Conference Paper
A Theory of QoS for Wireless
Dept. of Comput. Sci., Univ. of Illinois Urbana, Urbana, IL
DOI: 10.1109/INFCOM.2009.5061954 Conference: INFOCOM 2009, IEEE Source: IEEE Xplore

Conference Paper: Scheduling with Outdated CSI: Effective Service Capacities of Optimistic vs. Pessimistic Policies
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ABSTRACT: The concept of the effective service capacity is an analytical framework for evaluating QoSconstrained queuing performance of communication systems. Recently, it has been applied to the analysis of different wireless systems like pointtopoint systems or multiuser systems. In contrast to previous work, we consider in this work slotbased systems where a scheduler determines a packet size to be transmitted at the beginning of the slot. For this, the scheduler can utilize outdated channel state information. Based on a threshold error model, we derive the effective service capacity for different scheduling strategies that the scheduler might apply. We show that even slightly outdated channel state information leads to a significant loss in capacity in comparison to an ideal system with perfect channel state information available at the transmitter. This loss depends on the 'risklevel' the scheduler is willing to take which is represented by an SNR margin. We show that for any QoS target and average link state there exists an optimal SNR margin improving the maximum sustainable rate. Typically, this SNR margin is around 3 dB but is sensible to the QoS target and average link quality. Finally, we can also show that adapting to the instantaneous channel state only pays off if the correlation between the channel estimate and the channel state is relatively high (with a coefficient above 0.9).IEEE 20th International Workshop on Quality of Service (IWQoS), Coimbra, Portugal; 06/2012  [Show abstract] [Hide abstract]
ABSTRACT: We consider a data aggregating wireless network where all nodes have data to send to a single destination node, the sink. We consider a linear placement of nodes with the sink at one end. The nodes communicate directly to the sink (single hop transmission) and we assume that the nodes are scheduled one at a time by a central scheduler (possibly the sink). The wireless nodes are power limited and our network objective (notion of fairness) is to maximize the minimum throughput of the nodes subject to the node power constraints. In this work, we consider network designs that permit adapting node transmission time, node transmission power and node placements, and study cross layer strategies that seek to maximize the network throughput. Using simulations, we characterize the performance of the dif ferent strategies and comment on their applicability for various network scenarios.01/2013;  [Show abstract] [Hide abstract]
ABSTRACT: Motivated by the regular service requirements of video applications for improving QualityofExperience (QoE) of users, we consider the design of scheduling strategies in multihop wireless networks that not only maximize system throughput but also provide regular interservice times for all links. Since the service regularity of links is related to the higherorder statistics of the arrival process and the policy operation, it is highly challenging to characterize and analyze directly. We overcome this obstacle by introducing a new quantity, namely the timesincelastservice (TSLS), which tracks the time since the last service. By combining it with the queuelength in the weight, we propose a novel maximumweight type scheduling policy, called Regular Service Guarantee (RSG) Algorithm. The unique evolution of the TSLS counter poses significant challenges for the analysis of the RSG Algorithm. To tackle these challenges, we first propose a novel Lyapunov function to show the throughput optimality of the RSG Algorithm. Then, we prove that the RSG Algorithm can provide service regularity guarantees by using the Lyapunovdrift based analysis of the steadystate behavior of the stochastic processes. In particular, our algorithm can achieve a degree of service regularity within a factor of a fundamental lower bound we derive. This factor is a function of the system statistics and design parameters and can be as low as two in some special networks. Our results, both analytical and numerical, exhibit significant service regularity improvements over the traditional throughputoptimal policies, which reveals the importance of incorporating the metric of timesincelastservice into the scheduling policy for providing regulated service.05/2014;
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