2,937 research outputs found
Distributed Beamforming and Rate Allocation in Multi-Antenna Cognitive Radio Networks
Abstract—We consider decentralized multi-antenna cognitive radio networks where secondary (cognitive) users are granted simultaneous spectrum access along with license-holding (pri-mary) users. We investigate the problem of designing beam-formers for the secondary users by maximizing the minimum rate, subject to a limited sum-power budget and constraints on the interference level imposed on each primary receiver. We consider two scenarios: the first one allows only single-user decoding at each secondary receiver whereas in the second case each secondary receiver is allowed to employ advanced multi-user decoding and is free to decode any subset of secondary users. We provide an optimal distributed algorithm for the first scenario and an explicit formulation of the optimization problem corresponding to the second scenario. This problem however is non-convex and hence cannot be efficiently solved even in a centralized setup. As a remedy, we suggest a two-step approach. In particular, the beamformers are first designed assuming single user decoding at each secondary receiver. An optimal distributed low-complexity algorithm is then proposed to allocate excess rates to the secondary users, which are made possible due to the use of advanced decoders at the secondary receivers. Simulation results demonstrate the gains yielded by the optimal beamformers as well as the rate allocation algorithms. I
Beamforming and Rate Allocation in MISO Cognitive Radio Networks
We consider decentralized multi-antenna cognitive radio networks where
secondary (cognitive) users are granted simultaneous spectrum access along with
license-holding (primary) users. We treat the problem of distributed
beamforming and rate allocation for the secondary users such that the minimum
weighted secondary rate is maximized. Such an optimization is subject to (1) a
limited weighted sum-power budget for the secondary users and (2) guaranteed
protection for the primary users in the sense that the interference level
imposed on each primary receiver does not exceed a specified level. Based on
the decoding method deployed by the secondary receivers, we consider three
scenarios for solving this problem. In the first scenario each secondary
receiver decodes only its designated transmitter while suppressing the rest as
Gaussian interferers (single-user decoding). In the second case each secondary
receiver employs the maximum likelihood decoder (MLD) to jointly decode all
secondary transmissions, and in the third one each secondary receiver uses the
unconstrained group decoder (UGD). By deploying the UGD, each secondary user is
allowed to decode any arbitrary subset of users (which contains its designated
user) after suppressing or canceling the remaining users.Comment: 32 pages, 6 figure
Dynamic Resource Allocation in Cognitive Radio Networks: A Convex Optimization Perspective
This article provides an overview of the state-of-art results on
communication resource allocation over space, time, and frequency for emerging
cognitive radio (CR) wireless networks. Focusing on the
interference-power/interference-temperature (IT) constraint approach for CRs to
protect primary radio transmissions, many new and challenging problems
regarding the design of CR systems are formulated, and some of the
corresponding solutions are shown to be obtainable by restructuring some
classic results known for traditional (non-CR) wireless networks. It is
demonstrated that convex optimization plays an essential role in solving these
problems, in a both rigorous and efficient way. Promising research directions
on interference management for CR and other related multiuser communication
systems are discussed.Comment: to appear in IEEE Signal Processing Magazine, special issue on convex
optimization for signal processin
Principles of Physical Layer Security in Multiuser Wireless Networks: A Survey
This paper provides a comprehensive review of the domain of physical layer
security in multiuser wireless networks. The essential premise of
physical-layer security is to enable the exchange of confidential messages over
a wireless medium in the presence of unauthorized eavesdroppers without relying
on higher-layer encryption. This can be achieved primarily in two ways: without
the need for a secret key by intelligently designing transmit coding
strategies, or by exploiting the wireless communication medium to develop
secret keys over public channels. The survey begins with an overview of the
foundations dating back to the pioneering work of Shannon and Wyner on
information-theoretic security. We then describe the evolution of secure
transmission strategies from point-to-point channels to multiple-antenna
systems, followed by generalizations to multiuser broadcast, multiple-access,
interference, and relay networks. Secret-key generation and establishment
protocols based on physical layer mechanisms are subsequently covered.
Approaches for secrecy based on channel coding design are then examined, along
with a description of inter-disciplinary approaches based on game theory and
stochastic geometry. The associated problem of physical-layer message
authentication is also introduced briefly. The survey concludes with
observations on potential research directions in this area.Comment: 23 pages, 10 figures, 303 refs. arXiv admin note: text overlap with
arXiv:1303.1609 by other authors. IEEE Communications Surveys and Tutorials,
201
Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks
In cognitive radio (CR) networks, there are scenarios where the secondary
(lower priority) users intend to communicate with each other by
opportunistically utilizing the transmit spectrum originally allocated to the
existing primary (higher priority) users. For such a scenario, a secondary user
usually has to trade off between two conflicting goals at the same time: one is
to maximize its own transmit throughput; and the other is to minimize the
amount of interference it produces at each primary receiver. In this paper, we
study this fundamental tradeoff from an information-theoretic perspective by
characterizing the secondary user's channel capacity under both its own
transmit-power constraint as well as a set of interference-power constraints
each imposed at one of the primary receivers. In particular, this paper
exploits multi-antennas at the secondary transmitter to effectively balance
between spatial multiplexing for the secondary transmission and interference
avoidance at the primary receivers. Convex optimization techniques are used to
design algorithms for the optimal secondary transmit spatial spectrum that
achieves the capacity of the secondary transmission. Suboptimal solutions for
ease of implementation are also presented and their performances are compared
with the optimal solution. Furthermore, algorithms developed for the
single-channel transmission are also extended to the case of multi-channel
transmission whereby the secondary user is able to achieve opportunistic
spectrum sharing via transmit adaptations not only in space, but in time and
frequency domains as well.Comment: Extension of IEEE PIMRC 2007. 35 pages, 6 figures. Submitted to IEEE
Journal of Special Topics in Signal Processing, special issue on Signal
Processing and Networking for Dynamic Spectrum Acces
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