Covert Communication over Classical-Quantum Channels

The square root law (SRL) is the fundamental limit of covert communication over classical memoryless channels (with a classical adversary) and quantum lossy-noisy bosonic channels (with a quantum-powerful adversary). The SRL states that $\mathcal{O}(\sqrt{n})$ covert bits, but no more, can be reliably transmitted in $n$ channel uses with $\mathcal{O}(\sqrt{n})$ bits of secret pre-shared between the communicating parties. Here we investigate covert communication over general memoryless classical-quantum (cq) channels with fixed finite-size input alphabets, and show that the SRL governs covert communications in typical scenarios. %This demonstrates that the SRL is achievable over any quantum communications channel using a product-state transmission strategy, where the transmitted symbols in every channel use are drawn from a fixed finite-size alphabet. We characterize the optimal constants in front of $\sqrt{n}$ for the reliably communicated covert bits, as well as for the number of the pre-shared secret bits consumed. We assume a quantum-powerful adversary that can perform an arbitrary joint (entangling) measurement on all $n$ channel uses. However, we analyze the legitimate receiver that is able to employ a joint measurement as well as one that is restricted to performing a sequence of measurements on each of $n$ channel uses (product measurement). We also evaluate the scenarios where covert communication is not governed by the SRL

Distribution of the Loss Period for Some Queues in Continuous and Discrete Time

For soft real-time communication systems, packet loss due to excessive delay rather than average delay becomes the critical performance issue. While most previous studies of realtime systems measure loss as a time-average fraction of excessively delayed packets, this paper characterizes the stochastic properties of time-out loss periods for infinite queues, that is, uninterrupted intervals during which the virtual wait is at or above some fixed threshold. We present analytic expressions and numerical techniques for computing both "time-based" measures such as the distribution of periods during which all arriving packets are lost due to excessive delay as well as "packet-based" measures such as the distribution of the number of consecutively lost packets and the number of successful packets between such periods of loss. Both continuous and discrete-time systems are examined. It is shown that the assumption of random packet loss severely underestimates the number of consecutively lost pa..

Loss Correlation for Queues with Bursty Input Streams

The loss probability of a queueing system provides, in many cases, insufficient information for performance evaluation, for example, of data link layer protocols and applications with forward error correction. This paper evaluates and characterizes the correlation between packet losses for two queueing systems in discrete time that are motivated by BISDN applications. The first, a twoclass discrete-time queueing system, approximates the output queue of an ATM switch. The queue serves periodic foreground traffic and random background traffic. The background traffic is modeled as i.i.d. batches of arbitrary distribution. It is shown that the conditional loss probability (CLP) is independent of the buffer size if the buffer size is at least as large as the period of the foreground traffic. Example calculations indicate that losses occur essentially randomly as long as the foreground traffic uses less than 10% of the channel capacity. The second analysis derives the CLP seen by a selected ..

Modeling TCP Reno Performance: A Simple Model and Its Empirical Validation

Abstract—The steady-state performance of a bulk transfer TCP flow (i.e., a flow with a large amount of data to send, such as FTP transfers) may be characterized by the send rate, which is the amount of data sent by the sender in unit time. In this paper we develop a simple analytic characterization of the steady-state send rate as a function of loss rate and round trip time (RTT) for a bulk transfer TCP flow. Unlike the models in [7]–[9], and [12], our model captures not only the behavior of the fast retransmit mechanism but also the effect of the time-out mechanism. Our measurements suggest that this latter behavior is important from a modeling perspective, as almost all of our TCP traces contained more time-out events than fast retransmit events. Our measurements demonstrate that our model is able to more accurately predict TCP send rate and is accurate over a wider range of loss rates. We also present a simple extension of our model to compute the throughput of a bulk transfer TCP flow, which is defined as the amount of data received by the receiver in unit time. Index Terms—Empirical validation, modeling, retransmission timeouts, TCP