3,356 research outputs found
Quantifying Potential Energy Efficiency Gain in Green Cellular Wireless Networks
Conventional cellular wireless networks were designed with the purpose of
providing high throughput for the user and high capacity for the service
provider, without any provisions of energy efficiency. As a result, these
networks have an enormous Carbon footprint. In this paper, we describe the
sources of the inefficiencies in such networks. First we present results of the
studies on how much Carbon footprint such networks generate. We also discuss
how much more mobile traffic is expected to increase so that this Carbon
footprint will even increase tremendously more. We then discuss specific
sources of inefficiency and potential sources of improvement at the physical
layer as well as at higher layers of the communication protocol hierarchy. In
particular, considering that most of the energy inefficiency in cellular
wireless networks is at the base stations, we discuss multi-tier networks and
point to the potential of exploiting mobility patterns in order to use base
station energy judiciously. We then investigate potential methods to reduce
this inefficiency and quantify their individual contributions. By a
consideration of the combination of all potential gains, we conclude that an
improvement in energy consumption in cellular wireless networks by two orders
of magnitude, or even more, is possible.Comment: arXiv admin note: text overlap with arXiv:1210.843
Network-Level Performance Evaluation of a Two-Relay Cooperative Random Access Wireless System
In wireless networks relay nodes can be used to assist the users'
transmissions to reach their destination. Work on relay cooperation, from a
physical layer perspective, has up to now yielded well-known results. This
paper takes a different stance focusing on network-level cooperation. Extending
previous results for a single relay, we investigate here the benefits from the
deployment of a second one. We assume that the two relays do not generate
packets of their own and the system employs random access to the medium; we
further consider slotted time and that the users have saturated queues. We
obtain analytical expressions for the arrival and service rates of the queues
of the two relays and the stability conditions. We investigate a model of the
system, in which the users are divided into clusters, each being served by one
relay, and show its advantages in terms of aggregate and throughput per user.
We quantify the above, analytically for the case of the collision channel and
through simulations for the case of Multi-Packet Reception (MPR), and we
provide insight on when the deployment of a second relay in the system can
yield significant advantages.Comment: Submitted for journal publicatio
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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