Drug repurposing requires distinguishing established drug class targets from novel molecule-specific mechanisms and rapidly derisking their therapeutic potential in a time-critical manner, particularly in a pandemic scenario. In response to the challenge to rapidly identify treatment options for COVID-19, several studies reported that statins, as a drug class, reduce mortality in these patients. However, it is unknown if different statins exhibit consistent function or may have varying therapeutic benefit. A Bayesian network tool was used to predict drugs that shift the host transcriptomic response to SARS-CoV-2 infection towards a healthy state. Drugs were predicted using 14 RNA-sequencing datasets from 72 autopsy tissues and 465 COVID-19 patient samples or from cultured human cells and organoids infected with SARS-CoV-2. Top drug predictions included statins, which were then assessed using electronic medical records containing over 4,000 COVID-19 patients on statins to determine mortality risk in patients prescribed specific statins versus untreated matched controls. The same drugs were tested in Vero E6 cells infected with SARS-CoV-2 and human endothelial cells infected with a related OC43 coronavirus. Simvastatin was among the most highly predicted compounds (14/14 datasets) and five other statins, including atorvastatin, were predicted to be active in > 50% of analyses. Analysis of the clinical database revealed that reduced mortality risk was only observed in COVID-19 patients prescribed a subset of statins, including simvastatin and atorvastatin. In vitro testing of SARS-CoV-2 infected cells revealed simvastatin to be a potent direct inhibitor whereas most other statins were less effective. Simvastatin also inhibited OC43 infection and reduced cytokine production in endothelial cells. Statins may differ in their ability to sustain the lives of COVID-19 patients despite having a shared drug target and lipid-modifying mechanism of action. These findings highlight the value of target-agnostic drug prediction coupled with patient databases to identify and clinically evaluate non-obvious mechanisms and derisk and accelerate drug repurposing opportunities.

Motivation: Multiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full-term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy-related pathologies including preterm birth and preeclampsia. Results: We performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified. Availability and implementation: Datasets and scripts for reproduction of results are available through: https://nalab.stanford.edu/multiomics-pregnancy/. Supplementary information: Supplementary data are available at Bioinformatics online.

We study a multihop “virtual” full-duplex relay channel as a special case of a general multiple multicast relay network. For such a channel, quantize-map-and-forward (QMF) [and its generalization of noisy network coding (NNC) and short message NNC] achieves the cut-set upper bound within a constant additive gap, where the gap grows linearly with the number of relay stages K. This gap, however, may not be acceptable for practical communication systems with multihop transmissions (e.g., a wireless backhaul operating at high frequencies). Recently, we improved the capacity scaling by using a forward sliding-window (SW) decoding and by optimizing the quantization level at each relay, obtaining the gap that grows logarithmically as log K. Furthermore, the improved scheme has lower decoding complexity and delay than the general QMF and NNC approaches. In this paper, we further improve the performance by presenting a mixed scheme in which each relay can perform either decode-and-forward (DF) or the improved QMF (with SW decoding) and can choose to perform rate-splitting to enable partial interference cancellation. In general, the optimization of the relay DF/QMF configuration is combinatorial. Nevertheless, we provide that a simple greedy algorithm finds an optimal configuration under some practically reasonable assumptions. We derive an achievable rate that is easily computable and show that the proposed mixed scheme outperforms the QMF-only schemes. We demonstrate that the performance improvement increases with K, which indicates that the mixed scheme is indeed beneficial for multihop transmission.

A method of constructing rate-compatible polar codes that are capacity achieving at multiple code rates with low-complexity sequential decoders is presented. The underlying idea of the construction exploits certain common characteristics of polar codes that are optimized for a sequence of successively degraded channels. The proposed code consists of parallel concatenation of multiple polar codes with information-bit divider at the input of each polar encoder. Thus, it is referred to as parallel concatenated polar (PCP) codes. A lower-rate PCP code is simply constructed by adding more constituent polar codes, which enables incremental retransmissions at different rates in order to adapt to channel conditions. Due to the length limitation of polar codes, the PCP code can only support a restricted set of rates that is characterized by the size of the kernel when conventional polar codes are used. To overcome this limitation, punctured polar codes, which provide more flexibility on blocklength by controlling a puncturing fraction, are considered as constituent codes. The existence of capacity-achieving punctured polar codes for any given puncturing fraction is proven. Using such punctured polar codes as constituent codes, it is shown that the proposed PCP code is capacity achieving for an arbitrary sequence of rates and for any class of degraded channels.

We present a method of constructing rate-compatible polar codes that are capacity-achieving with low-complexity sequential decoders. The proposed code construction allows for incremental retransmissions at different rates in order to adapt to channel conditions. The main idea of the construction exploits certain common characteristics of polar codes that are optimized for a sequence of degraded channels. The proposed approach allows for an optimized polar code to be used at every transmission thereby achieving capacity. Due to the length limitation of conventional polar codes, the proposed construction can only support a restricted set of rates that is characterized by the size of the kernel when conventional polar codes are used. We thus consider punctured polar codes which provide more flexibility on block length by controlling a puncturing fraction. We show the existence of capacity-achieving punctured polar codes for any given puncturing fraction. Using punctured polar codes as constituent codes, we show that the proposed rate-compatible polar code is capacity-achieving for an arbitrary sequence of rates and for any class of degraded channels.

In this paper, we present a cooperative relaying strategy for half-duplex multihop relay networks. This scheme consists of three parts: 1) relay selection to yield a layered relay network; 2) group successive relaying that establishes a relay schedule to efficiently exploit half-duplex relays; and 3) a cooperative relaying scheme named short message noisy network coding with sliding-window decoding (SNNC-SW) that outperforms other state-of-the-art information theoretical schemes with lower decoding complexity and delay. We derive an achievable rate region of the proposed SNNC-SW scheme and attain a closed-form rate expression in the asymptotic case for several network models of interests. We then focus on the first part of our relaying strategy regarding efficient relay selection. We develop interference-harnessing routing that exploits the fact that in SNNC-SW, interference is treated as a useful signal. We show that, due to the efficient treatment of interference, this scheme can outperform routing schemes that deploy store-and-forward, a solution previously proposed for practical wireless multihop networks. Finally, we develop a low-complexity successive decoder of our scheme (implemented by a conventional MIMO decoder), which is a solution that can readily be implemented in practice. It is shown that also this practical scheme provides a significant gain over routing (based on store-and-forward) and the performance gap increases as the network becomes denser.

In this paper we present a novel transmission scheme for wireless multihop backhaul networks. The scheme consists of group successive relaying that efficiently exploits half-duplex relays and a coding scheme that improves quantize-map-and- forward (QMF). We derive an achievable rate region of the proposed scheme and attain a closed-form expression in the asymptotic case for several network models of interests. It is shown that the proposed scheme outperforms the multihop routing, which is a solution currently proposed for wireless multihop backhaul networks. Furthermore, the performance gap increases as a network becomes denser. Based on the proposed scheme, we present energy-efficient routing referred to as energy- harvesting in which each node requires a lower transmission power to achieve a desired performance compared to other schemes.

We study a multihop “virtual” full-duplex relay channel as a special case of a general multiple multicast relay network. For such channel, quantize-map-and-forward (QMF) (or noisy network coding (NNC)) achieves the cut-set upper bound within a constant gap where the gap grows linearly with the number of relay stages K. However, this gap may not be negligible for the systems with multihop transmissions (i.e., a wireless backhaul operating at higher frequencies). We have recently attained an improved result to the capacity scaling where the gap grows logarithmically as logK, by using an optimal quantization at relays and by exploiting relays' messages (decoded in the previous time slot) as side-information. In this paper, we further improve the performance of this network by presenting a mixed scheme where each relay can perform either decode-and-forward (DF) or QMF with possibly rate-splitting. We derive an achievable rate and show that the proposed scheme outperforms the optimized QMF. Furthermore, we demonstrate that this performance improvement increases with K.

We introduce a multihop “virtual” full-duplex relay channel as a special case of a general multiple multicast relay network. For such network, quantize-map-and-forward (QMF) (or noisy network coding (NNC)) can achieve the cut-set upper bound within a constant gap where the gap grows linearly with the number of relay stages K. However, this gap may not be negligible for the systems with multihop transmissions (e.g., a power-limited wireless backhaul system operating at high frequencies). In this paper, we obtain an improved result to the capacity scaling where the gap grows logarithmically as log (K). This is achieved by using an optimal quantization at relays and by exploiting relays' messages (decoded in the previous time slot) as side-information at the destination. We further improve the performance of this network by presenting a mixed strategy where each relay can perform either decode-and-forward (DF) or QMF with possibly rate-splitting.

We study the diversity-multiplexing tradeoff (DMT) for the slow fading interference channel with a relay (ICR). We derive four inner bounds on the DMT region: the first is based on the compress-and-forward (CF) relaying scheme, the second is based on the decode-and-forward (DF) relaying scheme, and the last two bounds are based on the half-duplex (HD) and full-duplex (FD) amplify-and-forward (AF) schemes. For the CF and DF schemes, we find conditions on the channel parameters and the multiplexing gains, under which the corresponding inner bound achieves the optimal DMT region. We also identify the cases in which the DMT region of the ICR corresponds to that of two parallel slow fading relay channels, implying that interference does not decrease the DMT for each pair, and that a single relay can be DMT-optimal for two pairs simultaneously. For the HD-AF scheme, we derive conditions on the channel coefficients under which the proposed scheme achieves the optimal DMT for the AF-based relay channel. Finally, we identify the conditions under which adding a relay strictly enlarges the DMT region relative to the interference channel without a relay.

We study the diversity-multiplexing tradeoff (DMT) for the slow fading interference channel with a relay (ICR). We first derive an outer bound on the DMT based on the cut-set bound. We then derive two inner bounds on the DMT: One is based on the compress-and-forward relaying scheme and the other is based on the decode-and-forward relaying scheme. We find conditions on the channel parameters and the multiplexing gains under which the proposed inner bounds achieve the optimal DMT. We also identify cases in which the DMT of the ICR is the same as two parallel fading relay channels, implying that interference does not decrease the DMT for each pair, and that a single relay can be DMT-optimal for two pairs simultaneously. Lastly, we identify conditions under which adding a relay strictly improves the DMT relative to the interference channel without a relay.

We study the discrete memoryless Z-interference channel where the transmitter of the pair that suffers from interference is cognitive. We first provide an outer bound on the capacity region of this channel. We then show that, when the channel of the transmitter–receiver pair that does not experience interference is deterministic and invertible, our proposed outer bound matches the best known inner bound. The obtained results imply that in the considered channel, superposition encoding at the noncognitive transmitter as well as Gel'fand–Pinsker encoding at the cognitive transmitter is needed in order to minimize the impact of interference. As a byproduct of the obtained capacity region, we obtain the capacity under the generalized Gel'fand–Pinsker setting where a transmitter–receiver pair communicates in the presence of interference noncausally known at the encoder.

The smallest network model that captures relaying in the presence of multiple communicating pairs causing interference to each other is the interference channel with a relay. In this paper, an achievable rate region for the interference channel with a relay is derived. Special cases of strong interference under which this region is the capacity region are presented. The results obtained demonstrate the benefits of interference forwarding at a relay. By forwarding interfering messages, the relay can improve their reception at unintended receivers and, thus, facilitate interference cancellation. We show that intentionally forwarding interfering messages can improve the achievable rates. The achievable rates and interference forwarding gains are also illustrated by numerical results in Gaussian channels. Finally, a sum-rate outer bound to the capacity region of the Gaussian interference channel with a relay is derived and compared with the achievable rate region. The cut-set bound for this channel is also derived and shown to be much looser than the new sum-rate outer bound.

In the simplest relaying strategy, a network node amplifies and forwards a received signal over a wireless channel. Multihop amplify-and-forward allows for a (noisy) linear combination of signals simultaneously sent from multiple sources to be propagated through the network over multiple layers of relays. The performance of multihop amplify-and-forward is limited by noise propagated to the destination over multiple hops, and we expect this strategy to perform well only in high SNR. In this paper, this intuition is formalized and high-SNR conditions under which multihop amplify-and-forward approaches capacity in a layered relay network are determined. By relating the received signal power and the received power of the propagated noise at the nodes, the rate achievable with multihop amplify-and-forward is determined. In particular, when all received powers are lower bounded by$1/\delta $, the noise power propagated to the destination over$L$layers is of the order$L\delta $. The result demonstrates that multihop amplify-and-forward approaches the cut-set bound as received powers at relays increase. As all powers in the network increase at the same rate, the multihop amplify-and-forward rate and the upper bound are within a gap that is independent of channel gains. This gap grows linearly with the number of nodes.

We study a special class of the cognitive radio channel in which the receiver of the cognitive pair does not suffer interference from the primary user. Previously developed general encoding schemes for this channel are complex as they attempt to cope with arbitrary channel conditions, which leads to rate regions that are difficult to evaluate. The focus of our work is to derive simple rate regions that are easily computable, thereby providing more insights into achievable rates and good coding strategies under different channel conditions. We first present several explicit achievable regions for the general discrete memoryless case. We also present an improved outer bound on the capacity region for the case of high interference. We then extend these regions to Gaussian channels. With a simple outer bound we establish a new capacity region in the high-interference regime. Lastly, we provide numerical comparisons between the derived achievable rate regions and the outer bounds.

We derive upper and lower bounds on the diversity-multiplexing tradeoff of the multiple-input multiple-output interference channel with a relay. The upper bound is derived from the cut-set bound and the lower bound is obtained by performing compress-and-forward at the relay. Based on the obtained bounds, we derive conditions under which the two bounds coincide, resulting in the optimal diversity-multiplexing tradeoff.

Achievable rates with amplify-and-forward (AF) and decode-and-forward (DF) cooperative strategies are examined for relay networks. Motivated by sensor network applications, power-constrained networks with large bandwidth resources and a large number of nodes are considered. It is shown that AF strategies do not necessarily benefit from the available bandwidth. Rather, transmitting in the optimum AF bandwidth allows the network to operate in the linear regime where the achieved rate increases linearly with the available network power. The optimum power allocation among the AF relays, shown to be a form of maximal ratio combining, indicates the favorable relay positions. Orthogonal node transmissions are also examined. While the same optimum bandwidth result still holds, the relay power allocation in this case can be viewed as a form of water-filling. In contrast, the DF strategy will optimally operate in the wideband regime and is shown to require a different choice of relays. Thus, in a large scale network, the choice of a coding strategy goes beyond determining a coding scheme at a node; it also determines the operating bandwidth, as well as the set of relays and best distribution of the relay power.

We study the discrete memoryless Z-interference channel (ZIC) where the transmitter of the pair that suffers from interference is cognitive. We first provide upper and lower bounds on the capacity of this channel. We then show that, when the channel of the transmitter-receiver pair that does not face interference is noiseless, the two bounds coincide and therefore define the capacity region. The obtained results imply that, unlike in the Gaussian cognitive ZIC, in the considered channel superposition encoding at the non-cognitive transmitter as well as Gel'fand-Pinsker encoding at the cognitive transmitter are needed in order to minimize the impact of interference. As a byproduct of the obtained capacity region, we obtain the capacity result for a generalized Gel'fand-Pinsker problem.

Cognitive radios hold tremendous promise for increasing spectral efficiency in wireless systems. This paper surveys the fundamental capacity limits and associated transmission techniques for different wireless network design paradigms based on this promising technology. These paradigms are unified by the definition of a cognitive radio as an intelligent wireless communication device that exploits side information about its environment to improve spectrum utilization. This side information typically comprises knowledge about the activity, channels, codebooks, and/or messages of other nodes with which the cognitive node shares the spectrum. Based on the nature of the available side information as well asa priorirules about spectrum usage, cognitive radio systems seek to underlay, overlay, or interweave the cognitive radios' signals with the transmissions of noncognitive nodes. We provide a comprehensive summary of the known capacity characterizations in terms of upper and lower bounds for each of these three approaches. The increase in system degrees of freedom obtained through cognitive radios is also illuminated. This information-theoretic survey provides guidelines for the spectral efficiency gains possible through cognitive radios, as well as practical design ideas to mitigate the coexistence challenges in today's crowded spectrum.

We study communication in networks with multiple source-destination pairs and relays. In such networks, the channel output at any destination receiver consists of both the desired signal and interference. In this setting the relay can help forward the desired message of a user to the destination receiver, or help forward interference to a receiver to improve its ability to cancel the interference. Focusing on the impact of interference forwarding, we define a new relay-interferer channel (RIC) model, which serves as the basic building block for the study of interference in multiuser networks. Using the RIC we show that correlation between the codebooks of the relay and the interferer (e.g. superposition codebooks) is essential for obtaining performance benefits from interference forwarding. We conclude that in order to achieve rate gains from relaying interference using the decode-and-forward strategy, a superposition codebook is required. Otherwise, this relay strategy has the same rate as interference cancellation at the receiver. We also conclude that compress-and-forward is not useful for forwarding interference and has no better performance than just treating interference as noise at the decoder.

Capacity gains due to relaying in wireless networks with multiple source-destination pairs are analyzed. A two- source, two-receiver network with the relay is considered. The focus is on the scenario in which, due to channel conditions, the relay can observe the signal from only one source. The relay can thus help the intended receiver of this message, via message forwarding, to decode it. In addition, the relay can simultaneously help the unintended receiver subtract the interference associated with this message. We call the latter strategy interference forwarding. An achievable rate region employing decode-and-forward (that simultaneously does message and interference forwarding) at the relay is derived and analyzed. This strategy is shown to achieve the capacity region under certain conditions. Our results demonstrate that the relay can help both receivers, despite the fact that it forwards only the message intended for one of them. This applies in general to communications in the presence of an interferer transmitting at any arbitrary rate. Interference forwarding improves reception of interfering signals at the receivers. This facilitates decoding of the unwanted messages and eliminating the resulting interference. Therefore, in networks with multiple source-destination pairs, in addition to relaying messages, interference forwarding may also be employed to help in combating interference.

We consider relaying strategies in networks with multiple source-destination pairs and possibly additional outside sources of interference. We study these networks in the discrete, memoryless setup, and focus on relaying strategies based on forwarding the interference. In particular, the relay encodes the interference signal so as to make it easier for the receiver to remove it. The objective is to help receivers with weak interference by making the interference strong enough so that these receivers are able to cancel it completely. Our proposed approach is a combination of ideas from decode-and-forward (DF) and/or estimate-and-forward (EF) but applied to the interfering signal rather than the desired signal. When based only on DF, the relay first decodes (part of) the interfering signal it wants to enhance. It then encodes the interference in such a way as to increase the interference at the assisted receiver. The rate of the relayed interference is not limited by the rate from the relay to the original destination of the forwarded message, thus, interference cancellation is not a by-product of enhancing the desired information at its intended destination, but a goal in itself. We call this method interference-forwarding (IF). IF can also be based on EF where, instead of forwarding the exact interfering signal, the relay simply sends a compressed version of it to the assisted receiver. Rate increase can thus be obtained even if the signal received at the relay is independent of the desired message and consists only of interference and noise.

We studyinformation-theoretic securityfor discrete memorylessinterferenceandbroadcastchannels with independent confidential messages sent to two receivers. Confidential messages are transmitted to their respective receivers while ensuring mutual information-theoretic secrecy. That is, each receiver is kept in total ignorance with respect to the message intended for the other receiver. The secrecy level is measured by the equivocation rate at the eavesdropping receiver. In this paper, we present inner and outer bounds on secrecy capacity regions for these two communication systems. The derived outer bounds have an identical mutual information expression that applies to both channel models. The difference is in the input distributions over which the expression is optimized. The inner bound rate regions are achieved byrandom binningtechniques. For the broadcast channel, adouble-binningcoding scheme allows for both joint encoding and preserving of confidentiality. Furthermore, we show that, for a special case of the interference channel, referred to as theswitchchannel, derived bounds meet. Finally, we describe several transmission schemes for Gaussian interference channels and derive their achievable rate regions while ensuring mutual information-theoretic secrecy. An encoding scheme in which transmitters dedicate some of their power to createartificial noiseis proposed and shown to outperform both time-sharing and simple multiplexed transmission of the confidential messages.

Relaying is a fundamental building block of wireless networks. Sophisticated relaying strategies at the physical layer have been developed for a single flow, but multiple flows are typically handled by time sharing the channel between the flows at the network level. In this paper, time-sharing when forwarding two data streams at the relay is compared to joint relaying and network coding that allows the relay to combine data streams. Two commonly occurring blocks in wireless networks with both unicast and multicast traffic are considered. It is shown that joint relaying and network coding can achieve gains and even double the throughput for certain channel conditions.

An achievable region, outer bounds and a capacity result are established for two-sender two-receiver interference channels with one cognitive transmitter. Specifically, we assume that one transmitter knows either the full or, more realistically, the partial message of the other transmitter due to its cognitive capabilities. The achievable region is obtained by a rate-splitting strategy, which generalizes prior strategies under both weak and strong interference conditions. The outer bounds are based on an extension of the Nair-El Gamal outer bound for the broadcast channel capacity. When only the partial message is known to the cognitive user, the capacity region in strong interference is established. In this regime, the interference is such that both receivers can decode both messages with no rate penalty.

Capacity regions are established for several two-sender, two-receiver channels with partial transmitter cooperation. First, the capacity regions are determined for compound multiple- access channels (MACs) with common information and compound MACs with conferencing. Next, two interference channel models are considered: an interference channel with common information (ICCI) and an interference channel with unidirectional cooperation (ICUC) in which the message sent by one of the encoders is known to the other encoder. The capacity regions of both of these channels are determined when there is strong interference, i.e., the interference is such that both receivers can decode all messages with no rate penalty. The resulting capacity regions coincide with the capacity region of the compound MAC with common information.

A multiple-access channel is considered in which messages from one encoder are confidential. Confidential messages are to be transmitted with perfect secrecy, as measured by equivocation at the other encoder. The upper bounds and the achievable rates for this communication situation are determined.

We compare the rates of one-shot and iterative conferencing in a cooperative Gaussian relay channel. The relay and receiver cooperate via a conference, as introduced by Willems, in which they exchange a series of communications over orthogonal links. Under one-shot conferencing, decode-and-forward (DF) is capacity-achieving when the relay has a strong channel. On the other hand, Wyner-Ziv compress-and-forward (CF) approaches the cut-set bound when the conference link capacity is large. To contrast with one-shot conferencing, we consider a two-round iterative conference scheme; it comprises CF in the first round, and DF in the second. When the relay has a weak channel, the iterative scheme is disadvantageous. However, when the relay channel is strong, iterative cooperation, with optimal allocation of conferencing resources, outperforms one-shot cooperation provided that the conference link capacity is large. When precise allocation of conferencing resources is not possible, we consider iterative cooperation with symmetric conference links, and show that the iterative scheme still surpasses one-shot cooperation, albeit under more restricted conditions.

A multi-access problem is considered where two encoders wish to communicate their messages to two decoders. The encoders can further cooperate via a conference, as introduced by Willems for multi-access channels. The capacity region of this channel is shown to be the intersection of the capacity regions of two multi-access channels with partially cooperating encoders

We consider cooperative data multicast in a wireless network with the objective to maximize the network lifetime. We present the maximum lifetime accumulative broadcast (MLAB) algorithm that specifies the nodes' order of transmission and transmit power levels. We prove that the solution found by MLAB is optimal but not necessarily unique. The power levels found by the algorithm ensure that the lifetimes of the active relays are the same, causing them to fail simultaneously. For the same battery levels at all the nodes, the optimum transmit powers become the same. The simplicity of the solution is made possible by allowing the nodes that are out of the transmission range of a transmitter to collect the energy of unreliably received overheard signals. As a message is forwarded through the network, nodes will have multiple opportunities to reliably receive the message by collecting energy during each retransmission. We refer to this cooperative strategy as accumulative multicast. Cooperative multicast not only increases the multicast energy-efficiency by allowing for more energy radiated in the network to be collected, but also facilitates load balancing by relaxing the constraint that a relay has to transmit with power sufficient to reach its most disadvantaged child. When the message is to be delivered to all network nodes this cooperative strategy becomes accumulative broadcast (Maric and Yates, 2002). Simulation results demonstrate that cooperative broadcast significantly increased network lifetime compared with conventional broadcast. We also present the distributed MLAB algorithm for accumulative broadcast that determines the transmit power levels locally at the nodes.

For reliable and unreliable forwarding in a parallel-relay network that allows orthogonal transmissions, we maximize the achievable rate under the total power constraint over all nodes. In such a network, the energy cost per information bit [S. Verdu, 1990] during the reliable forwarding is minimized in the wideband regime. For the wideband decode-and-forward (DF) strategy, we show that the optimum parallel-relay solution is to send the data through one relay that is in the "best" position. On the other hand, as observed in [B.E. Schein, 2001], the benefit of unreliable amplify-and-forward (AF) strategy diminishes in the wideband regime. We characterize the optimum bandwidth for AF and show that transmitting in the optimum bandwidth allows the network to operate in the linear regime where the achieved rate increases linearly with transmit power. We identify the best subset of AF relay nodes and characterize the optimum power allocation per dimension among relays.

We address the minimum-energy broadcast problem under the assumption that nodes beyond the nominal range of a transmitter can collect the energy of unreliably received overheard signals. As a message is forwarded through the network, a node will have multiple opportunities to reliably receive the message by collecting energy during each retransmission. We refer to this cooperative strategy as accumulative broadcast. We seek to employ accumulative broadcast in a large scale loosely synchronized, low-power network. Therefore, we focus on distributed network layer approaches for accumulative broadcast in which loosely synchronized nodes use only local information. To further simplify the system architecture, we assume that nodes forward only reliably decoded messages. Under these assumptions, we formulate the minimum-energy accumulative broadcast problem. We present a solution employing two subproblems. First, we identify the ordering in which nodes should transmit. Second, we determine the optimum power levels for that ordering. While the second subproblem can be solved by means of linear programming, the ordering subproblem is found to be NP-complete. We devise a heuristic algorithm to find a good ordering. Simulation results show the performance of the algorithm to be close to optimum and a significant improvement over the well known BIP algorithm for constructing energy-efficient broadcast trees. We then formulate a distributed version of the accumulative broadcast algorithm that uses only local information at the nodes and has performance close to its centralized counterpart.

We examine techniques for increasing spectral efficiency of cellular systems by using slow frequency hopping (FH) with dynamic frequency-hop (DFH) pattern adaptation. We first present analytical results illustrating the improvements in frequency outage probabilities obtained by DFH in comparison with random frequency hopping (RFH). Next, we show simulation results comparing the performance of various DFH and RFH techniques. System performance is expressed by cumulative distribution functions of codeword error rates. Systems that we study incorporate channel coding, interleaving, antenna diversity, and power control. Analysis and simulations consider the effects of path loss, shadowing, Rayleigh fading, cochannel interference, coherence bandwidth, voice activity, and occupancy. The results indicate that systems using DFH can support substantially more users than systems using RFH.