Adaptive downlink scheduling and rate selection: a cross-layer design

Haleem, M.A.; Chandramouli, R.

doi:10.1109/jsac.2005.845636

Cited by 63 publications

(46 citation statements)

References 7 publications

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“…In addition, the scope for licensed spectrum is not the same as the un-licensed spectrum. The idea of cross layer design [13] is introduced into this model. Routing agent is the key part in CRNRM model.…”

Section: Cognitive Radio Network Routing Model (Crnrm)mentioning

confidence: 99%

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A Survey on Different Routing Models in Cognitive Radio Ad-hoc Network

Ealias¹,

Gaur²

2014

IJAREEIE

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ABSTRACT:The demand for radio spectrum is expected to grow rapidly with the rapid growth of wireless communication in the near future. However, radio spectrum is a limited resource and it is already very crowded. The limited available spectrum and the inefficiency in the spectrum usage necessitate a new communication paradigm to exploit the existing wireless spectrum opportunistically. As it is difficult to accommodate more wireless applications within this limited resource, effective utilization of the unused wireless spectrum is a challenge from spectrum management perspective. To deal with the problems of spectrum congestion and spectrum under-utilization, cognitive radio (CR) has been recently proposed as the solution to current low usage of licensed spectrum problem. The main function for the cognitive radio is detecting unused spectrum, sharing the spectrum without harmful interference with other users and capturing the best scheduling the spectrum. Cognitive radio networks (CRNs) can make full use of spectrum resources of heterogeneous wireless architectures via dynamic spectrum access techniques. However, routing in CRNs impose challenges due to the fluctuating nature of the available spectrum. To study routing algorithm a model that can simulate CRNs routing protocol needs defining. This paper presents a comprehensive summary of different routing models for cognitive radio ad-hoc networks.

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Section: Cognitive Radio Network Routing Model (Crnrm)mentioning

confidence: 99%

“…And channel id is used for channel assignment. Cross layer design approach is introduced in DSMCRM model [13]. Routing agent is used to identify the user.…”

Section: Dynamic Spectrum Management Cognitive Radio Routing Model (Dmentioning

confidence: 99%

A Survey on Different Routing Models in Cognitive Radio Ad-hoc Network

Ealias¹,

Gaur²

2014

IJAREEIE

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“…In addition, the LA approaches can also track the optimal action for non-stationary environments as long as the statistic characteristics of the environment does not change very fast. Recently, the learning automata techniques have been extensively applied in various aspects in the communication and networking communities [16] [17] [18] [19] [20]. For an overview of learning automata techniques, refer to [21].…”

Section: B Learning Automatamentioning

confidence: 99%

Stochastic Channel Selection in Cognitive Radio Networks

Song

Fang

Zhang

2007

IEEE GLOBECOM 2007-2007 IEEE Global Telecommunications Conference

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Abstract-In this paper, we investigate the channel selection strategy for secondary users in cognitive radio networks. We claim that in order to avoid the costly channel switchings, a secondary user may desire an optimal channel which maximizes the probability of successful transmissions, rather than consistently adapting channels to the random environment. We propose a stochastic channel selection algorithm based on the learning automata techniques. This algorithm adjusts the probability of selecting each available channel and converges to the -optimal solution asymptotically.

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“…A user does not get personal benefit if a system optimizes the total throughput, but the performance of the own application is poor. The scheduling concept presented in [4,3] is specially designed for OFDM-TDMA transmissions and integrates the channel state into the MAC layer scheduling. In the approach presented in this paper, the PHY scheduling is separated from the MAC scheduling, however the schedulers communicate through an abstract interface, i. e. providing an importance metric instead of giving detailed information about packet lifetime etc.…”

Section: Introductionmentioning

confidence: 99%

Optimization of a QoS Aware Cross-Layer Scheduler by Packet Aggregation

Könsgen

Islam

Timm‐Giel

et al.

Wireless and Mobile Networking

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In this paper, the performance of a QoS-aware two-stage cross-layer scheduler utilising a MIMO channel for transmission is considered along with TDMA, OFDMA and SDMA channel access methods which serves a number of users with QoS-constrained data flows. OFDMA and SDMA allow a parallel transmission of packets which can have different transmission durations due to varying physical bit rates and packet lengths. The data flow with the longest packet slows down the other flows because they have to wait until the transmission is complete. This paper proposes packet aggregation where waiting times are reduced by transmitting more than one packet per user if airtime is left. It is shown that this method significantly enhances the QoS parameters throughput and delay. For constant-size packets, shorter delays can be achieved than for variable-size packets. Aggregating non-consecutive packets further enhances the performance, however the packets have to be buffered at the receiver to put them into the correct order. IntroductionWireless LANs have to meet increasing requirements nowadays and in the future: high data rates for each user, high spectral efficiency in the sense of a high total capacity and meeting several types of QoS requirements for different applications.Up to now, most protocols stacks are designed according to the OSI model which defines seven layers from the physical layer up to the application layer, with an increasing degree of abstraction from the physical hardware. In legacy protocol stacks, these different protocol layers have been optimised independently of each other. This separation is in particular problematic for the design of the two lowest layers, which are the MAC and the PHY layer, because there are close mutual dependencies between these two layers. The QoS requirements have already to be considered by selecting the physical transmission method. Moreover, the actual channel conditions and the effects of these conditions for a QoS aware transmission have to be known when selecting a particular packet for the transmission.Please use the following format when citing this chapter:

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Adaptive downlink scheduling and rate selection: a cross-layer design

Cited by 63 publications

References 7 publications

A Survey on Different Routing Models in Cognitive Radio Ad-hoc Network

A Survey on Different Routing Models in Cognitive Radio Ad-hoc Network

Stochastic Channel Selection in Cognitive Radio Networks

Optimization of a QoS Aware Cross-Layer Scheduler by Packet Aggregation

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