A neural network approach to solving the link activation problem in multihop radio networks

Barnhart, C.M.; Wieselthier, Jeffrey E.; Ephremides, Anthony

doi:10.1109/26.380169

Cited by 20 publications

(13 citation statements)

References 15 publications

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“…Our formulation of an LP to jointly optimize routing and scheduling within the framework of variable-rate transmissions dependent on the interference power is in contrast to that of other authors, who either do not consider the joint routing-scheduling problem [16], or focus on power control in place of variable-rate transmission [14], or neglect the effect of interference on transmission rates [15], [17], or do not formulate the routing problem as an LP [10]. In addition, in this paper, we also provide a systematic evaluation of the throughput-range tradeoff for backhaul communication.…”

Section: Introductionmentioning

confidence: 71%

Throughput-range tradeoff of wireless mesh backhaul networks

Viswanathan¹,

Mukherjee²

2006

IEEE J. Select. Areas Commun.

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Abstract-Wireless backhaul communication is expected to play a significant role in providing the necessary backhaul resources for future high-rate wireless networks. Mesh networking, in which information is routed from source to destination over multiple wireless links, has potential advantages over traditional single-hop networking, especially for backhaul communication. We develop a linear programming framework for determining optimum routing and scheduling of flows that maximizes throughput in a wireless mesh network and accounts for the effect of interference and variable-rate transmission. We then apply this framework to examine the throughput and range capabilities for providing wireless backhaul to a hexagonal grid of base stations, for both single-hop and multihop transmissions for various network scenarios. We then discuss the application of mesh networking for load balancing of wired backhaul traffic under unequal access traffic conditions. Numerical results show a significant benefit for mesh networking under unbalanced loading.

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Section: Introductionmentioning

confidence: 71%

Throughput-range tradeoff of wireless mesh backhaul networks

Viswanathan¹,

Mukherjee²

2006

IEEE J. Select. Areas Commun.

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“…3. Let the SD pair be (1,6), and the reliability of each station be 0.9. Dividing the cases into those in which the stations are in normal or fault states, there can be 26 states, since there are 6 stations.…”

Section: Reliability-constrained Route Assignment Problemmentioning

confidence: 99%

“…The performance of the proposed procedure is evaluated by simulation [5]. Finally, the conclusions of the paper are presented [6].…”

Section: Introductionmentioning

confidence: 99%

“…For this purpose, the topology of the communication network is represented by a graph, and the communication path assignment problem [3] and the scheduling problem [6,7] are formulated. In the former, when multiple transfer request pairs (SD pairs) indicating the source and the destination of the packet are specified, the communication path is assigned so that the total required number of time slots is minimized.…”

Section: Introductionmentioning

confidence: 99%

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A neural network combined two‐stage algorithm for route assignment problems with reliability satisfaction in multihop radio networks

Baba

Funabiki

Tajima

2002

Electron Comm Jpn Pt III

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SUMMARYThe radio network is a large-scale communication network in which a large number of stations are distributed over a wide area. Each station can communicate directly by radio packets only with neighborhood stations. Packet communication between stations which cannot communicate directly is realized by passing packets through multiple stations between them. For this purpose, when a packet communication request arises, the route for the packet and the transfer timing must be chosen so that the total transfer time is minimized and the efficiency of the radio network is maximized. It should be noted that the reliability, representing the probability that the required performance is achieved, fluctuates among the stations in the network due to the differences in the time of installation, the designed performance, and communication congestion. Consequently, this paper proposes a two-stage algorithm in which the route is assigned so that its reliability is larger than the required value. The proposed algorithm is composed of the iterative reliability satisfaction extraction procedure, in which a set of path candidates satisfying the reliability condition for the given transfer request, and the greedy neural network procedure, in which the route minimizing the cost is selected from the set of path candidates. The effectiveness of the proposed algorithm is demonstrated by simulation for networks with up to 500 stations.

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“…In an early work, Barnhard, Wieselthier and Ephremides [29] trained neural networks to find a link-activation schedule within a network. Other work has applied neural networks to create efficient routing across a network [32].…”

Section: Neural Networkmentioning

confidence: 99%

Experiences Implementing Cognitive Radio Control Algorithms

Doerr

Sicker

Grunwald

2007

IEEE GLOBECOM 2007-2007 IEEE Global Telecommunications Conference

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Abstract-In recent years, several algorithms for controlling cognitive radio platforms have been proposed. In this paper, we review the existing approaches that have been developed for cognitive radio control algorithms and extract the common sensing and control requirements for those algorithms. We also briefly discuss the challenges of defining representative testing scenarios. We then synthesize our experience implementing cognitive radio control algorithms and extract a set of pragmatic issues challenging researchers in cognitive radios. We conclude with a set of open questions and problems and discuss implications for future research.

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A neural network approach to solving the link activation problem in multihop radio networks

Cited by 20 publications

References 15 publications

Throughput-range tradeoff of wireless mesh backhaul networks

Throughput-range tradeoff of wireless mesh backhaul networks

A neural network combined two‐stage algorithm for route assignment problems with reliability satisfaction in multihop radio networks

Experiences Implementing Cognitive Radio Control Algorithms

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