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49
Capacityachieving input covariance for singleuser multiantenna channels
 IEEE Trans. Wireless Commun
, 2006
"... Abstract — We characterize the capacityachieving input covariance for multiantenna channels known instantaneously at the receiver and in distribution at the transmitter. Our characterization, valid for arbitrary numbers of antennas, encompasses both the eigenvectors and the eigenvalues. The eigenv ..."
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Cited by 32 (11 self)
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Abstract — We characterize the capacityachieving input covariance for multiantenna channels known instantaneously at the receiver and in distribution at the transmitter. Our characterization, valid for arbitrary numbers of antennas, encompasses both the eigenvectors and the eigenvalues. The eigenvectors are found for zeromean channels with arbitrary fading profiles and a wide range of correlation and keyhole structures. For the eigenvalues, in turn, we present necessary and sufficient conditions as well as an iterative algorithm that exhibits remarkable properties: universal applicability, robustness and rapid convergence. In addition, we identify channel structures for which an isotropic input achieves capacity. Index Terms — Capacity, MIMO, input optimization, fading, antenna correlation, Ricean fading, keyhole channel.
Power Allocation Games for MIMO Multiple Access Channels with Coordination
, 2009
"... A game theoretic approach is used to derive the optimal decentralized power allocation (PA) in fast fading multiple access channels where the transmitters and receiver are equipped with multiple antennas. The players (the mobile terminals) are free to choose their PA in order to maximize their indiv ..."
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Cited by 21 (14 self)
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A game theoretic approach is used to derive the optimal decentralized power allocation (PA) in fast fading multiple access channels where the transmitters and receiver are equipped with multiple antennas. The players (the mobile terminals) are free to choose their PA in order to maximize their individual transmission rates (in particular they can ignore some specified centralized policies). A simple coordination mechanism between users is introduced. The nature and influence of this mechanism is studied in detail. The coordination signal indicates to the users the order in which the receiver applies successive interference cancellation and the frequency at which this order is used. Two different games are investigated: the users can either adapt their temporal PA to their decoding rank at the receiver or optimize their spatial PA between their transmit antennas. For both games a thorough analysis of the existence, uniqueness and sumrate efficiency of the network Nash equilibrium is conducted. Analytical and simulation results are provided to assess the gap between the decentralized network performance and its equivalent virtual multiple input multiple output system, which is shown to be zero in some cases and relatively small in general.
Discrete power control: Cooperative and noncooperative optimization
 in INFOCOM
, 2007
"... Abstract — We consider an uplink power control problem where each mobile wishes to maximize its throughput (which depends on the transmission powers of all mobiles) but has a constraint on the average power consumption. A finite number of power levels are available to each mobile. The decision of a ..."
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Cited by 15 (3 self)
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Abstract — We consider an uplink power control problem where each mobile wishes to maximize its throughput (which depends on the transmission powers of all mobiles) but has a constraint on the average power consumption. A finite number of power levels are available to each mobile. The decision of a mobile to select a particular power level may depend on its channel state. We consider two frameworks concerning the state information of the channels of other mobiles: (i) the case of full state information and (ii) the case of local state information. In each of the two frameworks, we consider both cooperative as well as noncooperative power control. We manage to characterize the structure of equilibria policies and, more generally, of bestresponse policies in the noncooperative case. We present an algorithm to compute equilibria policies in the case of two noncooperative players. Finally, we study the case where a malicious mobile, which also has average power constraints, tries to jam the communication of the other mobile. Our results are illustrated and validated through various numerical examples. I.
A game theoretic approach for cooperative mimo systems with cellular reuse of the relay slot
 in Proc. IEEE ICASSP
, 2004
"... An iterative game theory based algorithm is proposed to allocate the resources in cooperative schemes for the downlink. Both Amplify and Forward (AF) and Decode and Forward (DF) cooperative schemes are considered with cellular reuse of the relay slot. Multiple antennas can be used at the involved st ..."
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Cited by 12 (3 self)
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An iterative game theory based algorithm is proposed to allocate the resources in cooperative schemes for the downlink. Both Amplify and Forward (AF) and Decode and Forward (DF) cooperative schemes are considered with cellular reuse of the relay slot. Multiple antennas can be used at the involved stations. Using the algorithm proposed, the simultaneous relay powers are decided in a decentralized way using mean channel level measures and mean values of noise and interference power. The cell capacity gain for the cooperative schemes using the decentralized algorithm is evaluated by means of simulation both for the AF and DF approaches. 1.
Optimization of the MIMO compound capacity
 IEEE Transactions on Wireless Communications
, 2007
"... Abstract — In this paper, we consider the optimization of the compound capacity in a rank one Ricean multiple input multiple output channel using partial channel state information at the transmitter side. We model the channel as a deterministic matrix within a known ellipsoid, and address the compou ..."
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Cited by 11 (1 self)
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Abstract — In this paper, we consider the optimization of the compound capacity in a rank one Ricean multiple input multiple output channel using partial channel state information at the transmitter side. We model the channel as a deterministic matrix within a known ellipsoid, and address the compound capacity defined as the maximum worst case mutual information in the set. We find that the optimal transmit strategy is always beamforming, and can be found using a simple one dimensional search. Similar results are derived for the worst case sumrate of a multiple access channel with individual power constraints and a total power constraint. In this multiuser setting we assume equal array response at the receiver for all users. These results motivate the growing use of systems using simple beamforming transmit strategies. Index Terms — MIMO, compound capacity, beamforming. I.
Correlated anarchy in overlapping wireless networks
 IEEE Journal on Selected Areas in Communications
, 2008
"... Abstract—We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless accesspoints (possibly belonging to different standards) by introducing an iterated noncooperative game. Users start out completely uneducated and naïve but, by usi ..."
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Cited by 6 (0 self)
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Abstract—We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless accesspoints (possibly belonging to different standards) by introducing an iterated noncooperative game. Users start out completely uneducated and naïve but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g. spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the wellstudied minority game, generalizing its analysis to an arbitrary number of choices. Index Terms—Wireless networks, Nash equilibrium, correlated equilibrium, price of anarchy, evolutionary games, replicas
Dynamic Discrete Power Control in Cellular Networks
"... We consider an uplink power control problem where each mobile wishes to maximize its throughput (which depends on the transmission powers of all mobiles) but has a constraint on the average power consumption. A finite number of power levels are available to each mobile. The decision of a mobile to ..."
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Cited by 6 (3 self)
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We consider an uplink power control problem where each mobile wishes to maximize its throughput (which depends on the transmission powers of all mobiles) but has a constraint on the average power consumption. A finite number of power levels are available to each mobile. The decision of a mobile to select a particular power level may depend on its channel state. We consider two frameworks concerning the state information of the channels of other mobiles: (i) the case of full state information and (ii) the case of local state information. In each of the two frameworks, we consider both cooperative as well as noncooperative power control. We manage to characterize the structure of equilibria policies and, more generally, of bestresponse policies in the noncooperative case. We present an algorithm to compute equilibria policies in the case of two noncooperative players. Finally, we study the case where a malicious mobile, which also has average power constraints, tries to jam the communication of another mobile. Our results are illustrated and validated through various numerical examples. I
On the minimax robustness of the uniform transmission power strategy in MIMO systems
 IEEE Commun. Lett
, 2003
"... Abstract — In this letter, it is shown that the uniform power allocation across transmit antennas is optimal in the sense that this strategy will maximize the minimum average mutual information of a multipleinputmultipleoutput (MIMO) system across the class of any arbitrary correlated fading chan ..."
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Cited by 5 (0 self)
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Abstract — In this letter, it is shown that the uniform power allocation across transmit antennas is optimal in the sense that this strategy will maximize the minimum average mutual information of a multipleinputmultipleoutput (MIMO) system across the class of any arbitrary correlated fading channels, with constraints on the the total fixed transmit power (), total power of the fades at the transmitter side (), and total power of the fades at the receiver side (), if the channel state information (CSI) is perfectly known at the receiver side only. I.
Optimum transmit architecture of a MIMO system under modulus channel knowledge at the transmitter
 in Proc. IEEE Information Theory Workshop (ITW’04
, 2004
"... Abstract — In this paper, we study the ergodic capacity of a multiple input multiple output (MIMO) uncorrelated flat fading channel with perfect channel state information at the receiver and partial channel state information at the transmitter. We focus our attention on the case where the transmitte ..."
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Cited by 5 (3 self)
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Abstract — In this paper, we study the ergodic capacity of a multiple input multiple output (MIMO) uncorrelated flat fading channel with perfect channel state information at the receiver and partial channel state information at the transmitter. We focus our attention on the case where the transmitter is informed only with the modulus of the channel matrix coefficients. First, we prove that a simple power allocation strategy among transmitting antennas is the optimal scheme, in the sense that is a capacity achieving architecture. Next, for the particular case where only two antennas are used at each communication end, we derive closed form expressions for the ergodic capacity and the optimal power assigned to each antenna. I.