3,270 research outputs found
Cooperative Precoding/Resource Allocation Games under Spectral Mask and Total Power Constraints
The use of orthogonal signaling schemes such as time-, frequency-, or
code-division multiplexing (T-, F-, CDM) in multi-user systems allows for
power-efficient simple receivers. It is shown in this paper that by using
orthogonal signaling on frequency selective fading channels, the cooperative
Nash bargaining (NB)-based precoding games for multi-user systems, which aim at
maximizing the information rates of all users, are simplified to the
corresponding cooperative resource allocation games. The latter provides
additional practically desired simplifications to transmitter design and
significantly reduces the overhead during user cooperation. The complexity of
the corresponding precoding/resource allocation games, however, depends on the
constraints imposed on the users. If only spectral mask constraints are
present, the corresponding cooperative NB problem can be formulated as a convex
optimization problem and solved efficiently in a distributed manner using dual
decomposition based algorithm. However, the NB problem is non-convex if total
power constraints are also imposed on the users. In this case, the complexity
associate with finding the NB solution is unacceptably high. Therefore, the
multi-user systems are categorized into bandwidth- and power-dominant based on
a bottleneck resource, and different manners of cooperation are developed for
each type of systems for the case of two-users. Such classification guarantees
that the solution obtained in each case is Pareto-optimal and actually can be
identical to the optimal solution, while the complexity is significantly
reduced. Simulation results demonstrate the efficiency of the proposed
cooperative precoding/resource allocation strategies and the reduced complexity
of the proposed algorithms.Comment: 33 pages, 8 figures, Submitted to the IEEE Trans. Signal Processing
in Oct. 200
Power Allocation and Time-Domain Artificial Noise Design for Wiretap OFDM with Discrete Inputs
Optimal power allocation for orthogonal frequency division multiplexing
(OFDM) wiretap channels with Gaussian channel inputs has already been studied
in some previous works from an information theoretical viewpoint. However,
these results are not sufficient for practical system design. One reason is
that discrete channel inputs, such as quadrature amplitude modulation (QAM)
signals, instead of Gaussian channel inputs, are deployed in current practical
wireless systems to maintain moderate peak transmission power and receiver
complexity. In this paper, we investigate the power allocation and artificial
noise design for OFDM wiretap channels with discrete channel inputs. We first
prove that the secrecy rate function for discrete channel inputs is nonconcave
with respect to the transmission power. To resolve the corresponding nonconvex
secrecy rate maximization problem, we develop a low-complexity power allocation
algorithm, which yields a duality gap diminishing in the order of
O(1/\sqrt{N}), where N is the number of subcarriers of OFDM. We then show that
independent frequency-domain artificial noise cannot improve the secrecy rate
of single-antenna wiretap channels. Towards this end, we propose a novel
time-domain artificial noise design which exploits temporal degrees of freedom
provided by the cyclic prefix of OFDM systems {to jam the eavesdropper and
boost the secrecy rate even with a single antenna at the transmitter}.
Numerical results are provided to illustrate the performance of the proposed
design schemes.Comment: 12 pages, 7 figures, accepted by IEEE Transactions on Wireless
Communications, Jan. 201
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
- …