Channel Coherence in the Low-SNR Regime

Channel capacity in the limit of vanishing signal-to-noise ratio (SNR) per degree of freedom is known to be linear in SNR for fading and nonfading channels, regardless of channel state information at the receiver (CSIR). It has recently been shown that the significant engineering difference between the coherent and the noncoherent fading channels, including the requirement of peaky signaling and the resulting spectral efficiency, is determined by how the capacity limit is approached as SNR tends to zero, or in other words, the sublinear term in the capacity expression. In this paper, we show that this sublinear term is determined by the channel coherence level, which we define to quantify the relation between the SNR and the channel coherence time. This allows us to trace a continuum between the case with perfect CSIR and the case with no CSIR at all. Using this approach, we also evaluate the performance of suboptimal training schemes     

Resilient Network Coding in the Presence of Byzantine Adversaries

Network coding substantially increases network throughput. But since it involves mixing of information inside the network, a single corrupted packet generated by a malicious node can end up contaminating all the information reaching a destination, preventing decoding. This paper introduces distributed polynomial-time rate-optimal network codes that work in the presence of Byzantine nodes. We present algorithms that target adversaries with different attacking capabilities. When the adversary can eavesdrop on all links and jam links, our first algorithm achieves a rate of , where is the network capacity. In contrast, when the adversary has limited eavesdropping capabilities, we provide algorithms that achieve the higher rate of . Our algorithms attain the optimal rate given the strength of the adversary. They are information-theoretically secure. They operate in a distributed manner, assume no knowledge of the topology, and can be designed and implemented in polynomial time. Furthermore, only the source and destination need to be modified; nonmalicious nodes inside the network are oblivious to the presence of adversaries and implement a classical distributed network code. Finally, our algorithms work over wired and wireless networks.     

Generalized loop-back recovery in optical mesh networks

Current means of providing loop-back recovery, which is widely used in SONET, rely on ring topologies, or on overlaying logical ring topologies upon physical meshes. Loop-back is desirable to provide rapid preplanned recovery of link or node failures in a bandwidth-efficient distributed manner. We introduce generalized loop-back, a novel scheme for performing loop-back in optical mesh networks. We present an algorithm to perform recovery for link failure and one to perform generalized loop-back recovery for node failure. We illustrate the operation of both algorithms, prove their validity, and present a network management protocol algorithm, which enables distributed operation for link or node failure. We present three different applications of generalized loop-back. First, we present heuristic algorithms for selecting recovery graphs, which maintain short maximum and average lengths of recovery paths. Second, we present WDM-based loop-back recovery for optical networks where wavelengths are used to back up other wavelengths. We compare, for WDM-based loop-back, the operation of generalized loop-back operation with known ring-based ways of providing loop-back recovery over mesh networks. Finally, we introduce the use of generalized loop-back to provide recovery in a way that allows dynamic choice of routes over preplanned directions     

A distributed scheme for achieving energy-delay tradeoffs with multiple service classes over a dynamically varying network

We consider a dynamical probabilistic traffic model for the number of users transmitting at any time. This model captures both user mobility and traffic burstiness. Moreover, we assume no centralized controller, such as a scheduler, is available. When multiple users transmit simultaneously, multiple-access interference (MAI) affects throughput considerably. Most queue control schemes assume individual users know the states of their own queues (local queue information) along with the states of other users queues (shared queue information) and address issues of scheduling; but this sharing of information may be onerous in a practical system. While shared queue information has recently been shown (Me/spl acute/dard et al., 2004) not to affect the capacity of such systems, it has a considerable impact on delay. We introduce a scheme, where for each user, a bit of shared queue information specifies whether its queue length is above or below a threshold. Our scheme relies on two different service classes implemented through a superposition coding scheme (first proposed with Me/spl acute/dard and Goldsmith, 1999, further studied and expanded with Me/spl acute/dard et al., 2004). The first class experiences no delay due to multiple-access interference, while the second class requires retransmissions when such an event occurs. We show how our scheme affords an energy-delay tradeoff. Moreover, when configured properly, our scheme can attain boundary points of the region corresponding to minimum energy with no shared queue information for zero delay along with minimum energy subject to system stability. We derive bounds on the performance of the multiple-access system using our proposed scheme by introducing Lyapunov function bounds in a manner similar to Bertsimas et al., 2001.     

Bandwidth scaling for fading multipath channels

We show that very large bandwidths on fading multipath channels cannot be effectively utilized by spread-spectrum systems that (in a particular sense) spread the available power uniformly over both time and frequency. The approach is to express the input process as an expansion in an orthonormal set of functions each localized in time and frequency. The fourth moment of each coefficient in this expansion is then uniformly constrained. We show that such a constraint forces the mutual information to 0 inversely with increasing bandwidth. Simply constraining the second moment of these coefficients does not achieve this effect. The results suggest strongly that conventional direct-sequence code-division multiple-access (CDMA) systems do not scale well to extremely large bandwidths. To illustrate how the interplay between channel estimation and symbol detection affects capacity, we present results for a specific channel and CDMA signaling scheme     

Minimum-cost multicast over coded packet networks

We consider the problem of establishing minimum-cost multicast connections over coded packet networks, i.e., packet networks where the contents of outgoing packets are arbitrary, causal functions of the contents of received packets. We consider both wireline and wireless packet networks as well as both static multicast (where membership of the multicast group remains constant for the duration of the connection) and dynamic multicast (where membership of the multicast group changes in time, with nodes joining and leaving the group). For static multicast, we reduce the problem to a polynomial-time solvable optimization problem, and we present decentralized algorithms for solving it. These algorithms, when coupled with existing decentralized schemes for constructing network codes, yield a fully decentralized approach for achieving minimum-cost multicast. By contrast, establishing minimum-cost static multicast connections over routed packet networks is a very difficult problem even using centralized computation, except in the special cases of unicast and broadcast connections. For dynamic multicast, we reduce the problem to a dynamic programming problem and apply the theory of dynamic programming to suggest how it may be solved.     

Codecast: a network-coding-based ad hoc multicast protocol

In this article we present CodeCast, a network-coding-based ad hoc multicast protocol. CodeCast is especially well-suited for multimedia applications with low-loss, low-latency constraints such as audio/video streaming. The key ingredient of CodeCast is random network coding, which transparently implements both localized loss recovery and path diversity with very low overhead. Simulation results show that in a typical setting, CodeCast yields a nearly 100 percent delivery ratio, as compared to a 94 percent delivery ratio by traditional multicast. More importantly, the overhead is reduced by as much as 50 percent     

Chemical micropatterning of polycarbonate for site-specific peptide immobilization and biomolecular interactions

Polycarbonate (PC) is a useful substrate for the preparation of microfluidic devices. Recently, its utility in bioanalysis has attracted much attention owing to the possibility of using compact discs as platforms for the high-throughput analysis of biomolecular interactions. In this article we report a novel method for the chemical micropatterning of polycarbonate based on the printing of functionalized silica nanoparticles. The semicarbazide groups present on the surface of the nanoparticles were used for the site-specific semicarbazone ligation of unprotected peptides derivatized by an alpha-oxoaldehyde group. The peptide micropatterns permitted the specific capture of antibodies. We report also the characterization of micropatterns on PC by using a wide-field optical imaging technique called Sarfus; this allows the detection of nm-thick films by using nonreflecting PC substrates and an optical microscope working with reflected differential interference contrast. The method described here is an easy way to modify polycarbonate surfaces for biomolecular interaction studies and should stimulate the use of PC for developing plastic biosensors.     

Binary adaptive coded pilot symbol assisted modulation over Rayleigh fading channels without feedback

Pilot symbol assisted modulation (PSAM) is a standard approach for transceiver design for time-varying channels, with channel estimates obtained from pilot symbols being employed for coherent demodulation of the data symbols. In this paper, we show that PSAM schemes can be improved by adapting the coded modulation strategy at the sender to the quality of the channel measurement at the receiver, without requiring any channel feedback from the receiver. We consider performance in terms of achievable rate for binary signaling schemes. The transmitter employs interleaved codes, with data symbols coded according to their distance from the nearest pilot symbols. Symbols far away from pilot symbols encounter poorer channel measurements at the receiver and are therefore coded with lower rate codes, while symbols close to pilot symbols benefit from recent channel measurements and are coded with higher rate codes. The performance benefits from this approach are quantified in the context of binary signaling over time-varying Rayleigh fading channels described by a Gauss-Markov model. The spacing of the pilot symbols is optimized to maximize the mutual information between input and output in this setting. Causal and noncausal channel estimators of varying complexity and delay are considered. It is shown that, by appropriate optimization for the spacing between consecutive pilot symbols, the adaptive coding techniques proposed can improve achievable rate, without any feedback from the receiver to the sender. Moreover, channel estimation based on the two closest pilot symbols is generally close to optimal.     

Capacity of nearly decomposable Markovian fading channels under asymmetric receiver-sender side information

We investigate the following issue: if fast fades are Markovian and known at the receiver, while the transmitter has only a coarse quantization of the fading process, what capacity penalty comes from having the transmitter act on the current coarse quantization alone? For time-varying channels which experience rapid time variations, sender and receiver typically have asymmetric channel side information. To avoid the expense of providing, through feedback, detailed channel side information to the sender, the receiver offers the sender only a coarse, generally time-averaged, representation of the state of the channel, which we term slow variations. Thus, the receiver tracks the fast variations of the channel (and the slow ones perforce) while the sender receives feedback only about the slow variations. While the fast variations (micro-states) remain Markovian, the slow variations (macro-states) are not. We compute an approximate channel capacity in the following sense: each rate smaller than the "approximate" capacity, computed using results by Caire and Shamai, can be achieved for sufficiently large separation between the time scales for the slow and fast fades. The difference between the true capacity and the approximate capacity is O(/spl epsi/log/sup 2/(/spl epsi/)log(-log(/spl epsi/))), where /spl epsi/ is the ratio between the speed of variation of the channel in the macro- and micro-states. The approximate capacity is computed by power allocation between the slowly varying states using appropriate water filling.