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47
Capacity Limits of MIMO Channels
 IEEE J. SELECT. AREAS COMMUN
, 2003
"... We provide an overview of the extensive recent results on the Shannon capacity of singleuser and multiuser multipleinput multipleoutput (MIMO) channels. Although enormous capacity gains have been predicted for such channels, these predictions are based on somewhat unrealistic assumptions about t ..."
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Cited by 222 (11 self)
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We provide an overview of the extensive recent results on the Shannon capacity of singleuser and multiuser multipleinput multipleoutput (MIMO) channels. Although enormous capacity gains have been predicted for such channels, these predictions are based on somewhat unrealistic assumptions about the underlying timevarying channel model and how well it can be tracked at the receiver, as well as at the transmitter. More realistic assumptions can dramatically impact the potential capacity gains of MIMO techniques. For timevarying MIMO channels there are multiple Shannon theoretic capacity definitions and, for each definition, different correlation models and channel information assumptions that we consider. We first provide a comprehensive summary of ergodic and capacity versus outage results for singleuser MIMO channels. These results indicate that the capacity gain obtained from multiple antennas heavily depends
Capacity and Optimal Resource Allocation for Fading Broadcast Channels: Part I: Ergodic Capacity
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On the duality of Gaussian multipleaccess and broadcast channels
 IEEE Trans. Inf. Theory
, 2004
"... Abstract—We define a duality between Gaussian multipleaccess channels (MACs) and Gaussian broadcast channels (BCs). The dual channels we consider have the same channel gains and the same noise power at all receivers. We show that the capacity region of the BC (both constant and fading) can be writt ..."
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Cited by 73 (13 self)
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Abstract—We define a duality between Gaussian multipleaccess channels (MACs) and Gaussian broadcast channels (BCs). The dual channels we consider have the same channel gains and the same noise power at all receivers. We show that the capacity region of the BC (both constant and fading) can be written in terms of the capacity region of the dual MAC, and vice versa. We can use this result to find the capacity region of the MAC if the capacity region of only the BC is known, and vice versa. For fading channels we show duality under ergodic capacity, but duality also holds for different capacity definitions for fading channels such as outage capacity and minimumrate capacity. Using duality, many results known for only one of the two channels can be extended to the dual channel as well. Index Terms—Broadcast channel (BC), channel capacity, duality, fading channels, multipleinput multipleoutput (MIMO) systems, multipleaccess channel (MAC). I.
Uniform Power Allocation in MIMO Channels: a GameTheoretic Approach
 IEEE Trans. Inf. Theory
, 2003
"... This publication has been included here just to facilitate downloads to those people asking for personal use copies. This material may be published at copyrighted journals or conference proceedings, so personal use of the download is required. In particular, publications from IEEE have to be downloa ..."
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Cited by 39 (4 self)
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This publication has been included here just to facilitate downloads to those people asking for personal use copies. This material may be published at copyrighted journals or conference proceedings, so personal use of the download is required. In particular, publications from IEEE have to be downloaded according to the following IEEE note: c○2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
SpaceTime Multiple Access: Linear Growth in the Sum Rate
 in Proc. 40th Annual Allerton Conf. Communications, Control and Computing
, 2002
"... It is known that some of the spectacular capacity gains of using multiple antennas on a pointtopoint rich scattering channel, namely linear growth with the number of antennas, can also be obtained in a multiuser environment. We give the constant of proportionality of linear growth in the sumcapa ..."
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Cited by 31 (7 self)
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It is known that some of the spectacular capacity gains of using multiple antennas on a pointtopoint rich scattering channel, namely linear growth with the number of antennas, can also be obtained in a multiuser environment. We give the constant of proportionality of linear growth in the sumcapacity when the number of users and antennas grow simultaneously, but with fewer users than antennas. We assume that the transmitter and receivers know the channel. Because of the linear growth in sumcapacity, we can accommodate more users simply by adding more antennas, without increasing total transmitted power or bandwidth or lowering the rate to existing users. We dub any scheme that can achieve linear growth in this fashion a spacetime multiple access scheme. Channelhardening arguments show that a "channelinversion" technique used in pointtopoint multipleantenna links achieves a large fraction of this linear growth in a multiuser environment without excessive transmitter power. Thus, multipleantennas offer a tremendous advantage in designing scheduling, networking, and multipleaccess protocols in rich scattering environments.
SpaceTime Autocoding
 IEEE Trans. Inform. Theory
, 1999
"... Prior treatments of spacetime communications in Rayleigh flat fading generally assume that channel coding covers either one fading intervalin which case there is a nonzero "outage capacity"or multiple fading intervalsin which case there is a nonzero Shannon capacity. However, we establish ..."
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Cited by 30 (3 self)
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Prior treatments of spacetime communications in Rayleigh flat fading generally assume that channel coding covers either one fading intervalin which case there is a nonzero "outage capacity"or multiple fading intervalsin which case there is a nonzero Shannon capacity. However, we establish conditions under which channel codes span only one fading interval and yet are arbitrarily reliable. In short, spacetime signals are their own channel codes. We call this phenomenon spacetime autocoding, and the accompanying capacity the spacetime autocapacity. Let an Mtransmitterantenna, Nreceiverantenna Rayleigh flat fading channel be characterized by an M \Theta N matrix of independent propagation coefficients, distributed as zeromean, unitvariance complex Gaussian random variables. This propagation matrix is unknown to the transmitter, it remains constant during a T symbol coherence interval, and there is a fixed total transmit power. Let the coherence interval and number of ...
Control of Mobile Communications with Time Varying Channels in Heavy Traffic
 IEEE Trans. Automat. Control
, 2001
"... Consider a system with a xed number (K) of remote units and a single base transmitter with time varying (and perhaps correlated) connecting channels. Data to be transmitted to the remote units arrives according to some random process and is queued according to its destination. The forward link is tr ..."
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Cited by 16 (1 self)
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Consider a system with a xed number (K) of remote units and a single base transmitter with time varying (and perhaps correlated) connecting channels. Data to be transmitted to the remote units arrives according to some random process and is queued according to its destination. The forward link is treated. Power is to be allocated to the K channels in a queue and channel state dependent way to minimize some cost criterion. The modeling and control problem can be quite difficult. The channel time variations (fading) are fast and the bandwidth and data arrival rates are high. Owing to the complexity of the physical problem and the high speed of both the fading and arrival and service rates, an asymptotic or averaging method is promising. A heavy traffic analysis is done. By heavy traffic, we mean that on the average there is little server idle time and little spare power over the "average" requirements. Heavy traffic analysis has been very helpful in simplifying analysis of both controlled and uncontrolled problems in queueing and communications networks. It tends to eliminate unessential detail and focus on the fundamental issues of scaling and parametric dependencies. To illustrate the scope of the method, a variety of models are considered. The basic model assumes that the channel state is known or can be well estimated and that given the channel state there is a well defined rate of transmission per unit power. Then convergence of the controlled scaled queue lengths is shown. The scaling is different from the usual in heavy traffic work, and the limit Wiener process depends only on the channel state process and not on the...
On peak versus average interference power constraints for protecting primary users in cognitive radio networks
 IEEE Trans. Wireless Commun
, 2009
"... This paper considers spectrum sharing for wireless communication between a cognitive radio (CR) link and a primary radio (PR) link. It is assumed that the CR protects the PR transmission by applying the socalled interferencetemperature constraint, whereby the CR is allowed to transmit regardless o ..."
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Cited by 13 (6 self)
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This paper considers spectrum sharing for wireless communication between a cognitive radio (CR) link and a primary radio (PR) link. It is assumed that the CR protects the PR transmission by applying the socalled interferencetemperature constraint, whereby the CR is allowed to transmit regardless of the PR’s on/off status provided that the resultant interference power level at the PR receiver is kept below some predefined threshold. For the fading PR and CR channels, the interferencepower constraint at the PR receiver is usually one of the following two types: One is to regulate the average interference power (AIP) over all the fading states, while the other is to limit the peak interference power (PIP) at each fading state. From the CR’s perspective, given the same average and peak power threshold, the AIP constraint is more favorable than the PIP counterpart because of its more flexibility for dynamically allocating transmit powers over the fading states. On the contrary, from the perspective of protecting the PR, the more restrictive PIP constraint appears at a first glance to be a better option than the AIP. Some surprisingly, this paper shows that in terms of various forms of capacity limits achievable for the PR fading channel, e.g., the ergodic and outage capacities, the AIP constraint is also superior over the PIP. This result is based upon an interesting interference diversity phenomenon, i.e., randomized interference powers over the fading states in the AIP case are more advantageous over deterministic ones in the PIP case for minimizing the resultant PR capacity losses. Therefore, the AIP constraint results in larger fading channel capacities than the PIP for both the CR and PR transmissions. Index Terms Cognitive radio, spectrum sharing, interference temperature, interference diversity, fading channel capacity.
On ergodic sum capacity of fading cognitive multipleaccess and broadcast channels
 IEEE Trans. Inf. Theory. Available [Online
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On the Duality of MultipleAccess and Broadcast Channels
 Channels”, Allerton Conference on Commun., Control, and Computing
, 2001
"... We show that the Gaussian multipleaccess channel and the Gaussian broadcast channel are fundamentally related and are essentially duals of each other. The dual channels we consider have the same channel gains and the same noise power at all receivers. We show that the capacity region of a broadc ..."
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Cited by 9 (6 self)
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We show that the Gaussian multipleaccess channel and the Gaussian broadcast channel are fundamentally related and are essentially duals of each other. The dual channels we consider have the same channel gains and the same noise power at all receivers. We show that the capacity region of a broadcast channel (both constant and fading) can be written in terms of the capacity region of the dual multipleaccess channel, and vice versa. We can use this result to find the capacity region of the MAC if the capacity region of only the broadcast channel is known, and vice versa. For fading channels we show duality under ergodic capacity, but duality also holds for different notions of Shannon capacity for fading channels such as outage capacity and minimum rate capacity. Using duality, many results known for only one of the two channels are now known for the dual channel as well.