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ABSTRACT: Wireless systems comprised of rechargeable nodes have a significantly prolonged lifetime and are sustainable. A distinct characteristic of these systems is the fact that the nodes can harvest energy throughout the duration in which communication takes place. As such, transmission policies of the nodes need to adapt to these harvested energy arrivals. In this paper, we consider optimization of the transmission policy of an energy harvesting transmitter which has a limited battery capacity, communicating in a wireless fading channel. In particular, we identify the optimal offline transmission policies that maximize the number of bits delivered by a deadline, and minimize the transmission completion time of the communication session. We introduce a directional water-filling algorithm which provides a simple and concise interpretation of the necessary optimality conditions as well as energy storage capacity and causality. We solve the throughput maximization problem for the fading channel using the directional water-filling algorithm, which simultaneously adapts to the energy harvested as well as the channel variations in time. We then solve the transmission completion time minimization problem by utilizing its equivalence to its throughput maximization counterpart.
INFOCOM, 2011 Proceedings IEEE; 05/2011
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ABSTRACT: In this paper, we consider a single-user communication system, where an energy harvesting transmitter communicates with a receiver over a fading wireless channel. We design adaptive transmission policies that adapt to the random energy arrivals at the transmitter and random fluctuations in the channel, in order to maximize the average number of bits transmitted by a finite deadline T. We solve for the optimum transmission scheme using stochastic dynamic programming. This optimal solution does not admit a closed form expression and is computationally expensive. We then propose several suboptimal event based adaptive transmission policies that react to the changes in energy arrivals and fading states. We provide extensive simulation results that compare the performances of the optimal and proposed simpler solutions.
Information Sciences and Systems (CISS), 2011 45th Annual Conference on; 04/2011
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ABSTRACT: In the distributed coding of correlated sources, the problem of characterizing the joint probability distribution of a pair of random variables satisfying an n-letter Markov chain arises. The exact solution of this problem is intractable. In this paper, we seek a single-letter necessary condition for this n-letter Markov chain. To this end, we propose a new data processing inequality on a new measure of correlation through a spectral method. Based on this new data processing inequality, we provide a single-letter necessary condition for the required joint probability distribution. We apply our results to two specific examples involving the distributed coding of correlated sources: multiple-access channel with correlated sources and multiterminal rate-distortion region, and propose new necessary conditions for these two problems.
IEEE Transactions on Information Theory 02/2011; · 3.01 Impact Factor
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ABSTRACT: Multiple antenna systems are known to provide very large data rates, when the perfect channel state information (CSI) is available at the receiver. However, this requires the receiver to perform a noise-free, multi-dimensional channel estimation, without using communication resources. In practice, any channel estimation is noisy and uses system resources. We shall examine the trade-off between improving channel estimation and increasing the achievable data rate. We consider transmit side correlated multi-input multi-output (MIMO) channels with block fading, where each block is divided into training and data transmission phases. The receiver has a noisy CSI that it obtains through a channel estimation process, while the transmitter has partial CSI in the form of covariance feedback. In Part I of this two-part paper, we consider the single-user case, and optimize the achievable rate jointly over parameters associated with the training phase and data transmission phase. In particular, we first choose the training signal to minimize the channel estimation error, and then, develop an iterative algorithm to solve for the optimum system resources such as time, power and spatial dimensions. Specifically, the algorithm finds the optimum training duration, the optimum allocation of power between training and data transmission phases, the optimum allocation of power over the antennas during the data transmission phase.
IEEE Transactions on Wireless Communications 03/2010; · 2.59 Impact Factor
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ABSTRACT: This is the second part of a two-part paper on the joint channel estimation and resource allocation problem in MIMO systems with noisy channel estimation at the receiver side and partial CSI, in the form of covariance feedback, available at the transmitter side.We consider transmit-side correlated MIMO channels with block fading, where each block is divided into training and data transmission phases. In this paper, we extend the single-user results of Part I to the multiple access channel. For the data transmission phase, we propose an iterative algorithm to solve for the optimum system resources such as time, power and spatial dimensions. This algorithm updates the parameters of the users in a round-robin fashion. In particular, the algorithm updates the training and data transmission parameters of a user, when those of the rest of the users are fixed, in a way to maximize the achievable sum-rate in a multiple access channel; and iterates over users in a round-robin fashion. Finally, we provide a detailed numerical analysis to support the analytical results of both parts of this two-part paper.
IEEE Transactions on Wireless Communications 03/2010; · 2.59 Impact Factor
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ABSTRACT: We investigate the behavior of two users and one jammer in an additive white Gaussian noise (AWGN) channel with and without fading when they participate in a noncooperative zero-sum game, with the channel's input/output mutual information as the objective function. We assume that the jammer can eavesdrop on the channel and can use the information obtained to perform correlated jamming. We also differentiate between the availability of perfect and noisy information about the user signals at the jammer. Under various assumptions on the channel characteristics, and the extent of information available at the users and the jammer, we show the existence, or otherwise nonexistence of a simultaneously optimal set of strategies for the users and the jammer, and characterize those strategies whenever they exist.
IEEE Transactions on Information Theory 11/2009; · 3.01 Impact Factor
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ABSTRACT: We find the secrecy capacity of the 2-2-1 Gaussian MIMO wiretap channel, which consists of a transmitter and a receiver with two antennas each, and an eavesdropper with a single antenna. We determine the secrecy capacity of this channel by proposing an achievable scheme and then developing a tight upper bound that meets the proposed achievable secrecy rate. We show that, for this channel, Gaussian signalling in the form of beam-forming is optimal, and no pre-processing of information is necessary.
IEEE Transactions on Information Theory 10/2009; · 3.01 Impact Factor
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ABSTRACT: We obtain a dependence balance based outer bound on the capacity region of the two-user multiple access channel with generalized feedback (MAC-GF). We investigate a Gaussian MAC with user-cooperation (MAC-UC), where each transmitter receives an additive white Gaussian noise corrupted version of the channel input of the other transmitter. For all non-zero values of cooperation noise variances, our outer bound strictly improves upon the cut-set outer bound. Moreover, as the variances of the cooperation noises become large, our outer bound collapses to the capacity region of the Gaussian MAC without cooperation.
Information Theory, 2009. ISIT 2009. IEEE International Symposium on; 08/2009
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ABSTRACT: We consider the sum capacity of a multi-input multi-output (MIMO) multiple access channel (MAC) where the receiver has the perfect channel state information (CSI), while the transmitters have either no or partial CSI. When the transmitters have partial CSI, it is in the form of either the covariance matrix of the channel or the mean matrix of the channel. For the covariance feedback case, we mainly consider physical models that result in single-sided correlation structures. For the mean feedback case, we consider physical models that result in in-phase received signals. Under these assumptions, we analyze the MIMO-MAC from three different viewpoints. First, we consider a finite-sized system. We show that the optimum transmit directions of each user are the eigenvectors of its own channel covariance and mean feedback matrices, in the covariance and mean feedback models, respectively. Also, we find the conditions under which beamforming is optimal for all users. Second, in the covariance feedback case, we prove that the region where beamforming is optimal for all users gets larger with the addition of new users into the system. In the mean feedback case, we show through simulations that this is not necessarily true. Third, we consider the asymptotic case where the number of users is large. We show that in both no and partial CSI cases, beamforming is asymptotically optimal. In particular, in the case of no CSI, we show that a simple form of beamforming, which may be characterized as an arbitrary antenna selection scheme, achieves the sum capacity. In the case of partial CSI, we show that beamforming in the direction of the strongest eigenvector of the channel feedback matrix achieves the sum capacity. Finally, we generalize our covariance feedback results to double-sided correlation structures in the Appendix.
IEEE Transactions on Communications 05/2009; · 1.68 Impact Factor
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ABSTRACT: We consider correlated MIMO multiple access channels with block fading, where each block is divided into training and data transmission phases. We find the channel estimation and data transmission parameters that jointly optimize the achievable data rate of the system. Our results for the training phase are particularly interesting, where we show that the optimum training signals of the users should be non-overlapping in time. For the data transmission phase, we propose an iterative algorithm that updates the parameters of the users in a round-robin fashion. In particular, the algorithm updates the training and data transmission parameters of a user, when those of the rest of the users are fixed, in a way to maximize the achievable sum-rate in a multiple access channel; and iterates over users in a round-robin fashion.
Global Telecommunications Conference, 2008. IEEE GLOBECOM 2008. IEEE; 01/2009
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ABSTRACT: We provide a single-letter characterization for the capacity region of a class of discrete degraded interference channels (DDICs). The class of DDICs considered includes the DADIC studied by Benzel in 1979. We show that for the class of DDICs studied, encoder cooperation does not enlarge the capacity region, and therefore, the capacity region of the class of DDICs is the same as the capacity region of the corresponding degraded broadcast channel.
IEEE Transactions on Information Theory 10/2008; · 3.01 Impact Factor
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ABSTRACT: Cognitive radios have the ability to sense their RF environment and adapt their transmission parameters to perform optimally in any situation. Part of this involves selecting the best modulation type for a particular channel. In this paper we consider a variable-rate, variable-power, adaptive, m-ary quadrature amplitude modulation (M-QAM) scheme in a single-user communication scenario. The channel between the transmitter and receiver is assumed to be a Rayleigh block-fading channel. Each block is divided into training and data phases. During the training phase, the receiver estimates the channel and feeds the estimate back to the transmitter. During the data phase, the transmitter sends its message by adapting the size of the M- QAM constellation. We first find a closed-form expression that relates the bit error rate (BER) to the constellation size of the M-QAM, and therefore to the data rate of our system. Then, for a given target BER, we maximize the data rate over the training parameters, which are the training signal, the training duration, and the training power. When these optimum parameters are used in a MATLAB implementation, we find that the target BER is matched to within an order of magnitude, and the resulting data rate is close to the theoretical limit.
Communications, 2008. ICC '08. IEEE International Conference on; 06/2008
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ABSTRACT: We investigate the effects of user cooperation on the secrecy of multiple access channels with generalized feedback (MAC-GF). We show that cooperation can increase the achievable secrecy region. We propose achievable schemes which use compress-and-forward (CAF) based transmission strategies. CAF based strategies allow users to increase their rates up to levels which are not decodable by the cooperating partners, consequently improving the secrecy of the users. We also provide outer bounds on the achievable equivocation rates. The outer bounds we derive depend only on the channel inputs and outputs, and hence, are easily computable. Finally, we specialize our results to a Gaussian MAC-GF, and present numerical results which demonstrate the beneficial effects of cooperation on secrecy.
Information Sciences and Systems, 2008. CISS 2008. 42nd Annual Conference on; 04/2008
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ABSTRACT: We consider a single-user correlated MIMO channel with block fading, where each block is divided into training and data transmission phases. The receiver has a noisy CSI that it obtains through a channel estimation process, while the transmitter has partial CSI in the form of covariance feedback. We optimize the achievable rate jointly over the parameters of the training and data transmission phases. In particular, we first choose the training signal to minimize the channel estimation error, and then, develop an iterative algorithm to solve for the optimum training duration, the optimum allocation of power between training and data transmission phases, and the optimum allocation of power over the antennas during the data transmission phase.
Information Sciences and Systems, 2008. CISS 2008. 42nd Annual Conference on; 04/2008
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ABSTRACT: We find the secrecy capacity of the 2-2-1 Gaussian MIMO wire-tap channel, which consists of a transmitter and a receiver with two antennas each, and an eavesdropper with a single antenna. We determine the secrecy capacity of this channel by proposing an achievable scheme and then developing a tight upper bound that meets the proposed achievable secrecy rate. We show that, for this channel, Gaussian signalling in the form of beam-forming is optimal, and no pre-processing of information is necessary.
Communications, Control and Signal Processing, 2008. ISCCSP 2008. 3rd International Symposium on; 04/2008
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ABSTRACT: We investigate the optimal performance of dense sensor networks by studying the joint source-channel coding problem. There are N uniformly spaced sensor nodes sampling noiselessly a one-dimensional spatial random process over an interval [0, U<sub>0</sub>]. The overall goal of the sensor network is for the sensor nodes to code and transmit the measurement samples to a collector node over a cooperative multiple-access channel with noisy feedback, and for the collector node to reconstruct the entire random process with minimum expected distortion. We provide separation-based lower and upper bounds for the minimum achievable expected distortion when the underlying random process is Gaussian. When the Gaussian random process satisfies some general conditions, such as the eigenvalues of its Karhunen-Loeve expansion decrease roughly inverse polynomially in order x, i.e., the kth eigenvalue is roughly k<sup>-x</sup>, we evaluate the lower and upper bounds explicitly, and show that they are of the same order for a wide range of power constraints. Thus, for these random processes, under these power constraints, we show that the minimum achievable expected distortion decreases as (log NP(N)<sup>1-x</sup>, where P(N) is the sum power constraint on the sensor nodes. Further, we show that the achievability scheme that achieves the lower bound on the distortion is a separation-based scheme that is composed of multiterminal rate-distortion coding and amplify-and-forward channel coding. Therefore, we conclude that separation is order-optimal for the dense Gaussian sensor network scenario under consideration, when the underlying random process satisfies some general conditions.
IEEE Transactions on Information Theory 11/2007; · 3.01 Impact Factor
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ABSTRACT: In this paper, we propose a new coding scheme for the general relay channel. This coding scheme is in the form of a block Markov code. The transmitter uses a superposition Markov code. The relay compresses the received signal and maps the compressed version of the received signal into a codeword conditioned on the codeword of the previous block. The receiver performs joint decoding after it has received all of the B blocks. We show that this coding scheme can be viewed as a generalization of the well-known compress-and-forward (CAF) scheme proposed by cover and El Gamal. Our coding scheme provides options for preserving the correlation between the channel inputs of the transmitter and the relay, which is not possible in the CAF scheme. Thus, our proposed scheme may potentially yield a larger achievable rate than the CAF scheme.
Information Theory Workshop, 2007. ITW '07. IEEE; 10/2007
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ABSTRACT: We consider both the single-user and the multi-user power allocation problems in MIMO systems, where the receiver side has the perfect channel state information (CSI), and the transmitter side has partial CSI, which is in the form of covariance feedback. In a single-user MIMO system, we consider an iterative algorithm that solves for the eigenvalues of the optimum transmit covariance matrix that maximizes the rate. The algorithm is based on enforcing the Karush-Kuhn-Tucker (KKT) optimality conditions of the optimization problem at each iteration. We prove that this algorithm converges to the unique global optimum power allocation when initiated at an arbitrary point. We, then, consider the multi-user generalization of the problem, which is to find the eigenvalues of the optimum transmit covariance matrices of all users that maximize the sum rate of the MIMO multiple access channel (MIMO-MAC). For this problem, we propose an algorithm that finds the unique optimum power allocation policies of all users. At a given iteration, the multi-user algorithm updates the power allocation of one user, given the power allocations of the rest of the users, and iterates over all users in a round-robin fashion. Finally, we make several suggestions that significantly improve the convergence rate of the proposed algorithms.
IEEE Journal on Selected Areas in Communications 10/2007; · 3.41 Impact Factor
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ABSTRACT: For a fading Gaussian multiple access channel with user cooperation, we obtain the power allocation policies that maximize the average rates achievable by block Markov superposition coding, subject to average power constraints. The optimal policies result in a coding scheme that is simpler than the one for a general multiple access channel with generalized feedback. This simpler coding scheme also leads to the possibility of formulating an otherwise non-concave optimization problem as a concave one. Using the perfect channel state information available at the transmitters to adapt the powers, we demonstrate gains over the achievable rates for existing cooperative systems.
IEEE Transactions on Wireless Communications 09/2007; · 2.59 Impact Factor
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ABSTRACT: We characterize the optimum power control policies that achieve arbitrary rate tuples on the boundary of the capacity region of a power controlled, code division multiple access (CDMA) system in a fading channel with perfect channel state information (CSI). We propose a "generalized" waterfilling approach, and provide an iterative algorithm that solves for the optimum power allocation policy, for a given arbitrary rate tuple on the boundary of the capacity region. We then investigate the effects of limited feedback on the capacity region, and demonstrate that a good power control policy may require only a very low rate feedback
IEEE Transactions on Wireless Communications 12/2006; · 2.59 Impact Factor
