Koen De Turck

Performance analysis of the IEEE 802.16e sleep mode for correlated downlink traffic

In this paper, we evaluate the performance of the IEEE 802.16e sleep mode mechanism in wireless access networks. This mechanism reduces the energy consumption of a mobile station (MS) by allowing it to turn off its radio interface (sleep mode) when there is no traffic present at its serving base station (BS). After a sleep period expires, the MS briefly checks the BS for data packets and switches off for the duration of another sleep period if none are available. Specifically for IEEE 802.16e, each additional sleep period doubles in length, up to a certain maximum. Clearly, the sleep mode mechanism can extend the battery life of the MS considerably, but also increases the delay at the BS buffer. For the performance analysis, we use a discrete-time queueing model with general service times and multiple server vacations. The vacations represent the sleep periods and have a length depending on the number of preceding vacations. Unlike previous studies, we take the (short-range) traffic correlation into account by assuming a D-BMAP arrival process, i.e. the distribution of the number of packet arrivals per slot is modulated by the transitions in a Markov chain with N background states. As results, we obtain the distribution of the number of packets in the queue at various sets of time epochs, the distribution of the packet delay and the antenna activity rate. We apply these results to the IEEE 802.16e sleep mode mechanism with correlated downlink traffic. By means of some examples, we show the influence of both the configuration parameters and the traffic correlation on the delay and the energy consumption.

Delay versus energy consumption of the IEEE 802.16e sleep-mode mechanism

We propose a discrete-time queueing model for the evaluation of the IEEE 802.16e sleep-mode mechanism of power saving class (PSC) I in wireless access networks. Contrary to previous studies, we model the downlink traffic by means of a discrete batch Markov arrival process (D-BMAP) with N phases, which allows to take traffic correlation into account. The tradeoff between energy saving and increased packet delay is discussed. In many situations, the sleep-mode performance improves for heavily correlated traffic. Also, when compared to other strategies, the exponential sleep-period update strategy of PSC I may not always be the best.

An analytic model of IEEE 802.16e sleep mode operation with correlated traffic

We propose and analyse a discrete-time queueing model for the evaluation of the IEEE 802.16e sleep mode operation in wireless access networks. This mechanism reduces the energy consumption of a mobile station (MS) by allowing it to turn off its radio interface (sleep mode) when there is no traffic present at its serving base station (BS). After a sleep period expires, the MS briefly checks the BS for data packets and switches off for the duration of another sleep period if none are available. Specifically for IEEE 802.16e, each additional sleep period doubles in length, up to a certain maximum. Clearly, the sleep mode mechanism can extend the battery life of the MS considerably, but also increases the delay at the BS buffer. n nFor the analysis, we use a discrete-time queueing model with general service times and multiple server vacations. The vacations represent the sleep periods and have a length depending on the number of preceding vacations. Unlike previous studies, we take the traffic correlation into account by assuming a D-BMAP arrival process. The distribution of the number of packets in the queue is obtained at various sets of time epochs, as well as the mean packet delay and the mean number of consecutive vacations. We apply these results to the IEEE 802.16e sleep mode mechanism with downlink traffic. By means of some examples, we show the influence of both the configuration parameters and the traffic correlation on the delay and the energy consumption.

Saturation Throughput in a Heterogeneous Multi-Channel Cognitive Radio Network

In this paper we consider a cognitive radio network in a heterogeneous multi-channel scenario where channels are different in terms of achievable bit rates. Upon arrival licensed users (PUs) will occupy first the channels with higher achievable rates. As a result, secondary users (SUs) will see a set of channels which are different not only in their physical capacities but also in the activity profile of PUs. Consequently, from the point of view of the effective throughput that SUs can obtain in each channel there exists a trade-off between the rate they can obtain in a certain channel and the amount of time they can use it. We develop a model that allows to solve this trade-off by computing the maximum effective throughput that SUs can achieve in each channel.

Performance of the Sleep-Mode Mechanism of the New IEEE 802.16m Proposal for Correlated Downlink Traffic

There is a considerable interest nowadays in making wireless telecommunication more energy-efficient. The sleep-mode mechanism in WiMAX (IEEE 802.16e) is one of such energy saving measures. Recently, Samsung proposed some modifications on the sleep-mode mechanism, scheduled to appear in the forthcoming IEEE 802.16m standard, aimed at minimizing the signaling overhead. In this work, we present a performance analysis of this proposal and clarify the differences with the standard mechanism included in IEEE 802.16e. We also propose some special algorithms aimed at reducing the computational complexity of the analysis.

Tail asymptotics of a Markov-modulated infinite-server queue

This paper analyzes large deviation probabilities related to the number of customers in a Markov-modulated infinite-server queue, with state-dependent arrival and service rates. Two specific scalings are studied: in the first, just the arrival rates are linearly scaled by

Rare event analysis of Markov-modulated infinite-server queues: A Poisson limit

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A Central Limit Theorem for Markov-Modulated Infinite-Server Queues

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