6,614 research outputs found
Exploiting Trust Degree for Multiple-Antenna User Cooperation
For a user cooperation system with multiple antennas, we consider a trust
degree based cooperation techniques to explore the influence of the
trustworthiness between users on the communication systems. For the system with
two communication pairs, when one communication pair achieves its quality of
service (QoS) requirement, they can help the transmission of the other
communication pair according to the trust degree, which quantifies the
trustworthiness between users in the cooperation. For given trust degree, we
investigate the user cooperation strategies, which include the power allocation
and precoder design for various antenna configurations. For SISO and MISO
cases, we provide the optimal power allocation and beamformer design that
maximize the expected achievable rates while guaranteeing the QoS requirement.
For a SIMO case, we resort to semidefinite relaxation (SDR) technique and block
coordinate update (BCU) method to solve the corresponding problem, and
guarantee the rank-one solutions at each step. For a MIMO case, as MIMO is the
generalization of MISO and SIMO, the similarities among their problem
structures inspire us to combine the methods from MISO and SIMO together to
efficiently tackle MIMO case. Simulation results show that the trust degree
information has a great effect on the performance of the user cooperation in
terms of the expected achievable rate, and the proposed user cooperation
strategies achieve high achievable rates for given trust degree.Comment: 15 pages,9 figures, to appear in IEEE Transactions on Wireless
communication
Green Cellular Networks: A Survey, Some Research Issues and Challenges
Energy efficiency in cellular networks is a growing concern for cellular
operators to not only maintain profitability, but also to reduce the overall
environment effects. This emerging trend of achieving energy efficiency in
cellular networks is motivating the standardization authorities and network
operators to continuously explore future technologies in order to bring
improvements in the entire network infrastructure. In this article, we present
a brief survey of methods to improve the power efficiency of cellular networks,
explore some research issues and challenges and suggest some techniques to
enable an energy efficient or "green" cellular network. Since base stations
consume a maximum portion of the total energy used in a cellular system, we
will first provide a comprehensive survey on techniques to obtain energy
savings in base stations. Next, we discuss how heterogeneous network deployment
based on micro, pico and femto-cells can be used to achieve this goal. Since
cognitive radio and cooperative relaying are undisputed future technologies in
this regard, we propose a research vision to make these technologies more
energy efficient. Lastly, we explore some broader perspectives in realizing a
"green" cellular network technologyComment: 16 pages, 5 figures, 2 table
Power allocation in wireless multi-user relay networks
In this paper, we consider an amplify-and-forward wireless relay system where multiple source nodes communicate with their corresponding destination nodes with the help of relay nodes. Conventionally, each relay equally distributes the available resources to its relayed sources. This approach is clearly sub-optimal since each user experiences dissimilar channel conditions, and thus, demands different amount of allocated resources to meet its quality-of-service (QoS) request. Therefore, this paper presents novel power allocation schemes to i) maximize the minimum signal-to-noise ratio among all users; ii) minimize the maximum transmit power over all sources; iii) maximize the network throughput. Moreover, due to limited power, it may be impossible to satisfy the QoS requirement for every user. Consequently, an admission control algorithm should first be carried out to maximize the number of users possibly served. Then, optimal power allocation is performed. Although the joint optimal admission control and power allocation problem is combinatorially hard, we develop an effective heuristic algorithm with significantly reduced complexity. Even though theoretically sub-optimal, it performs remarkably well. The proposed power allocation problems are formulated using geometric programming (GP), a well-studied class of nonlinear and nonconvex optimization. Since a GP problem is readily transformed into an equivalent convex optimization problem, optimal solution can be obtained efficiently. Numerical results demonstrate the effectiveness of our proposed approach
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