98,351 research outputs found
Underlay Cognitive Radio with Full or Partial Channel Quality Information
Underlay cognitive radios (UCRs) allow a secondary user to enter a primary
user's spectrum through intelligent utilization of multiuser channel quality
information (CQI) and sharing of codebook. The aim of this work is to study
two-user Gaussian UCR systems by assuming the full or partial knowledge of
multiuser CQI. Key contribution of this work is motivated by the fact that the
full knowledge of multiuser CQI is not always available. We first establish a
location-aided UCR model where the secondary user is assumed to have partial
CQI about the secondary-transmitter to primary-receiver link as well as full
CQI about the other links. Then, new UCR approaches are proposed and carefully
analyzed in terms of the secondary user's achievable rate, denoted by ,
the capacity penalty to primary user, denoted by , and capacity
outage probability. Numerical examples are provided to visually compare the
performance of UCRs with full knowledge of multiuser CQI and the proposed
approaches with partial knowledge of multiuser CQI.Comment: 29 Pages, 8 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
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