798 research outputs found
Joint Bandwidth and Power Allocation with Admission Control in Wireless Multi-User Networks With and Without Relaying
Equal allocation of bandwidth and/or power may not be efficient for wireless
multi-user networks with limited bandwidth and power resources. Joint bandwidth
and power allocation strategies for wireless multi-user networks with and
without relaying are proposed in this paper for (i) the maximization of the sum
capacity of all users; (ii) the maximization of the worst user capacity; and
(iii) the minimization of the total power consumption of all users. It is shown
that the proposed allocation problems are convex and, therefore, can be solved
efficiently. Moreover, the admission control based joint bandwidth and power
allocation is considered. A suboptimal greedy search algorithm is developed to
solve the admission control problem efficiently. The conditions under which the
greedy search is optimal are derived and shown to be mild. The performance
improvements offered by the proposed joint bandwidth and power allocation are
demonstrated by simulations. The advantages of the suboptimal greedy search
algorithm for admission control are also shown.Comment: 30 pages, 5 figures, submitted to IEEE Trans. Signal Processing in
June 201
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
Device-to-Device Communication in 5G Cellular Networks
Owing to the unprecedented and continuous growth in the number of connected users and networked devices, the next-generation 5G cellular networks are envisaged to support enormous number of simultaneously connected users and devices with access to numerous services and applications by providing networks with highly improved data rate, higher capacity, lower end-to-end latency, improved spectral efficiency, at lower power consumption. D2D communication underlaying cellular networks has been proposed as one of the key components of the 5G technology as a means of providing efficient spectrum reuse for improved spectral efficiency and take advantage of proximity between devices for reduced latency, improved user throughput, and reduced power consumption. Although D2D communication underlaying cellular networks promises lots of potentials, unlike the conventional cellular network architecture, there are new design issues and technical challenges that must be addressed for proper implementation of the technology. These include new device discovery procedures, physical layer architecture and radio resource management schemes. This thesis explores the potentials of D2D communication as an underlay to 5G cellular networks and focuses on efficient interference management solutions through mode selection, resource allocation and power control schemes. In this work, a joint admission control, resource allocation, and power control scheme was implemented for D2D communication underlaying 5G cellular networks. The performance of the system was evaluated, and comparisons were made with similar schemes.fi=OpinnÀytetyö kokotekstinÀ PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=LÀrdomsprov tillgÀngligt som fulltext i PDF-format
Optimal Distributed Resource Allocation for Decode-and-Forward Relay Networks
This paper presents a distributed resource allocation algorithm to jointly
optimize the power allocation, channel allocation and relay selection for
decode-and-forward (DF) relay networks with a large number of sources, relays,
and destinations. The well-known dual decomposition technique cannot directly
be applied to resolve this problem, because the achievable data rate of DF
relaying is not strictly concave, and thus the local resource allocation
subproblem may have non-unique solutions. We resolve this non-strict concavity
problem by using the idea of the proximal point method, which adds quadratic
terms to make the objective function strictly concave. However, the proximal
solution adds an extra layer of iterations over typical duality based
approaches, which can significantly slow down the speed of convergence. To
address this key weakness, we devise a fast algorithm without the need for this
additional layer of iterations, which converges to the optimal solution. Our
algorithm only needs local information exchange, and can easily adapt to
variations of network size and topology. We prove that our distributed resource
allocation algorithm converges to the optimal solution. A channel resource
adjustment method is further developed to provide more channel resources to the
bottleneck links and realize traffic load balance. Numerical results are
provided to illustrate the benefits of our algorithm
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