3,062 research outputs found
On Cooperative Multiple Access Channels with Delayed CSI at Transmitters
We consider a cooperative two-user multiaccess channel in which the
transmission is controlled by a random state. Both encoders transmit a common
message and, one of the encoders also transmits an individual message. We study
the capacity region of this communication model for different degrees of
availability of the states at the encoders, causally or strictly causally. In
the case in which the states are revealed causally to both encoders but not to
the decoder we find an explicit characterization of the capacity region in the
discrete memoryless case. In the case in which the states are revealed only
strictly causally to both encoders, we establish inner and outer bounds on the
capacity region. The outer bound is non-trivial, and has a relatively simple
form. It has the advantage of incorporating only one auxiliary random variable.
We then introduce a class of cooperative multiaccess channels with states known
strictly causally at both encoders for which the inner and outer bounds agree;
and so we characterize the capacity region for this class. In this class of
channels, the state can be obtained as a deterministic function of the channel
inputs and output. We also study the model in which the states are revealed,
strictly causally, in an asymmetric manner, to only one encoder. Throughout the
paper, we discuss a number of examples; and compute the capacity region of some
of these examples. The results shed more light on the utility of delayed
channel state information for increasing the capacity region of state-dependent
cooperative multiaccess channels; and tie with recent progress in this
framework.Comment: 54 pages. To appear in IEEE Transactions on Information Theory. arXiv
admin note: substantial text overlap with arXiv:1201.327
Adaptive Bit Partitioning for Multicell Intercell Interference Nulling with Delayed Limited Feedback
Base station cooperation can exploit knowledge of the users' channel state
information (CSI) at the transmitters to manage co-channel interference. Users
have to feedback CSI of the desired and interfering channels using
finite-bandwidth backhaul links. Existing codebook designs for single-cell
limited feedback can be used for multicell cooperation by partitioning the
available feedback resources between the multiple channels. In this paper, a
new feedback-bit allocation strategy is proposed, as a function of the delays
in the communication links and received signal strengths in the downlink.
Channel temporal correlation is modeled as a function of delay using the
Gauss-Markov model. Closed-form expressions for bit partitions are derived to
allocate more bits to quantize the stronger channels with smaller delays and
fewer bits to weaker channels with larger delays, assuming random vector
quantization. Cellular network simulations are used to show that the proposed
algorithm yields higher sum-rates than an equal-bit allocation technique.Comment: Submitted to IEEE Transactions on Signal Processing, July 201
Secure Degrees of Freedom of MIMO X-Channels with Output Feedback and Delayed CSIT
We investigate the problem of secure transmission over a two-user multi-input
multi-output (MIMO) X-channel in which channel state information is provided
with one-unit delay to both transmitters (CSIT), and each receiver feeds back
its channel output to a different transmitter. We refer to this model as MIMO
X-channel with asymmetric output feedback and delayed CSIT. The transmitters
are equipped with M-antennas each, and the receivers are equipped with
N-antennas each. For this model, accounting for both messages at each receiver,
we characterize the optimal sum secure degrees of freedom (SDoF) region. We
show that, in presence of asymmetric output feedback and delayed CSIT, the sum
SDoF region of the MIMO X-channel is same as the SDoF region of a two-user MIMO
BC with 2M-antennas at the transmitter, N-antennas at each receiver and delayed
CSIT. This result shows that, upon availability of asymmetric output feedback
and delayed CSIT, there is no performance loss in terms of sum SDoF due to the
distributed nature of the transmitters. Next, we show that this result also
holds if only output feedback is conveyed to the transmitters, but in a
symmetric manner, i.e., each receiver feeds back its output to both
transmitters and no CSIT. We also study the case in which only asymmetric
output feedback is provided to the transmitters, i.e., without CSIT, and derive
a lower bound on the sum SDoF for this model. Furthermore, we specialize our
results to the case in which there are no security constraints. In particular,
similar to the setting with security constraints, we show that the optimal sum
DoF region of the (M,M,N,N)--MIMO X-channel with asymmetric output feedback and
delayed CSIT is same as the DoF region of a two-user MIMO BC with 2M-antennas
at the transmitter, N-antennas at each receiver, and delayed CSIT. We
illustrate our results with some numerical examples.Comment: To Appear in IEEE Transactions on Information Forensics and Securit
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
Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks
Soaring capacity and coverage demands dictate that future cellular networks
need to soon migrate towards ultra-dense networks. However, network
densification comes with a host of challenges that include compromised energy
efficiency, complex interference management, cumbersome mobility management,
burdensome signaling overheads and higher backhaul costs. Interestingly, most
of the problems, that beleaguer network densification, stem from legacy
networks' one common feature i.e., tight coupling between the control and data
planes regardless of their degree of heterogeneity and cell density.
Consequently, in wake of 5G, control and data planes separation architecture
(SARC) has recently been conceived as a promising paradigm that has potential
to address most of aforementioned challenges. In this article, we review
various proposals that have been presented in literature so far to enable SARC.
More specifically, we analyze how and to what degree various SARC proposals
address the four main challenges in network densification namely: energy
efficiency, system level capacity maximization, interference management and
mobility management. We then focus on two salient features of future cellular
networks that have not yet been adapted in legacy networks at wide scale and
thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and
device-to-device (D2D) communications. After providing necessary background on
CoMP and D2D, we analyze how SARC can particularly act as a major enabler for
CoMP and D2D in context of 5G. This article thus serves as both a tutorial as
well as an up to date survey on SARC, CoMP and D2D. Most importantly, the
article provides an extensive outlook of challenges and opportunities that lie
at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201
Non-cooperative Feedback Rate Control Game for Channel State Information in Wireless Networks
It has been well recognized that channel state information (CSI) feedback is
of great importance for dowlink transmissions of closed-loop wireless networks.
However, the existing work typically researched the CSI feedback problem for
each individual mobile station (MS), and thus, cannot efficiently model the
interactions among self-interested mobile users in the network level. To this
end, in this paper, we propose an alternative approach to investigate the CSI
feedback rate control problem in the analytical setting of a game theoretic
framework, in which a multiple-antenna base station (BS) communicates with a
number of co-channel MSs through linear precoder. Specifically, we first
present a non-cooperative feedback-rate control game (NFC), in which each MS
selects the feedback rate to maximize its performance in a distributed way. To
improve efficiency from a social optimum point of view, we then introduce
pricing, called the non-cooperative feedback-rate control game with price
(NFCP). The game utility is defined as the performance gain by CSI feedback
minus the price as a linear function of the CSI feedback rate. The existence of
the Nash equilibrium of such games is investigated, and two types of feedback
protocols (FDMA and CSMA) are studied. Simulation results show that by
adjusting the pricing factor, the distributed NFCP game results in close
optimal performance compared with that of the centralized scheme.Comment: 26 pages, 10 figures; IEEE Journal on Selected Areas in
Communications, special issue on Game Theory in Wireless Communications, 201
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