emitting diodes' dynamic range. Achievable secrecy rate regions are derived under such amplitude constraints for this multi-receiver wiretap channel, first for direct transmission without the relays, and then for multiple relaying schemes: cooperative jamming, decode-and-forward, and amplify-and-forward. Superposition coding with uniform signaling is used at the transmitter and the relays. Further, for each relaying scheme, secure beamforming vectors are carefully designed at the relay nodes in order to hurt the eavesdropper and/or benefit the legitimate receivers. Superiority of the proposed relaying schemes, with secure beamforming, is shown over direct transmission. It is also shown that the best relaying scheme depends on how far the eavesdropper is located from the transmitter and the relays, the number of relays, and their geometric layout.

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Simple Semi-Grant-Free Transmission Strategies Assisted by Non-Orthogonal Multiple Access

Grant-free transmission is an important feature to be supported by future wireless networks since it reduces the signalling overhead caused by conventional grant-based schemes. However, for grant-free transmission, the number of users admitted to the same channel is not caped, which can lead to a failure of multi-user detection. This paper proposes non-orthogonal multiple-access (NOMA) assisted semi-grant-free (SGF) transmission, which is a compromise between grant-free and grant-based schemes. In particular, instead of reserving channels either for grant-based users or grant-free users, we focus on an SGF communication scenario, where users are admitted to the same channel via a combination of grant-based and grant-free protocols. As a result, a channel reserved by a grant-based user can be shared by grant-free users, which improves both connectivity and spectral efficiency. Two NOMA assisted SGF contention control mechanisms are developed to ensure that, with a small amount of signalling overhead, the number of admitted grant-free users is carefully controlled and the interference from the grant-free users to the grant-based users is effectively suppressed. Analytical results are provided to demonstrate that the two proposed SGF mechanisms employing different successive interference cancelation decoding orders are applicable to different practical network scenarios.

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Online Timely Status Updates with Erasures for Energy Harvesting Sensors

An energy harvesting sensor that is sending status updates to a destination through an erasure channel is considered, in which transmissions are prone to being erased with some probability $q$, independently from other transmissions. The sensor, however, is unaware of erasure events due to lack of feedback from the destination. Energy expenditure is normalized in the sense that one transmission consumes one unit of energy. The sensor is equipped with a unit-sized battery to save its incoming energy, which arrives according to a Poisson process of unit rate. The setting is online, in which energy arrival times are only revealed causally after being harvested, and the goal is to design transmission times such that the long term average age of information (AoI), defined as the time elapsed since the latest update has reached the destination successfully, is minimized. The optimal status update policy is first shown to have a renewal structure, in which the time instants at which the destination receives an update successfully constitute a renewal process. Then, for $q\leq\frac{1}{2}$, the optimal renewal policy is shown to have a threshold structure, in which a new status update is transmitted only if the AoI grows above a certain threshold, that is shown to be a decreasing function of $q$. While for $q>\frac{1}{2}$, the optimal renewal policy is shown to be greedy, in which a new status update is transmitted whenever energy is available.

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Partial Recovery of Erdős-Rényi Graph Alignment via $k$-Core Alignment

We determine information theoretic conditions under which it is possible to partially recover the alignment used to generate a pair of sparse, correlated Erdős-Rényi graphs. To prove our achievability result, we introduce the $k$-core alignment estimator. This estimator searches for an alignment in which the intersection of the correlated graphs using this alignment has a minimum degree of $k$. We prove a matching converse bound. As the number of vertices grows, recovery of the alignment for a fraction of the vertices tending to one is possible when the average degree of the intersection of the graph pair tends to infinity. It was previously known that exact alignment is possible when this average degree grows faster than the logarithm of the number of vertices.

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MVG Mechanism: Differential Privacy under Matrix-Valued Query

Differential privacy mechanism design has traditionally been tailored for a scalar-valued query function. Although many mechanisms such as the Laplace and Gaussian mechanisms can be extended to a matrix-valued query function by adding i.i.d. noise to each element of the matrix, this method is often suboptimal as it forfeits an opportunity to exploit the structural characteristics typically associated with matrix analysis. To address this challenge, we propose a novel differential privacy mechanism called the Matrix-Variate Gaussian (MVG) mechanism, which adds a matrix-valued noise drawn from a matrix-variate Gaussian distribution, and we rigorously prove that the MVG mechanism preserves $(ε,δ)$-differential privacy. Furthermore, we introduce the concept of directional noise made possible by the design of the MVG mechanism. Directional noise allows the impact of the noise on the utility of the matrix-valued query function to be moderated. Finally, we experimentally demonstrate the performance of our mechanism using three matrix-valued queries on three privacy-sensitive datasets. We find that the MVG mechanism notably outperforms four previous state-of-the-art approaches, and provides comparable utility to the non-private baseline.

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Peer-to-Peer Energy Trading with Sustainable User Participation: A Game Theoretic Approach

This paper explores the feasibility of social cooperation between prosumers within an energy network in establishing their sustainable participation in peer-to-peer (P2P) energy trading. In particular, a canonical coalition game (CCG) is utilized to propose a P2P energy trading scheme, in which a set of participating prosumers form a coalition group to trade their energy, if there is any, with one another. By exploring the concept of the core of the designed CCG framework, the mid-market rate is utilized as a pricing mechanism of the proposed P2P trading to confirm the stability of the coalition as well as to guarantee the benefit to the prosumers for forming the social coalition. The paper further introduces the motivational psychology models that are relevant to the proposed P2P scheme and it is shown that the outcomes of proposed P2P energy trading scheme satisfy the discussed models. Consequently, it is proven that the proposed scheme is consumer-centric that has the potential to corroborate sustainable prosumers participation in P2P energy trading. Finally, some numerical examples are provided to demonstrate the beneficial properties of the proposed scheme.

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On the Capacity of the Peak Power Constrained Vector Gaussian Channel: An Estimation Theoretic Perspective

This paper studies the capacity of an $n$-dimensional vector Gaussian noise channel subject to the constraint that an input must lie in the ball of radius $R$ centered at the origin. It is known that in this setting the optimizing input distribution is supported on a finite number of concentric spheres. However, the number, the positions and the probabilities of the spheres are generally unknown. This paper characterizes necessary and sufficient conditions on the constraint $R$ such that the input distribution supported on a single sphere is optimal. The maximum $\bar{R}_n$, such that using only a single sphere is optimal, is shown to be a solution of an integral equation. Moreover, it is shown that $\bar{R}_n$ scales as $\sqrt{n}$ and the exact limit of $\frac{\bar{R}_n}{\sqrt{n}}$ is found.

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Approximate Nash Region of the Gaussian Interference Channel with Noisy Output Feedback

In this paper, an achievable $η$-Nash equilibrium ($η$-NE) region for the two-user Gaussian interference channel with noisy channel-output feedback is presented for all $η\geqslant 1$. This result is obtained in the scenario in which each transmitter-receiver pair chooses its own transmit-receive configuration in order to maximize its own individual information transmission rate. At an $η$-NE, any unilateral deviation by either of the pairs does not increase the corresponding individual rate by more than $η$ bits per channel use.

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Ultra-Reliable and Low-Latency Wireless Communication: Tail, Risk and Scale

Ensuring ultra-reliable and low-latency communication (URLLC) for 5G wireless networks and beyond is of capital importance and is currently receiving tremendous attention in academia and industry. At its core, URLLC mandates a departure from expected utility-based network design approaches, in which relying on average quantities (e.g., average throughput, average delay and average response time) is no longer an option but a necessity. Instead, a principled and scalable framework which takes into account delay, reliability, packet size, network architecture, and topology (across access, edge, and core) and decision-making under uncertainty is sorely lacking. The overarching goal of this article is a first step to fill this void. Towards this vision, after providing definitions of latency and reliability, we closely examine various enablers of URLLC and their inherent tradeoffs. Subsequently, we focus our attention on a plethora of techniques and methodologies pertaining to the requirements of ultra-reliable and low-latency communication, as well as their applications through selected use cases. These results provide crisp insights for the design of low-latency and high-reliable wireless networks.

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Securing Downlink Non-Orthogonal Multiple Access Systems by Trusted Relays

A downlink single-input single-output non-orthogonal multiple access system is considered in which a base station (BS) is communicating with two legitimate users in the presence of an external eavesdropper. A group of trusted cooperative half-duplex relay nodes, powered by the BS, is employed to assist the BS's transmission. The goal is to design relaying schemes such that the legitimate users' secrecy rate region is maximized subject to a total power constraint on the BS and the relays' transmissions. Three relaying schemes are investigated: cooperative jamming, decode-and-forward, and amplify-and-forward. Depending on the scheme, secure beamforming signals are carefully designed for the relay nodes that either diminish the eavesdropper's rate without affecting that of the legitimate users, or increase the legitimate users' rates without increasing that of the eavesdropper. The results show that there is no relaying scheme that fits all conditions; the best relaying scheme depends on the system parameters, namely, the relays' and eavesdropper's distances from the BS, and the number of relays. They also show that the relatively simple cooperative jamming scheme outperforms other schemes when the relays are far from the BS and/or close to the eavesdropper.

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Protecting the Grid against IoT Botnets of High-Wattage Devices

We provide methods to prevent line failures in the power grid caused by a newly revealed MAnipulation of Demand (MAD) attacks via an IoT botnet of high-wattage devices. In particular, we develop two algorithms named Securing Additional margin For generators in Economic dispatch (SAFE) Algorithm and Iteratively MiniMize and boUNd Economic dispatch (IMMUNE) Algorithm for finding robust operating points for generators during the economic dispatch such that no lines are overloaded after automatic primary control response to any MAD attacks. In situations that the operating cost of the grid in a robust state is costly (or no robust operating points exist), we provide efficient methods to verify--in advance--if possible line overloads can be cleared during the secondary control after any MAD attacks. We then define the $αD$-robustness notion for the grids indicating that any line failures can be cleared during the secondary control if an adversary can increase/decrease the demands by $α$ fraction. We demonstrate that practical upper and lower bounds on the maximum $α$ for which the grid is $αD$-robust can be found efficiently in polynomial time. Finally, we evaluate the performance of the developed algorithms and methods on realistic power grid test cases. Our work provides the first methods for protecting the grid against potential line failures caused by MAD attacks.

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Delay Minimization for NOMA-MEC Offloading

This paper considers the minimization of the offloading delay for non-orthogonal multiple access assisted mobile edge computing (NOMA-MEC). By transforming the delay minimization problem into a form of fractional programming, two iterative algorithms based on Dinkelbach's method and Newton's method are proposed. The optimality of both methods is proved and their convergence is compared. Furthermore, criteria for choosing between three possible modes, namely orthogonal multiple access (OMA), pure NOMA, and hybrid NOMA, for MEC offloading are established.

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Joint Power and Time Allocation for NOMA-MEC Offloading

This paper considers non-orthogonal multiple access (NOMA) assisted mobile edge computing (MEC), where the power and time allocation is jointly optimized to reduce the energy consumption of offloading. Closed-form expressions for the optimal power and time allocation solutions are obtained and used to establish the conditions for determining whether conventional orthogonal multiple access (OMA), pure NOMA or hybrid NOMA should be used for MEC offloading.

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Mixed Quality of Service in Cell-Free Massive MIMO

Cell-free massive multiple-input multiple-output (MIMO) is a potential key technology for fifth generation wireless communication networks. A mixed quality-of-service (QoS) problem is investigated in the uplink of a cell-free massive MIMO system where the minimum rate of non-real time users is maximized with per user power constraints whilst the rate of the real-time users (RTUs) meet their target rates. First an approximated uplink user rate is derived based on available channel statistics. Next, the original mixed QoS problem is formulated in terms of receiver filter coefficients and user power allocations which can iteratively be solved through two sub-problems, namely, receiver filter coefficient design and power allocation, which are dealt with using a generalized eigenvalue problem and geometric programming, respectively. Numerical results show that with the proposed scheme, while the rates of RTUs meet the QoS constraints, the $90\%$-likely throughput improves significantly, compared to a simple benchmark scheme.

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Beta-Beta Bounds: Finite-Blocklength Analog of the Golden Formula

It is well known that the mutual information between two random variables can be expressed as the difference of two relative entropies that depend on an auxiliary distribution, a relation sometimes referred to as the golden formula. This paper is concerned with a finite-blocklength extension of this relation. This extension consists of two elements: 1) a finite-blocklength channel-coding converse bound by Polyanskiy and Verdú (2014), which involves the ratio of two Neyman-Pearson $β$ functions (beta-beta converse bound); and 2) a novel beta-beta channel-coding achievability bound, expressed again as the ratio of two Neyman-Pearson $β$ functions. To demonstrate the usefulness of this finite-blocklength extension of the golden formula, the beta-beta achievability and converse bounds are used to obtain a finite-blocklength extension of Verdú's (2002) wideband-slope approximation. The proof parallels the derivation of the latter, with the beta-beta bounds used in place of the golden formula. The beta-beta (achievability) bound is also shown to be useful in cases where the capacity-achieving output distribution is not a product distribution due to, e.g., a cost constraint or structural constraints on the codebook, such as orthogonality or constant composition. As an example, the bound is used to characterize the channel dispersion of the additive exponential-noise channel and to obtain a finite-blocklength achievability bound (the tightest to date) for multiple-input multiple-output Rayleigh-fading channels with perfect channel state information at the receiver.

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UAV-Enabled Communication Using NOMA

Unmanned aerial vehicles (UAVs) can be deployed as flying base stations (BSs) to leverage the strength of line-of-sight connections and effectively support the coverage and throughput of wireless communication. This paper considers a multiuser communication system, in which a single-antenna UAV-BS serves a large number of ground users by employing non-orthogonal multiple access (NOMA). The max-min rate optimization problem is formulated under total power, total bandwidth, UAV altitude, and antenna beamwdith constraints. The objective of max-min rate optimization is non-convex in all optimization variables, i.e. UAV altitude, transmit antenna beamwidth, power allocation and bandwidth allocation for multiple users. A path-following algorithm is proposed to solve the formulated problem. Next, orthogonal multiple access (OMA) and dirty paper coding (DPC)-based max-min rate optimization problems are formulated and respective path-following algorithms are developed to solve them. Numerical results show that NOMA outperforms OMA and achieves rates similar to those attained by DPC. In addition, a clear rate gain is observed by jointly optimizing all the parameters rather than optimizing a subset of parameters, which confirms the desirability of their joint optimization.

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IoT for Green Building Management

Buildings consume 60% of global electricity. However, current building management systems (BMSs) are highly expensive and difficult to justify for small to medium-sized buildings. As such, the Internet of Things (IoT), which can monitor and collect a large amount of data on different contexts of a building and feed the data to the processor of the BMS, provides a new opportunity to integrate intelligence into the BMS to monitor and manage the energy consumption of the building in a cost-effective manner. Although an extensive literature is available on IoT based BMS and applications of signal processing techniques for some aspects of building energy management separately, detailed study on their integration to address the overall BMS is quite limited. As such, the proposed paper will address this gap by providing an overview of an IoT based BMS leveraging signal processing and machine learning techniques. It is demonstrated how to extract high-level building occupancy information through simple and low-cost IoT sensors and studied the impact of human activities on energy usage of a building, which can be exploited to design energy conservation measures to reduce the building's energy consumption.

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Privacy-Aware Smart Metering: Progress and Challenges

The next-generation energy network, the so-called smart grid (SG), promises a tremendous increase in efficiency, safety and flexibility of managing the electricity grid as compared to the legacy energy network. This is needed today more than ever, as the global energy consumption is growing at an unprecedented rate, and renewable energy sources have to be seamlessly integrated into the grid to assure a sustainable human development. Smart meters (SMs) are among the crucial enablers of the SG concept; they supply accurate high-frequency information about users' household energy consumption to a utility provider, which is essential for time of use pricing, rapid fault detection, energy theft prevention, while also providing consumers with more flexibility and control over their consumption. However, highly accurate and granular SM data also poses a threat to consumer privacy as non-intrusive load monitoring techniques enable a malicious attacker to infer many details of a user's private life. This article focuses on privacy-enhancing energy management techniques that provide accurate energy consumption information to the grid operator, without sacrificing consumer privacy. In particular, we focus on techniques that shape and modify the actual user energy consumption by means of physical resources, such as rechargeable batteries, renewable energy sources or demand shaping. A rigorous mathematical analysis of privacy is presented under various physical constraints on the available physical resources. Finally, open questions and challenges that need to be addressed to pave the way to the effective protection of users' privacy in future SGs are presented.

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