Edwin K. P. Chong

A framework for opportunistic scheduling in wireless networks

Abstract We present a method, called opportunistic scheduling, for exploiting the time-varying nature of the radio environment to increase the overall performance of the system under certain quality of service/fairness requirements of users. We first introduce a general framework for opportunistic scheduling, and then identify three general categories of scheduling problems under this framework. We provide optimal solutions for each of these scheduling problems. All the proposed scheduling policies are implementable online; we provide parameter estimation algorithms and implementation procedures for them. We also show how previous work by us and others directly fits into or is related to this framework. We demonstrate via simulation that opportunistic scheduling schemes result in significant performance improvement compared with non-opportunistic alternatives.

A utility-based power-control scheme in wireless cellular systems

Distributed power-control algorithms for systems with hard signal-to-interference ratio (SIR) constraints may diverge when infeasibility arises. In this paper, we present a power-control framework called utility-based power control (UBPC) by reformulating the problem using a softened SIR requirement (utility) and adding a penalty on power consumption (cost). Under this framework, the goal is to maximize the net utility, defined as utility minus cost. Although UBPC is still noncooperative and distributed in nature, some degree of cooperation emerges: a user will automatically decrease its target SIR (and may even turn off transmission) when it senses that traffic congestion is building up. This framework enables us to improve system convergence and to satisfy heterogeneous service requirements (such as delay and bit error rate) for integrated networks with both voice users and data users. Fairness, adaptiveness, and a high degree of flexibility can be achieved by properly tuning parameters in UBPC.

Output MAI distributions of linear MMSE multiuser receivers in DS-CDMA systems

Multiple-access interference (MAI) in a code-division multiple-access (CDMA) system plays an important role in performance analysis and characterization of fundamental system limits. We study the behavior of the output MAI of the minimum mean-square error (MMSE) receiver employed in the uplink of a direct-sequence (DS)-CDMA system. We focus on imperfect power-controlled systems with random spreading, and establish that in a synchronous system (1) the output MAI of the MMSE receiver is asymptotically Gaussian, and (2) for almost every realization of the signatures and received powers, the conditional distribution of the output MAI converges weakly to the same Gaussian distribution as in the unconditional case. We also extend our study to asynchronous systems and establish the Gaussian nature of the output interference. These results indicate that in a large system the output interference is approximately Gaussian, and the performance of the MMSE receiver is robust to the randomness of the signatures and received powers. The Gaussianity justifies the use of single-user Gaussian codes for CDMA systems with linear MMSE receivers, and implies that from the viewpoints of detection and channel capacity, signal-to-interference ratio (SIR) is the key parameter that governs the performance of the MMSE receiver in a CDMA system.

Utility-based power control in cellular wireless systems

Distributed power control algorithms for systems with hard SIR constraints may diverge when infeasibility arises. We present a power control framework called utility-based power control (UBPC) by reformulating the problem using a softened SIR requirement (utility) and adding a penalty on power consumption (cost). Under this framework, the goal is to maximize the net utility, defined as utility minus cost. Although UBPC is still non-cooperative and distributed in nature, some degree of cooperation emerges: a user will automatically decrease its target SIR (and may even turn off transmission) when it senses that traffic congestion is building up. This framework enables us to improve the system convergence and to satisfy heterogeneous service requirements (such as delay and bit error rate) for integrated networks with both voice users and data users. Fairness, adaptiveness, and a high degree of flexibility can be achieved by properly tuning parameters in UBPC.

Efficient multicast stream authentication using erasure codes

We describe a novel method for authenticating multicast packets that is robust against packet loss. Our focus is to minimize the size of the communication overhead required to authenticate the packets. Our approach is to encode the hash values and the signatures with Rabins Information Dispersal Algorithm (IDA) to construct an authentication scheme that amortizes a single signature operation over multiple packets. This strategy is especially efficient in terms of space overhead, because just the essential elements needed for authentication (i.e., one hash per packet and one signature per group of packets) are used in conjunction with an erasure code that is space optimal. Using asymptotic techniques, we derive the authentication probability of our scheme using two different bursty loss models. A lower bound of the authentication probability is also derived for one of the loss models. To evaluate the performance of our scheme, we compare our technique with four other previously proposed schemes using empirical results.

Efficient multicast packet authentication using signature amortization

We describe a novel method for authenticating multicast packets that is robust against packet loss. Our main focus is to minimize the size of the communication overhead required to authenticate the packets. Our approach is to encode the hash values and the signatures with Rabins Information Dispersal Algorithm (IDA) to construct an authentication scheme that amortizes a single signature operation over multiple packets. This strategy is especially efficient in terms of space overhead, because just the essential elements needed for authentication (i.e., one hash per packet and one signature per group of packets) are used in conjunction with an erasure code that is space optimal. To evaluate the performance of our scheme, we compare our technique with four other previously proposed schemes using analytical and empirical results. Two different bursty loss models are considered in the analyses.

Constructing fair-exchange protocols for E-commerce via distributed computation of RSA signatures

Applications such as e-commerce payment protocols, electronic contract signing, and certified e-mail delivery require that fair exchange be assured. A fair-exchange protocol allows two parties to exchange items in a fair way so that either each party gets the others item, or neither party does. We describe a novel method of constructing very efficient fair-exchange protocols by distributing the computation of RSA signatures. Specifically, we employ multisignatures based on the RSA-signature scheme. To date, the vast majority of fair-exchange protocols require the use of zero-knowledge proofs, which is the most computationally intensive part of the exchange protocol. Using the intrinsic features of our multisignature model, we construct protocols that require no zero-knowledge proofs in the exchange protocol. Use of zero-knowledge proofs is needed only in the protocol setup phase--this is a one-time cost. Furthermore, our scheme uses multisignatures that are compatible with the underlying standard (single-signer) signature scheme, which makes it possible to readily integrate the fair-exchange feature with existing e-commerce systems.

An analysis of a class of neural networks for solving linear programming problems

A class of neural networks that solve linear programming problems is analyzed. The neural networks considered are modeled by dynamic gradient systems that are constructed using a parametric family of exact (nondifferentiable) penalty functions. It is proved that for a given linear programming problem and sufficiently large penalty parameters, any trajectory of the neural network converges in finite time to its solution set. For the analysis, Lyapunov-type theorems are developed for finite time convergence of nonsmooth sliding mode dynamic systems to invariant sets. The results are illustrated via numerical simulation examples.

Analysis of a class of distributed asynchronous power control algorithms for cellular wireless systems

In cellular wireless communication systems, uplink power control is needed to provide each mobile user with an acceptable signal to interference ratio (SIR) while simultaneously minimizing transmit power levels. We consider a class of distributed asynchronous power control algorithms based on the schemes used in IS-95 inner loop power control. Each users received SIR is measured (using possibly outdated information) and compared to a threshold, and a single control bit is then sent to the user, indicating whether its power level should be increased or decreased. The SIR measurements and power updates do not require synchronization. We show that under certain conditions, this class of algorithms is stable and converges to a region around the optimal power assignment. We characterize this region and show that it can be made as small as desired by choosing the algorithm parameters appropriately. For an appropriate choice of algorithm parameters, we show that convergence occurs in a finite number of iterations and derive an upper bound. To illustrate our general results, we apply them to systems with fixed base station assignment, dynamic base station assignment, and macrodiversity. Finally, we give an example to illustrate the algorithms robustness to errors in the power control commands.

Automated fault diagnosis using a discrete event systems framework

Automated fault diagnosis for a complex system is often a very difficult task. Before proceeding with fault diagnosis, we need to make sure that the given sensor configuration has the capability of assisting the diagnostician perform the fault diagnosis in an efficient manner. In this paper, we present some results on the testability of a system whose fault behavior is modeled by a nondeterministic automaton. We discuss the issues pertaining to testability such as optimal sensor configuration and the infimal partition of the fault space. We also present a manufacturing process example to illustrate the application of the results presented in the paper.<<ETX>>