Hussein Al-Zubaidy

Network-layer performance analysis of multihop fading channels

A fundamental problem for the delay and backlog analysis across multihop paths in wireless networks is how to account for the random properties of the wireless channel. Since the usual statistical models for radio signals in a propagation environment do not lend themselves easily to a description of the available service rate, the performance analysis of wireless networks has resorted to higher-layer abstractions, e.g., using Markov chain models. In this paper, we propose a network calculus that can incorporate common statistical models of fading channels and obtain statistical bounds on delay and backlog across multiple nodes. We conduct the analysis in a transfer domain, where the service process at a link is characterized by the instantaneous signal-to-noise ratio at the receiver. We discover that, in the transfer domain, the network model is governed by a dioid algebra, which we refer to as the (min, ×) algebra. Using this algebra, we derive the desired delay and backlog bounds. Using arguments from large deviations theory, we show that the bounds are asymptotically tight. An application of the analysis is demonstrated for a multihop network of Rayleigh fading channels with cross traffic at each hop.

A (min, ×) network calculus for multi-hop fading channels

A fundamental problem for the delay and backlog analysis across multi-hop paths in wireless networks is how to account for the random properties of the wireless channel. Since the usual statistical models for radio signals in a propagation environment do not lend themselves easily to a description of the available service rate, the performance analysis of wireless networks has resorted to higher-layer abstractions, e.g., using Markov chain models. In this work, we propose a network calculus that can incorporate common statistical models of fading channels and obtain statistical bounds on delay and backlog across multiple nodes. We conduct the analysis in a transfer domain, which we refer to as the SNR domain, where the service process at a link is characterized by the instantaneous signal-to-noise ratio at the receiver. We discover that, in the transfer domain, the network model is governed by a dioid algebra, which we refer to as (min, ×) algebra. Using this algebra we derive the desired delay and backlog bounds. An application of the analysis is demonstrated for a simple multi-hop network with Rayleigh fading channels.

Optimal scheduling in high-speed downlink packet access networks

We present an analytic model and a methodology to determine the optimal packet scheduling policy in a High-Speed Downlink Packet Access (HSDPA) system. The optimal policy is the one that maximizes cell throughput while maintaining a level of fairness between the users in the cell. A discrete stochastic dynamic programming model for the HSDPA downlink scheduler is presented. Value iteration is then used to solve for the optimal scheduling policy. We use a FSMC (Finite State Markov Channel) to model the HSDPA downlink channel. A near-optimal heuristic scheduling policy is developed. Simulation is used to study the performance of the resulting heuristic policy and compare it to the computed optimal policy. The results show that the performance of the heuristic policy is very close to that of the optimal policy. The heuristic policy has much less computational complexity, which makes it easy to deploy, with only slight reduction in performance compared to the optimal policy.

Delay Analysis for Wireless Fading Channels with Finite Blocklength Channel Coding

Upcoming low-latency machine-to-machine (M2M) applications are currently attracting a significant amount of interest from the wireless networking research community. The design challenge with respect to such future applications is to allow wireless networks to operate extremely reliably at very short deadlines for rather small packets. To date, it is unclear how to design wireless networks efficiently for such novel requirements. One reason is that existing performance models for wireless networks often assume that the rate of the channel code is equal to the Shannon capacity. However, this model does not hold anymore when the packet size and thus blocklength of the channel code is small. Although it is known that finite blocklength has a major impact on the physical layer performance, we lack higher-layer performance models which account in particular for the queueing effects under the finite blocklength regime. A recently developed methodology provides probabilistic higher-layer delay bounds for fading channels when assuming transmission at the Shannon capacity limit. Based on this novel approach, we develop service process characterizations for fading channels with finite blocklength channel coding, leading to novel probabilistic delay bounds that can give a fundamental insight into the capabilities and limitations of wireless networks when facing low-latency M2M applications. In particular, we show that the Shannon capacity model significantly overestimates the delay performance for such applications, which would lead to insufficient resource allocations. Finally, based on our (validated) analytical model, we study various important parameter trade-offs highlighting the sensitivity of the delay distribution under the finite blocklength regime.

On the recursive nature of end-to-end delay bound for heterogeneous wireless networks

Multi-hop wireless networks are increasingly becoming more relevant to current and emerging wireless network deployment. The need for understanding the performance of such networks in order to be able to provide quantifiable end-to-end quality of service is apparent. Until recently, only asymptotic results that describe the scaling of the delay in the size of the network under numerous conformity conditions were available. Recently, a new methodology for wireless networks performance analysis based on stochastic network calculus was presented [1]. This methodology enables the computation of end-to-end probabilistic delay bound of multi-hop wireless networks in terms of the underlying fading channel parameters. However, the approach assumes identically distributed channel gain which applies to a very specific class of networks. In this work, we seek to develop an end-to-end probabilistic delay bound for multi-hop wireless networks with non-identically distributed channel gains. We show that the delay bound for such networks can be computed recursively. We validate the resulting bound by means of simulation and discuss various numerical examples.

Optimal Scheduling Policy Determination for High Speed Downlink Packet Access

In this paper, we present an analytic model and methodology to determine optimal scheduling policy that involves two dimension space allocation: time and code, in high speed downlink packet access (HSDPA) system. A discrete stochastic dynamic programming model for the HSDPA downlink scheduler is presented. Value iteration is then used to solve for optimal policy. This framework is used to find the optimal scheduling policy for the case of two users sharing the same cell. Simulation is used to study the performance of the resulted optimal policy using round robin (RR) scheduler as a baseline. The policy granularity is introduced to reduce the computational complexity by reducing the action space. The results showed that finer granularity (down to 5 codes) enhances the performance significantly. However, the enhancement gained when using even finer granularity was marginal and does not justify the added complexity. The behaviour of the value function was observed to characterize the optimal scheduling policy. These observations is then used to develop a heuristic scheduling policy. The devised heuristic policy has much less computational complexity which makes it easy to deploy and with only slight reduction in performance compared to the optimal policy according to the simulation results.

Effective Capacity of Retransmission Schemes: A Recurrence Relation Approach

We consider the effective capacity performance measure of persistent- and truncated-retransmission schemes that can involve any combination of multiple transmissions per packet, multiple communication modes, or multiple packet communication. We present a structured unified analytical approach, based on a random walk model and recurrence relation formulation, and give exact effective capacity expressions for persistent hybrid automatic repeat request (HARQ) and for truncated-retransmission schemes. For the latter, effective capacity expressions are given for systems with finite (infinite) time horizon on an algebraic (spectral radius-based) form of a special block companion matrix. In contrast to prior HARQ models, assuming infinite time horizon, the proposed method does not involve a non-trivial per case modeling step. We give effective capacity expressions for several important cases that have not been addressed before, e.g., persistent-HARQ, truncated-HARQ, network-coded ARQ, two-mode-ARQ, and multilayer-ARQ. We propose an alternative quality-of-service-parameter (instead of the commonly used moment generating function parameter) that represents explicitly the target delay and the delay violation probability. This also enables the closed-form expressions for many of the studied systems. Moreover, we use the recently proposed matrix-exponential distributed modeling of wireless fading channels to provide the basis for numerous new effective capacity results for HARQ.

Power minimization for industrial wireless networks under statistical delay constraints

Energy efficiency is a very important aspect of modern communication systems. In particular, industrial appli-cations, that deploy wireless machine-to-machine communication and process automation, demand energy-efficient communication in order to prolong battery lifetime and reduce inter-node interference, while maintaining a predefined probabilistic delay bound. In this work, we propose an algorithm that minimizes the transmit power in a WirelessHART network under statistical delay constraints. We achieve this by utilizing a recently developed network calculus approach for wireless networks performance analysis. The evaluation of the algorithm shows that it reaches quasi-minimal power settings within a few iterations.

Call center performance evaluation

In this paper, the effect of using a combination of multi-skill and specialized agents on the performance of a call center is studied. An OPNET simulator for the call center has been designed, implemented, and verified. The designed simulator has the flexibility that facilitates comparison of different scenarios. The scenarios are mainly oriented toward finding the performance enhancement that could be gained by using a combination of multi-skill and specialized agents. As the usual case in such problems, there must be an optimum combination that results in the best performance for a lower cost. The designed simulator provides a very powerful and scalable tool that could be used to find such an optimum, and could be easily modified to support larger call centers. Some selected scenarios have been tested and the results introduced and analyzed. The result of our research concludes that the economies of scale could be obtained by cross training only a minor fraction of agents

Dynamic Packet Scheduler Optimization in Wireless Relay Networks

In this work, we investigate the optimal dynamic packet scheduling policy in a wireless relay network (WRN). We model this network by two sets of parallel queues, that represent the subscriber stations (SS) and the relay stations (RS), with random link connectivity. An optimal policy minimizes, in stochastic ordering sense, a cost function of the SS and RS queue sizes. We prove that, in a system with symmetrical connectivity and arrival distributions, a policy that tries to balance the lengths of all the system queues, at every time slot, is optimal. We use stochastic dominance and coupling arguments in our proof. We also provide a low-overhead algorithm for optimal policy implementation.