294 research outputs found
Fundamental Limits in MIMO Broadcast Channels
This paper studies the fundamental limits of MIMO broadcast channels from a high level, determining the sum-rate capacity of the system as a function of system paramaters, such as the number of transmit antennas, the number of users, the number of receive antennas, and the total transmit power. The crucial role of channel state information at the transmitter is emphasized, as well as the emergence of opportunistic transmission schemes. The effects of channel estimation errors, training, and spatial correlation are studied, as well as issues related to fairness, delay and differentiated rate scheduling
Fundamental Limits in Correlated Fading MIMO Broadcast Channels: Benefits of Transmit Correlation Diversity
We investigate asymptotic capacity limits of the Gaussian MIMO broadcast
channel (BC) with spatially correlated fading to understand when and how much
transmit correlation helps the capacity. By imposing a structure on channel
covariances (equivalently, transmit correlations at the transmitter side) of
users, also referred to as \emph{transmit correlation diversity}, the impact of
transmit correlation on the power gain of MIMO BCs is characterized in several
regimes of system parameters, with a particular interest in the large-scale
array (or massive MIMO) regime. Taking the cost for downlink training into
account, we provide asymptotic capacity bounds of multiuser MIMO downlink
systems to see how transmit correlation diversity affects the system
multiplexing gain. We make use of the notion of joint spatial division and
multiplexing (JSDM) to derive the capacity bounds. It is advocated in this
paper that transmit correlation diversity may be of use to significantly
increase multiplexing gain as well as power gain in multiuser MIMO systems. In
particular, the new type of diversity in wireless communications is shown to
improve the system multiplexing gain up to by a factor of the number of degrees
of such diversity. Finally, performance limits of conventional large-scale MIMO
systems not exploiting transmit correlation are also characterized.Comment: 29 pages, 8 figure
Multiuser Diversity for Secrecy Communications Using Opportunistic Jammer Selection -- Secure DoF and Jammer Scaling Law
In this paper, we propose opportunistic jammer selection in a wireless
security system for increasing the secure degrees of freedom (DoF) between a
transmitter and a legitimate receiver (say, Alice and Bob). There is a jammer
group consisting of jammers among which Bob selects jammers. The
selected jammers transmit independent and identically distributed Gaussian
signals to hinder the eavesdropper (Eve). Since the channels of Bob and Eve are
independent, we can select the jammers whose jamming channels are aligned at
Bob, but not at Eve. As a result, Eve cannot obtain any DoF unless it has more
than receive antennas, where is the number of jammer's transmit
antenna each, and hence can be regarded as defensible dimensions against
Eve. For the jamming signal alignment at Bob, we propose two opportunistic
jammer selection schemes and find the scaling law of the required number of
jammers for target secure DoF by a geometrical interpretation of the received
signals.Comment: Accepted with minor revisions, IEEE Trans. on Signal Processin
How Much Multiuser Diversity is Required for Energy Limited Multiuser Systems?
Multiuser diversity (MUDiv) is one of the central concepts in multiuser (MU)
systems. In particular, MUDiv allows for scheduling among users in order to
eliminate the negative effects of unfavorable channel fading conditions of some
users on the system performance. Scheduling, however, consumes energy (e.g.,
for making users' channel state information available to the scheduler). This
extra usage of energy, which could potentially be used for data transmission,
can be very wasteful, especially if the number of users is large. In this
paper, we answer the question of how much MUDiv is required for energy limited
MU systems. Focusing on uplink MU wireless systems, we develop MU scheduling
algorithms which aim at maximizing the MUDiv gain. Toward this end, we
introduce a new realistic energy model which accounts for scheduling energy and
describes the distribution of the total energy between scheduling and data
transmission stages. Using the fact that such energy distribution can be
controlled by varying the number of active users, we optimize this number by
either (i) minimizing the overall system bit error rate (BER) for a fixed total
energy of all users in the system or (ii) minimizing the total energy of all
users for fixed BER requirements. We find that for a fixed number of available
users, the achievable MUDiv gain can be improved by activating only a subset of
users. Using asymptotic analysis and numerical simulations, we show that our
approach benefits from MUDiv gains higher than that achievable by generic
greedy access algorithm, which is the optimal scheduling method for energy
unlimited systems.Comment: 28 pages, 9 figures, submitted to IEEE Trans. Signal Processing in
Oct. 200
Spectrum Sharing in Wireless Networks via QoS-Aware Secondary Multicast Beamforming
Secondary spectrum usage has the potential to considerably increase spectrum utilization. In this paper, quality-of-service (QoS)-aware spectrum underlay of a secondary multicast network is considered. A multiantenna secondary access point (AP) is used for multicast (common information) transmission to a number of secondary single-antenna receivers. The idea is that beamforming can be used to steer power towards the secondary receivers while limiting sidelobes that cause interference to primary receivers. Various optimal formulations of beamforming are proposed, motivated by different ldquocohabitationrdquo scenarios, including robust designs that are applicable with inaccurate or limited channel state information at the secondary AP. These formulations are NP-hard computational problems; yet it is shown how convex approximation-based multicast beamforming tools (originally developed without regard to primary interference constraints) can be adapted to work in a spectrum underlay context. Extensive simulation results demonstrate the effectiveness of the proposed approaches and provide insights on the tradeoffs between different design criteria
Interference Alignment for Cognitive Radio Communications and Networks: A Survey
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe
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