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H. Vincent Poor

Publications and source records attributed to H. Vincent Poor.

At least 847 records · Page 47Linked to original sources

A Vector Generalization of Costa's Entropy-Power Inequality with Applications

This paper considers an entropy-power inequality (EPI) of Costa and presents a natural vector generalization with a real positive semidefinite matrix parameter. This new inequality is proved using a perturbation approach via a fundamental relationship between the derivative of mutual information and the minimum mean-square error (MMSE) estimate in linear vector Gaussian channels. As an application, a new extremal entropy inequality is derived from the generalized Costa EPI and then used to establish the secrecy capacity regions of the degraded vector Gaussian broadcast channel with layered confidential messages.

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Cooperative Multiplexing: Toward Higher Spectral Efficiency in Multi-antenna Relay Networks

Previous work on cooperative communications has concentrated primarily on the diversity benefits of such techniques. This paper, instead, considers the multiplexing benefits of cooperative communications. First, a new interpretation on the fundamental tradeoff between the transmission rate and outage probability in multi-antenna relay networks is given. It follows that multiplexing gains can be obtained at any finite SNR, in full-duplex multi-antenna relay networks. Thus relaying can offer not only stronger link reliability, but also higher spectral efficiency. Specifically, the decode-and-forward protocol is applied and networks that have one source, one destination, and multiple relays are considered. A receive power gain at the relays, which captures the network large scale fading characteristics, is also considered. It is shown that this power gain can significantly affect the system diversity-multiplexing tradeoff for any finite SNR value. Several relaying protocols are proposed and are shown to offer nearly the same outage probability as if the transmit antennas at the source and the relay(s) were co-located, given certain SNR and receive power gains at the relays. Thus a higher multiplexing gain than that of the direct link can be obtained if the destination has more antennas than the source. Much of the analysis in the paper is valid for arbitrary channel fading statistics. These results point to a view of relay networks as a means for providing higher spectral efficiency, rather than only link reliability.

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How Much Information can One Get from a Wireless Ad Hoc Sensor Network over a Correlated Random Field?

New large deviations results that characterize the asymptotic information rates for general $d$-dimensional ($d$-D) stationary Gaussian fields are obtained. By applying the general results to sensor nodes on a two-dimensional (2-D) lattice, the asymptotic behavior of ad hoc sensor networks deployed over correlated random fields for statistical inference is investigated. Under a 2-D hidden Gauss-Markov random field model with symmetric first order conditional autoregression and the assumption of no in-network data fusion, the behavior of the total obtainable information [nats] and energy efficiency [nats/J] defined as the ratio of total gathered information to the required energy is obtained as the coverage area, node density and energy vary. When the sensor node density is fixed, the energy efficiency decreases to zero with rate $Θ({area}^{-1/2})$ and the per-node information under fixed per-node energy also diminishes to zero with rate $O(N_t^{-1/3})$ as the number $N_t$ of network nodes increases by increasing the coverage area. As the sensor spacing $d_n$ increases, the per-node information converges to its limit $D$ with rate $D-\sqrt{d_n}e^{-αd_n}$ for a given diffusion rate $α$. When the coverage area is fixed and the node density increases, the per-node information is inversely proportional to the node density. As the total energy $E_t$ consumed in the network increases, the total information obtainable from the network is given by $O(\log E_t)$ for the fixed node density and fixed coverage case and by $Θ(E_t^{2/3})$ for the fixed per-node sensing energy and fixed density and increasing coverage case.

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Noisy-interference Sum-rate Capacity of Parallel Gaussian Interference Channels

The sum-rate capacity of the parallel Gaussian interference channel is shown to be achieved by independent transmission across sub-channels and treating interference as noise in each sub-channel if the channel coefficients and power constraints satisfy a certain condition. The condition requires the interference to be weak, a situation commonly encountered in, e.g., digital subscriber line transmission. The optimal power allocation is characterized by using the concavity of sum-rate capacity as a function of the power constraints.

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Multiple Multicasts with the Help of a Relay

The problem of simultaneous multicasting of multiple messages with the help of a relay terminal is considered. In particular, a model is studied in which a relay station simultaneously assists two transmitters in multicasting their independent messages to two receivers. The relay may also have an independent message of its own to multicast. As a first step to address this general model, referred to as the compound multiple access channel with a relay (cMACr), the capacity region of the multiple access channel with a "cognitive" relay is characterized, including the cases of partial and rate-limited cognition. Then, achievable rate regions for the cMACr model are presented based on decode-and-forward (DF) and compress-and-forward (CF) relaying strategies. Moreover, an outer bound is derived for the special case, called the cMACr without cross-reception, in which each transmitter has a direct link to one of the receivers while the connection to the other receiver is enabled only through the relay terminal. The capacity region is characterized for a binary modulo additive cMACr without cross-reception, showing the optimality of binary linear block codes, thus highlighting the benefits of physical layer network coding and structured codes. Results are extended to the Gaussian channel model as well, providing achievable rate regions for DF and CF, as well as for a structured code design based on lattice codes. It is shown that the performance with lattice codes approaches the upper bound for increasing power, surpassing the rates achieved by the considered random coding-based techniques.

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Convergence and Tradeoff of Utility-Optimal CSMA

It has been recently suggested that in wireless networks, CSMA-based distributed MAC algorithms could achieve optimal utility without any message passing. We present the first proof of convergence of such adaptive CSMA algorithms towards an arbitrarily tight approximation of utility-optimizing schedule. We also briefly discuss the tradeoff between optimality at equilibrium and short-term fairness practically achieved by such algorithms.

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Opportunistic Communications in Fading Multiaccess Relay Channels

The problem of optimal resource allocation is studied for ergodic fading orthogonal multiaccess relay channels (MARCs) in which the users (sources) communicate with a destination with the aid of a half-duplex relay that transmits on a channel orthogonal to that used by the transmitting sources. Under the assumption that the instantaneous fading state information is available at all nodes, the maximum sum-rate and the optimal user and relay power allocations (policies) are developed for a decode-and-forward (DF) relay. With the observation that a DF relay results in two multiaccess channels, one at the relay and the other at the destination, a single known lemma on the sum-rate of two intersecting polymatroids is used to determine the DF sum-rate and the optimal user and relay policies. The lemma also enables a broad topological classification of fading MARCs into one of three types. The first type is the set of partially clustered MARCs where a user is clustered either with the relay or with the destination such that the users waterfill on their bottle-neck links to the distant receiver. The second type is the set of clustered MARCs where all users are either proximal to the relay or to the destination such that opportunistic multiuser scheduling to one of the receivers is optimal. The third type consists of arbitrarily clustered MARCs which are a combination of the first two types, and for this type it is shown that the optimal policies are opportunistic non-waterfilling solutions. The analysis is extended to develop the rate region of a K-user orthogonal half-duplex MARC. Finally, cutset outer bounds are used to show that DF achieves the capacity region for a class of clustered orthogonal half-duplex MARCs.

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Joint Source-Channel Coding at the Application Layer for Parallel Gaussian Sources

In this paper the multicasting of independent parallel Gaussian sources over a binary erasure broadcasted channel is considered. Multiresolution embedded quantizer and layered joint source-channel coding schemes are used in order to serve simultaneously several users at different channel capacities. The convex nature of the rate-distortion function, computed by means of reverse water-filling, allows us to solve relevant convex optimization problems corresponding to different performance criteria. Then, layered joint source-channel codes are constructed based on the concatenation of embedded scalar quantizers with binary rateless encoders.

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Robust Cognitive Beamforming With Partial Channel State Information

This paper considers a spectrum sharing based cognitive radio (CR) communication system, which consists of a secondary user (SU) having multiple transmit antennas and a single receive antenna and a primary user (PU) having a single receive antenna. The channel state information (CSI) on the link of the SU is assumed to be perfectly known at the SU transmitter (SU-Tx). However, due to loose cooperation between the SU and the PU, only partial CSI of the link between the SU-Tx and the PU is available at the SU-Tx. With the partial CSI and a prescribed transmit power constraint, our design objective is to determine the transmit signal covariance matrix that maximizes the rate of the SU while keeping the interference power to the PU below a threshold for all the possible channel realization within an uncertainty set. This problem, termed the robust cognitive beamforming problem, can be naturally formulated as a semi-infinite programming (SIP) problem with infinitely many constraints. This problem is first transformed into the second order cone programming (SOCP) problem and then solved via a standard interior point algorithm. Then, an analytical solution with much reduced complexity is developed from a geometric perspective. It is shown that both algorithms obtain the same optimal solution. Simulation examples are presented to validate the effectiveness of the proposed algorithms.

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MIMO Two-way Relay Channel: Diversity-Multiplexing Tradeoff Analysis

A multi-hop two-way relay channel is considered in which all the terminals are equipped with multiple antennas. Assuming independent quasi-static Rayleigh fading channels and channel state information available at the receivers, we characterize the optimal diversity-multiplexing gain tradeoff (DMT) curve for a full-duplex relay terminal. It is shown that the optimal DMT can be achieved by a compress-and-forward type relaying strategy in which the relay quantizes its received signal and transmits the corresponding channel codeword. It is noteworthy that, with this transmission protocol, the two transmissions in opposite directions can achieve their respective single user optimal DMT performances simultaneously, despite the interference they cause to each other. Motivated by the optimality of this scheme in the case of the two-way relay channel, a novel dynamic compress-and-forward (DCF) protocol is proposed for the one-way multi-hop MIMO relay channel for a half-duplex relay terminal, and this scheme is shown to achieve the optimal DMT performance.

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Secret Communication with Feedback

Secure communication with feedback is studied. An achievability scheme in which the backward channel is used to generate a shared secret key is proposed. The scenario of binary symmetric forward and backward channels is considered, and a combination of the proposed scheme and Maurer's coding scheme is shown to achieve improved secrecy rates. The scenario of a Gaussian channel with perfect output feedback is also analyzed and the Schalkwijk-Kailath coding scheme is shown to achieve the secrecy capacity for this channel.

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Interference Channels with Correlated Receiver Side Information

The problem of joint source-channel coding in transmitting independent sources over interference channels with correlated receiver side information is studied. When each receiver has side information correlated with its own desired source, it is shown that source-channel code separation is optimal. When each receiver has side information correlated with the interfering source, sufficient conditions for reliable transmission are provided based on a joint source-channel coding scheme using the superposition encoding and partial decoding idea of Han and Kobayashi. When the receiver side information is a deterministic function of the interfering source, source-channel code separation is again shown to be optimal. As a special case, for a class of Z-interference channels, when the side information of the receiver facing interference is a deterministic function of the interfering source, necessary and sufficient conditions for reliable transmission are provided in the form of single letter expressions. As a byproduct of these joint source-channel coding results, the capacity region of a class of Z-channels with degraded message sets is also provided.

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Interference Alignment for Secrecy

This paper studies the frequency/time selective $K$-user Gaussian interference channel with secrecy constraints. Two distinct models, namely the interference channel with confidential messages and the one with an external eavesdropper, are analyzed. The key difference between the two models is the lack of channel state information (CSI) about the external eavesdropper. Using interference alignment along with secrecy pre-coding, it is shown that each user can achieve non-zero secure Degrees of Freedom (DoF) for both cases. More precisely, the proposed coding scheme achieves $\frac{K-2}{2K-2}$ secure DoF {\em with probability one} per user in the confidential messages model. For the external eavesdropper scenario, on the other hand, it is shown that each user can achieve $\frac{K-2}{2K}$ secure DoF {\em in the ergodic setting}. Remarkably, these results establish the {\em positive impact} of interference on the secrecy capacity region of wireless networks.

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Secure Wireless Communications via Cooperation

The feasibility of physical-layer-based security approaches for wireless communications in the presence of one or more eavesdroppers is hampered by channel conditions. In this paper, cooperation is investigated as an approach to overcome this problem and improve the performance of secure communications. In particular, a decode-and-forward (DF) based cooperative protocol is considered, and the objective is to design the system for secrecy capacity maximization or transmit power minimization. System design for the DF-based cooperative protocol is first studied by assuming the availability of global channel state information (CSI). For the case of one eavesdropper, an iterative scheme is proposed to obtain the optimal solution for the problem of transmit power minimization. For the case of multiple eavesdroppers, the problem of secrecy capacity maximization or transmit power minimization is in general intractable. Suboptimal system design is proposed by adding an additional constraint, i.e., the complete nulling of signals at all eavesdroppers, which yields simple closed-form solutions for the aforementioned two problems. Then, the impact of imperfect CSI of eavesdroppers on system design is studied, in which the ergodic secrecy capacity is of interest.

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On the Capacity of MIMO Interference Channels

The capacity region of a multiple-input-multiple-output interference channel (MIMO IC) where the channel matrices are square and invertible is studied. The capacity region for strong interference is established where the definition of strong interference parallels that of scalar channels. Moreover, the sum-rate capacity for Z interference, noisy interference, and mixed interference is established. These results generalize known results for the scalar Gaussian IC.

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On Gaussian MIMO BC-MAC Duality With Multiple Transmit Covariance Constraints

Owing to the structure of the Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC), associated optimization problems such as capacity region computation and beamforming optimization are typically non-convex, and cannot be solved directly. One feasible approach to these problems is to transform them into their dual multiple access channel (MAC) problems, which are easier to deal with due to their convexity properties. The conventional BC-MAC duality is established via BC-MAC signal transformation, and has been successfully applied to solve beamforming optimization, signal-to-interference-plus-noise ratio (SINR) balancing, and capacity region computation. However, this conventional duality approach is applicable only to the case, in which the base station (BS) of the BC is subject to a single sum power constraint. An alternative approach is minimax duality, established by Yu in the framework of Lagrange duality, which can be applied to solve the per-antenna power constraint problem. This paper extends the conventional BC-MAC duality to the general linear constraint case, and thereby establishes a general BC-MAC duality. This new duality is applied to solve the capacity computation and beamforming optimization for the MIMO and multiple-input single-output (MISO) BC, respectively, with multiple linear constraints. Moreover, the relationship between this new general BC-MAC duality and minimax duality is also presented. It is shown that the general BC-MAC duality offers more flexibility in solving BC optimization problems relative to minimax duality. Numerical results are provided to illustrate the effectiveness of the proposed algorithms.

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Diversity-Multiplexing Tradeoffs in MIMO Relay Channels

A multi-hop relay channel with multiple antenna terminals in a quasi-static slow fading environment is considered. For both full-duplex and half-duplex relays the fundamental diversity-multiplexing tradeoff (DMT) is analyzed. It is shown that, while decode-and-forward (DF) relaying achieves the optimal DMT in the full-duplex relay scenario, the dynamic decode-and-forward (DDF) protocol is needed to achieve the optimal DMT if the relay is constrained to half-duplex operation. For the latter case, static protocols are considered as well, and the corresponding achievable DMT performance is characterized.

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Energy-Efficient Resource Allocation in Multiuser MIMO Systems: A Game-Theoretic Framework

This paper focuses on the cross-layer issue of resource allocation for energy efficiency in the uplink of a multiuser MIMO wireless communication system. Assuming that all of the transmitters and the uplink receiver are equipped with multiple antennas, the situation considered is that in which each terminal is allowed to vary its transmit power, beamforming vector, and uplink receiver in order to maximize its own utility, which is defined as the ratio of data throughput to transmit power; the case in which non-linear interference cancellation is used at the receiver is also investigated. Applying a game-theoretic formulation, several non-cooperative games for utility maximization are thus formulated, and their performance is compared in terms of achieved average utility, achieved average SINR and average transmit power at the Nash equilibrium. Numerical results show that the use of the proposed cross-layer resource allocation policies brings remarkable advantages to the network performance.

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