In this paper, a many-sources large deviations principle (LDP) for the transient workload of a multiqueue single-server system is established where the service rates are chosen from a compact, convex, and coordinate-convex rate region and where the service discipline is the max-weight policy. Under the assumption that the arrival processes satisfy a many-sources LDP, this is accomplished by employing Garcia's extended contraction principle that is applicable to quasi-continuous mappings. For the traditional single-server queue (simplex rate-region), an LDP for the stationary workload is also established under the additional requirements that the scheduling policy be work-conserving and that the arrival processes satisfy certain mixing conditions. The LDP results can be used to calculate asymptotic buffer overflow probabilities accounting for the multiplexing gain, e.g., when the arrival process is an average of i.i.d. processes. The rate function for the stationary workload is expressed in term of the rate functions of the finite-horizon workloads when the arrival processes have i.i.d. increments.

This work analyzes the high-SNR asymptotic error performance of outage-limited communications with fading, where the number of bits that arrive at the transmitter during any timeslot is random but the delivery of bits at the receiver must adhere to a strict delay limitation. Specifically, bit errors are caused by erroneous decoding at the receiver or violation of the strict delay constraint. Under certain scaling of the statistics of the bit-arrival process with SNR, this paper shows that the optimal decay behavior of the asymptotic total probability of bit error depends on how fast the burstiness of the source scales down with SNR. If the source burstiness scales down too slowly, the total probability of error is asymptotically dominated by delay-violation events. On the other hand, if the source burstiness scales down too quickly, the total probability of error is asymptotically dominated by channel-error events. However, at the proper scaling, where the burstiness scales linearly with${{ 1}\over { \sqrt {\log {\rm SNR} }}}$and at the optimal coding duration and transmission rate, the occurrences of channel errors and delay-violation errors are asymptotically balanced. In this latter case, the optimal exponent of the total probability of error reveals a tradeoff that addresses the question of how much of the allowable time and rate should be used for gaining reliability over the channel and how much for accommodating the burstiness with delay constraints.

This paper considers the problem of optimal server allocation in a time-slotted system with N statistically symmetric queues and K servers when the arrivals and channels are stochastic and time-varying. In this setting, we identify two classes of "desirable" policies with potentially competing goals of maximizing instantaneous throughput versus balancing the load. Via an example, we show that these goals, in general, can be incompatible, implying an empty intersection between the two classes of policies. On the other hand, we establish the existence of a policy achieving both goals when the connectivities between each queue and each server are random and either "ON" or "OFF". We use dynamic programming (DP) and properties of the value function to establish the delay optimality of a policy, which, at each time-slot, simultaneously maximizes the instantaneous throughput and balances the queues.

This work investigates the asymptotic error performance of outage-limited communications in cooperative wireless relay networks, with fading that is quasi-static, with an information-arrival process that is stochastic and bursty, and with bits that have a strictly limited lifespan. Employing large- deviation techniques, we analyze the probability of bit error where such errors are due to both erroneous decoding as well as due to delay violation. We derive a tradeoff between, on one hand, the optimal negative SNR exponent of the total probability of error, and on the other hand, the ratio of the average bit- arrival rate to the ergodic capacity of the channel. This is for the case of the orthogonal amplify-and-forward protocol, constant system loading, many flows and asymptotically high values of SNR. The tradeoff holds for any delay limitation. As a practical consequence, the tradeoff tells us how to better balance the effects of channel atypicality (outage) and burstiness atypicality, by proper choice of transmission rate and by optimizing the cooperative cluster size, i.e., limiting the cooperation to a specific subset of the cooperative users.

Multiple antennas at the transmitters and receivers in a multiple access channel (MAC) can provide simultaneous diversity, spatial multiplexing, and space-division multiple access gains. The fundamental tradeoff in the asymptotically large SNR regime is shown by Tse et al. (2004). On the other hand, MAC scheduling can provide a statistical-multiplexing gain to improve the delay performance as shown by Bertsimas et al. (1998) and Stolyar and Ramanan (2001). In this paper, we formulate and analytically derive bounds on the optimal operating point for MIMO-MAC channel for bursty sources with delay constraints. Our system model brings together the four types of gains: diversity, spatial multiplexing, space-division multiple-access, and statistical-multiplexing gains. Our objective is to minimize the end-to-end performance as defined by the delay bound violation probability as well as the channel decoding error probability. We And the optimal diversity gain and rate region in which the system should operate. As an example, we illustrate our technique and the optimal operating point for the case of a compound Poisson source. In addition, we note an interesting interplay between the intensity of the traffic and resource pooling with regard to both multiple-access and statistical-multiplexing gains.

We consider a system with a bursty and delay-sensitive data source to be transmitted over a constant-rate MIMO channel with no CSI information at the transmitter. Given the diversity-multiplexing tradeoff region of the MIMO channel, we find the optimal multiplexing rate that optimizes the end-to-end loss probability. Based on the effective bandwidth model of the source, we present an analytical tradeoff between the error probability over the MIMO channel and the probability of delay violation. We illustrate the optimal operating points for i.i.d. sources and Markov-modulated sources and show the relation between sources burstiness, delay bound, and optimal multiplexing rate