A network of distributed agents operating in a GPS-denied environment is tasked with tracking the position of a mobile asset. The agents use time-of-flight (ToF) measurements obtained from transmissions of a beacon signal by the asset to estimate the asset's position, but the estimates are noisy due to clock drift at the agents' local clocks. The clock drift can be reduced by having the asset and network of agents perform a distributed synchronization process; however, synchronization and localization cannot be performed simultaneously because the clock states are not well defined during synchronization and due to constraints on the radios' communication resources. The problem of optimizing when the agents should perform sensing or synchronization is formulated as a partially observed Markov decision process (POMDP) with continuous observations. Table-based Q-learning is used to search for an optimal policy on the belief space of the POMDP, but some form of approximation must be used because the belief space is a high -dimensional continuous space. We compare the performance of two approaches: 1) in replicated Q-learning, we learn a$Q$function that is a linear function of the continuous beliefs; 2) in triple-Q learning, the beliefs are replaced by a model with fewer parameters, and quantization is used on a continuous parameter. Simulations are used to compare the performance of these methods with the approach that is most commonly used, which is using periodic synchronization at an optimized, fixed rate.

We report results of an experiment in applying deep Q-learning for dynamic spectrum sharing (DSS) in the Alleys of Austin scenario from the DARPA Spectrum Collaboration Challenge. This scenario mimics mobile operations in an urban environment by up to five squads (teams) of soldiers. Each team operates its own wireless network. We consider teamwise– distributed DSS, where there is no central agent to coordinate spectrum usage across teams, but spectrum usage within each team is coordinated by a single member of that team. The spatial distributions of the soldiers creates opportunities for spatial reuse by certain subsets of the teams, and our experiment is set up to evaluate whether the deep Q-learning algorithm can discover and take advantage of these opportunities. The results show that deep Q-learning is able to take advantage of spatial reuse and that doing so results in better performance than a fair-share, disjoint spectrum allocation among the teams.

We consider the problem of jammer placement to partition a wireless network, where the network nodes and jammers are located in the real plane. In previous research, we found optimal and suboptimal jammer placements by reducing the search space for the jammers to the locations of the network nodes. In this paper, we develop techniques to find optimal jammer placements over all possible jammer placements in the real plane. Our approach finds a set of candidate jammer locations (CJLs) such that a jammer-placement solution using the CJLs achieves the minimum possible cardinality among all possible jammer placements in the real plane. The CJLs can be used directly with the optimal and fast, suboptimal algorithms for jammer placement from our previous work.

In cooperative spectrum sensing, multiple sensors work together to perform tasks such as localizing a target transmitter. However, the exchange of spectrum measurements leads to exposure of the physical location of participating sensors. Furthermore, in some cases, the sensitive characteristics of all participants can be revealed through the compromise of any one sensor. Accordingly, without guarantees about how data will be handled, there is little reason for such devices to work together. In this work, we protect the location of sensors cooperating in spectrum sensing by processing measurements within attestable containers, or enclaves. We use the enclave as a building block for new privacy-preserving particle filter protocols. We instantiate this enclave using Intel Software Guard Extensions (SGX) and investigate how the inclusion of enclaves impacts sensor privacy, carefully enumerating the different threats present in centralized and decentralized architectures. We show that enclave-based particle filter protocols incur minimal overhead (adding 16 milliseconds of processing to the measurement processing function versus unprotected computation), whereas cryptographically-based approaches suffer from multiple orders of magnitude greater costs. Our work demonstrates that enclaves can be effectively deployed in a decentralized architecture while dramatically improving current data handling techniques.

Wireless communication systems are susceptible to both unintentional interference and intentional jamming attacks. For mesh and ad-hoc networks, interference affects the network topology and can cause the network to partition, which may completely disrupt the applications or missions that depend on the network. Defensive techniques can be applied to try to prevent such disruptions to the network topology. Most previous research in this area is on improving network resilience by adapting the network topology when a jamming attack occurs. In this paper, we consider making a network more robust to jamming attacks before any such attack has happened. We consider a network in which the positions of most of the radios in the network are not under the control of the network operator, but the network operator can position a few “helper nodes” to add robustness against jamming. For instance, most of the nodes are radios on vehicles participating in a mission, and the helper nodes are mounted on mobile robots or UAVs. We develop techniques to determine where to position the helper nodes to maximize the robustness of the network to certain jamming attacks aimed at disrupting the network topology. Using our recent results for quickly determining how to attack a network, we use the harmony search algorithm to find helper node placements that maximize the number of jammers needed to disrupt the network.

We consider the problem of finding fast techniques to solve jammer placement problems, where the goal is to partition a wireless network and the communication and jamming effects can be modeled using graphs. We have previously developed optimal jammer placement techniques based on solving a binary linear program, but the complexity of the optimal solution is an exponential function of the number of nodes in the network. Several computationally efficient techniques are known for finding edge separators of networks, including spectral cuts and multilevel cuts. However, the jammer placement problem is more similar to finding a vertex separator and is complicated by the fact that a jammer can block communications to all of the neighbors of the jammer in a jamming graph. In this paper, we develop computationally efficient, but suboptimal, techniques for jammer placement that first find an edge cut using spectral or multilevel graph cuts and then find the minimum number of jammers required to block communication across all of the edges in the edge cut. The results show that the proposed techniques are orders of magnitude faster than even heuristic approaches to solving the optimum jammer placement problem, while offering different tradeoffs between the number of jammers required and the maximum order of the residual subnetworks. For networks of over 400 nodes, the solution based on multi-level graph partitioning uses fewer jammers, leaves smaller clusters, and requires lower computational complexity than the heuristic optimization of the optimal jammer placement problem.

Traditional comics are increasingly being augmented with digital effects, such as recoloring, stereoscopy, and animation. An open question in this endeavor is identifying where in a comic panel the effects should be placed. We propose a fast, semi-automatic technique to identify effects-worthy segments in a comic panel by utilizing gaze locations as a proxy for the importance of a region. We take advantage of the fact that comic artists influence viewer gaze towards narrative important regions. By capturing gaze locations from multiple viewers, we can identify important regions and direct a computer vision segmentation algorithm to extract these segments. The challenge is that these gaze data are noisy and difficult to process. Our key contribution is to leverage a theoretical breakthrough in the computer networks community towards robust and meaningful clustering of gaze locations into semantic regions, without needing the user to specify the number of clusters. We present a method based on the concept of relative eigen quality that takes a scanned comic image and a set of gaze points and produces an image segmentation. We demonstrate a variety of effects such as defocus, recoloring, stereoscopy, and animations. We also investigate the use of artificially generated gaze locations from saliency models in place of actual gaze locations.

In this work, we present a semi-automatic method based on gaze data to identify the objects in comic images on which digital effects will look best. Our key contribution is a robust technique to cluster the noisy gaze data without having to specify the number of clusters as input. We also present an approach to segment the identified object of interest.

We consider the problem of assigning a group of users with different rate requirements to a set of frequency bands, which may have different bandwidths, when the users access the channel via carrier-sense multiple access (CSMA). For example, in systems that employ dynamic spectrum access (DSA), secondary users may interleave their transmissions into space-time-frequency slots left open by primary users. The set of primary users that are active at a given time may leave a set of available channels that have unequal bandwidths. The use of CSMA by the secondary users reduces the need to coordinate transmissions among the users allocated to a particular frequency band, but it also results in potential collisions, which reduce the overall data rate that can be accommodated in the band. This is especially true when the presence of a finite sensing delay is considered. In this paper, we consider the layer problem of allocating users to the available frequency bands to minimize the bandwidth used (to accommodate other groups of secondary users), while taking into account the CSMA interactions of assigning multiple users to a band. We formulate this as a new form of bin packing problem, in which the size of the bin depends on the number of users that are assigned to the bin. A near optimal solution to this problem is found numerically using the Gurobi solver, and the performance is compared with the suboptimal first-fit algorithm, which has complexity that is appropriate for online implementation. Simulation results are provided to compare the optimal and online algorithms in terms of efficiency in allocating the bandwidth to the users and their complexity.

Autonomous mobile robots, such as unmanned aerial or ground vehicles, will play important roles in future military and commercial applications. Future systems will require the robots to communicate with each other on a peer-to-peer basis over a wireless link and are able to form a networked system such as an ad hoc network. In this paper, we consider a problem of optimizing the topology of the network for such systems. Our solution consists of two steps. We first develop a novel method to select a network tree topology from arbitrary initial connected network topology. Second, we develop a new optimization algorithm to reconfigure the network, starting from the tree found in the first step, while maintaining the connectivity to minimize the aggregate traffic under the constraints on the total number of hops that the mobile robots may move. We present simulation results to compare the performance of our algorithms.

We consider communication in the uplink of a wireless mesh or sensor network. A group of mobile radios or sensors (“nodes”) have information to transmit to one or more access points (APs). When the channels from the nodes to the APs suffer from fading, direct transmissions to the APs may have a high failure probability, and packets may need to be relayed through other nodes. In conventional routing, the relay is preselected, and hence fading may cause a high failure probability at the router. Geographic approaches can improve performance through opportunistic reception, in which a relay is selected from those nodes that receive the packet correctly and move it toward the AP. Existing geographic transmission schemes use an ad hoc design for the protocol that selects the relay node. In this paper, we propose Geographic Transmission with Optimized Relaying (GATOR), which provides a mathematical design for relay selection in a time-slotted geographic communication scheme. For path-loss exponent two, the relay selection scheme simplifies to depend on circular regions around the destination. Simulation results show that GATOR provides better performance than direct transmission, routing, and other geographic transmission schemes, especially when the signal-to-noise ratios are low and APs are sparse.

We consider communication in the uplink of a wireless mesh or sensor network. A group of mobile radios or sensors (hereafter called "nodes") have information to transmit to one or more access points (APs) (or "sinks"). When the channels from the nodes to the APs suffer from fading, direct transmissions to the APs may fail with a high probability, and packets may need to be relayed through other nodes. Under the conventional approach, routing, the relaying node is pre-selected, and fading may also cause a high probability of failure at the router. Thus, we propose a geographic approach, in which the relay is selected from those nodes that have received the packet correctly and can move it toward the AP. In this paper, we consider the design of a scheme to select which nodes should compete to relay the packet, and we develop and evaluate a protocol for this purpose. The results show that the geographic approach provides better performance than direct transmission, routing, and a previously developed geographic transmission scheme, especially when the signal-to-noise ratios are low and APs are sparse.

Multi-packet reception (MPR) has recently received attention for use in military wireless ad hoc networks because of the potential to greatly improve spatial reuse. However, MPR typically requires complicated hardware that makes it prohibitive to implement in many current military platforms. An alternative, cross-layer approach is to use an overlapped transmission technique, in which multiple transmissions can occur in the same geographical area because the communicators can use their knowledge of some of the interfering packets to recover the desired information. Examples of overlapped transmission techniques include overlapped carrier-sense multiple-access (OCSMA), physical-layer network coding, analog network coding, and Katti et al.'s COPE protocol. These techniques have much lower signal processing demands than MPR techniques and have also stimulated a lot of interest for use in military networks. Much of the previous research on overlapped transmission focuses on the physical-layer: how transmissions should be allowed to overlap, how the signals should be designed and detected, and the error probabilities under different conditions. These works tend to make optimistic assumptions about the availability of packets to perform overlapped transmission: often performance is evaluated for a simple three-node network under the assumption that traffic is always available at each of the edge nodes. In this paper, we explain why these protocols may suffer under real-world traffic conditions because of directional traffic flows and congestion control at the transport layer. We focus on how transmission control affects the performance of the OCSMA protocol. We propose modifications to the TCP parameters and the OCSMA protocol to improve the performance. We also show that OCSMA offers better fairness over the IEEE 802.11 MAC protocol in several scenarios.

The problem of secret sharing over the Gaussian wiretap channel is considered. A source and a destination intend to share secret information over a Gaussian channel in the presence of a wiretapper who observes the transmission through another Gaussian channel. Two constraints are imposed on the source-to-destination channel; namely, the source can transmit only binary phase-shift-keyed (BPSK) symbols, and symbol-by-symbol hard-decision quantization is applied to the received symbols of the destination. An error-free public channel is also available for the source and destination to exchange messages in order to help the secret-sharing process. The wiretapper can perfectly observe all messages in the public channel. It is shown that a secret-sharing scheme that employs a random ensemble of regular low-density parity-check (LDPC) codes can achieve the key capacity of the BPSK-constrained Gaussian wiretap channel asymptotically with increasing block length. To accommodate practical constraints of finite block length and limited decoding complexity, fixed irregular LDPC codes are also designed to replace the regular LDPC code ensemble in the proposed secret-sharing scheme.

In wireless multi-hop packet radio networks (MPRNs) that employ geographic transmissions, sleep schedules or node activation techniques may be used to power off some nodes to conserve energy. We consider the problem of selecting which nodes should power on to listen to a scheduled transmission when the channel suffers from random fading. We choose the objective of maximizing the expected value of the distance covered in a single transmission between a transmitter and the farthest receiver that successfully receives the packet, under a constraint on the expected number of receivers that turn on. Since there is a tradeoff between the distance of a node from the transmitter and the probability that the node receives the message correctly, we propose to use node-activation based on link-distance (NA-BOLD). We investigate optimal and sub-optimal NA-BOLD schemes and compare their performance with that of schemes that use a constant sleep schedule for every node within some radius of the transmitter. Our results show that the proposed NA-BOLD schemes achieve significantly larger transmission distances than conventional schemes.

In wireless ad hoc networks (WANets), multihop routing may result in a radio knowing the content of transmissions of nearby radios. This knowledge can be used to improve spatial reuse in the network, thereby enhancing network throughput. Consider two radios, Alice and Bob, that are neighbors in a WANet not employing spread-spectrum multiple access. Suppose that Alice transmits a packet to Bob for which Bob is not the final destination. Later, Bob forwards that packet on to the destination. Any transmission by Bob not intended for Alice usually causes interference that prevents Alice from receiving a packet from any of her neighbors. However, if Bob is transmitting a packet that he previously received from Alice, then Alice knows the content of the interfering packet, and this knowledge can allow Alice to receive a packet from one of her neighbors during Bob's transmission. In this paper, we develop overlapped transmission techniques based on this idea and analyze several factors affecting their performance. We then develop a MAC protocol based on the IEEE 802.11 standard to support overlapped transmission in a WANet. The resulting overlapped CSMA (OCSMA) protocol improves spatial reuse and end-to-end throughput in several scenarios.

The decision feedback equalizer (DFE) is widely used in practice for intersymbol interference (ISI) mitigation because of its low complexity. The performance of the DFE can be enhanced by arbitrating between the output of a standard DFE and a second DFE that operates on the time-reversed received sequence. The combination is called a bidirectional DFE (BDFE). Several previous papers have discussed how to arbitrate between the outputs of the forward and reverse equalizers to make hard decisions. We show that the arbitration algorithms proposed by other researchers are inefficient and propose a trellis-based conflict resolution (TBCR) algorithm that simultaneously provides better performance and lower complexity. We further show how the TBCR approach can be used to create soft-output BDFE algorithms for use with soft-input decoding of an error-control code. The soft-output BDFE algorithms offer better performance than previously proposed algorithms while requiring lower complexity than the maximum a posteriori equalizer. We also propose a novel method to reduce the computational complexity of BDFE algorithms by simultaneously computing the coefficients of the forward and reverse equalizers.

In mobile ad hoc networks (MANETs), conventional packet forwarding schemes that pre-select the next-hop receivers for a packet may fail if the channel coherence time is on the order of the typical packet duration because the pre-selected node may often suffer a deep fade for the duration of the packet. An alternative approach is geographic transmission, in which the packet is transmitted in the direction of the destination, but the next-hop forwarding node is selected among those nodes that are in the direction of the destination and that correctly recover the message. This approach takes advantage of multi-user diversity to significantly improve the probability of the packet being correctly received by a forwarding agent. However, this approach places additional burden on the energies of the mobile nodes if the forwarding scheme requires all of the next-hop neighbors of the transmitter (that are in the direction of the destination) attempt to receive a transmitted message. In this paper, we consider the joint design of node-activation strategies and transmission rates to maximize the expected value of transport capacity over a Nakagami-m channel under a constraint on the expected number of nodes that attempt to receive a packet. We show that our approach offers better performance than other approaches.

We consider a collection of battery-operated, low-power sensors randomly deployed within a geographic region for the purpose of sensing/monitoring the environment. In such a scenario, it is desirable to allow nodes to sleep (power off) whenever possible to conserve energy and increase the lifetime of the network. However, when the channel is subject to random variations, such as fading, there is an inherent trade-off between node activation and diversity. We consider a scenario in which a fixed number of nodes are allowed to turn on around a transmitter and the goal is to maximize the expected value of the distance that the message travels from the transmitter to the farthest receiver. We investigate the design of an algorithm to probabilistically determine whether a node should turn on based on its distance from the transmitter. This turns out to be a difficult probabilistic problem. We transform this problem into an analytical problem that provides a sub-optimal solution to the probabilistic problem. We compare the performance of this approach to a simpler protocol that turns on all the nodes within some radius of the transmitter. The results show that the link-distance based activation protocol provides significant gains in maximizing the expected value of the transmission distance to the farthest receiver, compared to the simpler protocol.

Collaborative decoding is an approach that can achieve diversity and combining gain by exchanging decoding information among a cluster of physically separated receivers. On AWGN channels, the least-reliable-bits (LRB) exchange scheme can achieve performance close to equal-gain combining (EGC) of all received symbols from all receivers, while reducing the amount of information that must be exchanged. In this paper, we analyze the error performance of collaborative decoding with the LRB exchange scheme when nonrecursive convolutional codes are used. The analysis is based on the observation that the extrinsic information generated in the collaborative decoding of these convolutional codes can be approximated by Gaussian random variables. A density-evolution model based on a single maximum a posteriori decoder is used to obtain the statistical characteristics of the extrinsic information. With the statistical knowledge of the extrinsic information, we develop an approximate upper bound for the error performance of the collaborative decoding process. Numerical results show that our analysis gives very good predictions of the bit error rate for collaborative decoding with LRB exchange. At high signal-to-noise ratios collaborative decoding with properly chosen parameters can achieve the same error performance as EGC of all received symbols from all receiving nodes.

In this paper, we present a new decoding algorithm for the Wyner-Ziv (WZ) video coding scheme based on turbo codes. In this scheme, a video frame is encoded using a turbo code, and only a subset of the parity bits are sent to the decoder. At the decoder, the temporal correlation of the video sequence is exploited by using the previous frame as noisy side information (SI) for the current frame. However, there is a mismatch between the SI, which is available as pixel values, and the binary code bits. Previous implementations of the decoder use suboptimal approaches that convert pixel values to soft information for code bits. We present a new decoding algorithm for this application based on decoding on a hyper-trellis, in which multiple states of the original code trellis are combined. We show that this approach significantly improves performance without changing the complexity of the decoder. We also introduce a new technique for the WZ decoder to exploit the spatial correlation within a frame without requiring transform-domain encoding at the encoder, thereby reducing its complexity. Simulation results for fixed-rate transmission show a 9-10-dB improvement in the peak signal-to-noise ratio when compared to a WZ video codec that does bitwise decoding and utilizes only the temporal correlation.

In this paper, we apply the EM algorithm for mitigation of multi-access interference (MAI) in asynchronous slow frequency-hop spread spectrum (FHSS) systems that employ binary frequency-shift keying (BFSK) modulation. MAI occurs if the hopping patterns of the users are not orthogonal. We show that when FSK signals arrive asynchronously, the time offset exposes portions of the desired and interfering signals in a way that can be exploited to improve the decoder performance. We develop an iterative detection, estimation, and decoding scheme to recover the desired signal in the presence of MAI. We compare the performance of this algorithm with that of a conventional noncoherent BFSK transceiver and show that the EM-based algorithm is particularly effective in the presence of strong interfering signals and allows more users in a FHSS system.

In this paper, we evaluate the performance of various channel-sharing schemes in the forward link from a base station (BS) to several mobile stations (MSs). Simultaneous transmission (broadcasting) to all mobile stations using the entire available bandwidth is known to yield rates dominating any other channel-sharing technique for Gaussian channels. However, broadcasting is very complicated from an implementation point of view. We analyze and compare different channel-sharing techniques on the basis of the asymptotic minimum signal-to-noise ratio (SNR) per MS necessary at the BS to transmit to a certain set of MSs in a single cell at a common data rate. From our results we conclude that suboptimal but practical methods like two- or three-level superposition coding when used in conjunction with frequency division multiplexing perform sufficiently close to the optimum and hence, are good alternatives to the optimal broadcasting scheme.

We present a cooperative communication scheme in which a group of receivers can collaborate to decode a message that none of the receivers can individually decode. The receivers act as a virtual antenna array in which the combining must be performed over bandwidth-constrained links. The proposed approach is targeted at systems in which the cooperative information must be digitized, such as for wireless or wired links that are constrained to use digital modulation. In such systems, previously proposed schemes such as amplify-and-forward would require that a large amount of information be exchanged when there are many collaborating nodes. The approach presented in this paper, called improved least-reliable bits (I-LRB) collaborative decoding, provides a higher level of adaptation than previously proposed cooperative schemes. The I-LRB scheme utilizes reliability information and information about competing paths in soft-input, soft-output (SISO) decoders to adaptively select the amount of information that is needed to correct a particular part of a message, as well as which bits should be exchanged. Simulation results show that the proposed approach offers a significant performance advantage over a constrained-overhead, incremental form of maximal ratio combining (MRC).

Dirty paper coding has been shown to achieve the capacity region of a Gaussian broadcast channel. However, it is a complicated scheme and assumes knowledge of the interfering signals at the transmitter. In this paper, we compare the downlink user capacity of dirty paper coding and time-division multiple access (TDMA) in a single cell of a cellular network with single antennas at the transmitter and each of the receivers. Here we define user capacity as the expected value of the number of users/receivers to which the transmitter can simultaneously transmit at an equal rate. The system that we consider selects the users to which it transmits from a population of mobile users. We derive closed-form expressions for the downlink user capacity using dirty paper coding and TDMA under a total transmit power constraint and a common target information rate at all the mobile users, as the user population tends to infinity. The results indicate that DPC provides a gain of at most 12% in user capacity over TDMA for the scenarios that we consider. Thus TDMA may be an attractive alternative to DPC because of the complexity of the latter

Superposition coding techniques can be used to improve communications efficiency in a variety of scenarios. These techniques are particularly appropriate for applications in which there are spatial or temporal disparities in received signal-to-noise ratios (SNRs). In this paper, we consider the application of superposition coding to improve the throughput of the forward link in a CDMA cellular system using orthogonal spreading sequences. By taking advantage of power disparities that are created by power control on the forward link, the system can transmit to a larger number of users by transmitting to multiple users on a single spreading sequence and using superposition coding. We use an abstraction of a cellular communication system in which Shannon capacity or the optimal capacity equations for broadcasting on an additive white Gaussian noise channel are used to determine the required transmit power to a user or users. We evaluate the user capacity achieved with the proposed superposition coding technique under both average-and fixed-power constraints. We compare the performance of the proposed technique to that of a system that employs generalized Welch bound equality (GWBE) sequences. The results indicate that superposition coding can significantly increase the user capacity of a cellular system and that broadcasting is much more effective than using GWBE sequences

We consider the use of multiuser diversity to maximize transmission distance in a wireless network. This differs from previous work on multiuser diversity, which focused mainly on increasing the data rate. We analyze the maximum achievable transmission distance in a geocasting scenario, in which any radio in a specified geographical area is an acceptable destination for a packet. Performance results are presented for Rayleigh fading and nonfading channels. To illustrate the benefits of multiuser diversity, we show that higher transmission distances can be achieved over fading channels than over nonfading channels if the density of radios is sufficiently high. We also illustrate one application of our results to protocol design

We consider a communication scenario in which a message is received in the presence of partial-time Gaussian jamming and additive white Gaussian noise. We consider a quasi-static channel, in which the amplitude and phase are constant over each packet transmission. The receiver does not know the amplitude and phase of the incoming signal, which symbols are jammed, or even the statistics of the jammer, such as the jamming power and jamming probability. In this scenario, the receiver must accurately estimate the parameters of the channel and the jamming to achieve good performance. We apply the expectation-maximization (EM) algorithm to iteratively approximate the maximum-likelihood (ML) estimator for all of the parameters. We find that the overall performance of the EM algorithm is very sensitive to the initial estimates, so we propose a new initial estimator that offers good performance. The EM algorithm approach requires pilot symbols to resolve a phase ambiguity. Thus, we also present a blind estimation algorithm to avoid the reduction in overall code rate from the use of pilot symbols

One of the most promising approaches to improving communication efficiency in wireless communication systems is the use of multiuser diversity. Although it has been widely investigated and shown feasible and efficient in cellular networks, there is little work for the ad hoc networks, especially in real protocol and algorithm design. In this paper, we propose a novel scheme, namely, the Opportunistic Medium Access and Auto Rate (OMAR), to efficiently utilize the shared medium in IEEE 802.11-based ad hoc networks by taking advantage of diversity, distributed scheduling, and adaptivity. In an ad hoc network, especially in a heterogeneous ad hoc network or a mesh network, some nodes may need to communicate with multiple one-hop nodes. We allow such a node with a certain number of links to function as a clusterhead to locally coordinate multiuser communications. We introduce a CDF-based (Cumulative Distribution Function) K-ary opportunistic splitting algorithm and a distributed stochastic scheduling algorithm to resolve intra and intercluster collisions, respectively. Fairness is formulated and solved in terms of social optimality within and across clusters. Analytical and simulation results show that our scheme can significantly improve communication efficiency while providing social fairness.

We propose new collaborative reception techniques for use in the presence of a partial-time Gaussian jammer. Under the proposed techniques, a group of radios acts as a distributed antenna array by exchanging information that is then used to perform jamming mitigation. We propose two such jamming mitigation techniques that offer a tradeoff between performance and complexity. The results show that these techniques can allow communications in much more severe jamming conditions than when collaboration is not employed or when conventional collaboration techniques based on maximal-ratio combining are applied. Example scenarios with strong jamming show that three collaborating radios can reduce the frame error rate by more than two orders of magnitude over single-radio reception. In another scenario it is shown that a jammer must jam at least 75% of the transmitted symbols to produce an unacceptable frame error rate with three collaborating radios, but only 43% of the transmitted symbols if there is no collaboration.

A new approach to design video coding schemes for wireless video applications has emerged recently. Schemes using this approach are based on the principle of distributed source coding, and they exploit the correlation in the frames of the video sequence at the decoder. One such scheme models the correlation between frames as a Laplacian channel, and uses a turbo code to correct errors occurring in this pseudo-channel. Existing implementations use a sub-optimal approximation to compute the channel likelihoods in the BCJR algorithm in the turbo decoder. To resolve this sub-optimality, we propose applying the BCJR algorithm on a trellis-structure with parallel transitions. This trellis structure is called a hyper-trellis. The BCJR maximum a posteriori algorithm is modified to use the hyper-trellis, and computation of the channel-likelihoods are shown to be optimal on the hyper-trellis. Simulation results show that the hyper-trellis approach can yield a 5 dB improvement in peak signal-to-noise ratio.

In collaborative decoding, spatial diversity is achieved by exchanging decoding information among a cluster of physically separated receivers. The least-reliable-bit (LRB) exchange scheme helps collaborative decoding to lower the amount of information that must be exchanged while providing performance close to the maximal-ratio combining technique. In this paper, we approximately evaluate the error performance of the collaborative decoding with the LRB exchange scheme when nonrecursive convolutional codes are used. The Gaussian approximation and union bound are used in the analysis.

Collaborative techniques have been proposed to improve communications in the presence of a hostile jammer. A distributed detection and decoding technique based on collaborative decoding has been shown to he effective for communications over non-fading channels for coherent communications. In this paper, we consider collaborative communications strategies for jamming channels in which the message and jamming signals experience independent block fading at each receiving node. Furthermore, we assume that the phase of the message signal is not known and must be estimated from the received signal. Joint decoding and estimation of all of the fading and jamming parameters is computationally prohibitive, so we develop iterative estimation and decoding algorithms. The fading coefficient and parameters of the jamming signal are estimated using the EM and BCJR algorithms. The results show that the proposed technique is an effective response to hostile jamming.

We propose a cooperative-diversity technique for ad hoc networks based on the decode-and-forward relaying strategy. We develop a MAC protocol based on slotted ALOHA that allows neighbors of a transmitter to act as relays and forward a packet toward its final destination when the transmission to the intended recipient fails. The proposed technique provides additional robustness against fading, packet collisions and radio mobility. Network simulations confirm that under heavy traffic conditions, in which every radio always has packets to send, the proposed cooperative-diversity slotted-ALOHA protocol can provide a higher one-hop and end-to-end throughput than the standard slotted-ALOHA protocol can. A similar advantage in end-to-end delay can be obtained when the traffic is light. As a result, the proposed cooperative-diversity ALOHA protocol can be used to improve these measures of quality of service (QoS) in ad hoc wireless networks.

Cooperative communication techniques are network-based approaches to achieve spatial diversity in systems in which each node only has a single antenna. Many such techniques are based on relaying, which is effective in terms of error performance but requires a large information exchange among the cooperating nodes. Cooperative reception techniques that offer near-optimal performance with a smaller information exchange are an area of ongoing research. One promising approach is to investigate combining techniques that can be used as a model for designing efficient cooperative reception schemes. In this paper, we consider one such technique, called reliability filling, that combines only as much information as needed to meet some reliability threshold. We analyze the performance of this technique for several scenarios of interest. Analytical estimates of the overhead involved in reliability filling are also given. Analysis and simulation results show that reliability filling can offer performance close to maximal-ratio combining while combining fewer symbols.

In previous work, unequal error-protection techniques have been applied to improve the throughput of a wireless communication system in which a transmission is received by several radios with different capabilities. For instance, these capabilities may correspond to differences in path loss, fading, or interference. By taking advantage of the broadcast nature of the channel, additional messages for the more-capable receivers can be included on transmissions to the less-capable receivers at very little cost (in terms of required energy at the transmitter or error probabilities at the receivers). This technique has been termed simulcasting or multicast signaling. In this paper, we consider the use of these techniques in an ad hoc network. These techniques impact the link throughput, end-to-end throughput, and network connectivity. We investigate how the choice of parameters for the simulcasting technique affects these network performance metrics. The results indicate that a properly chosen simulcasting technique can improve the link and end-to-end throughput in wireless ad hoc networks with only a slight degradation in other metrics, such as network connectivity.

We consider the use of selective-retransmission automatic repeat request (ARQ) protocols to improve communication performance on partial-time jamming channels. The schemes that we propose are based on reliability-based hybrid ARQ (RB-HARQ), in which the set of bits to be retransmitted is adaptively selected based on the estimated a posteriori probabilities at the output of a soft-input, soft-output decoder. For channels with bursty partial-time jamming, the RB-HARQ techniques are particularly appropriate because these techniques can identify which symbols need to be retransmitted, and the bursty nature of the jamming reduces the overhead required to relay this information to the source. We extend our reliability measure to incorporate not only a posteriori probability information but also estimates of the probability that a bit was jammed. We compare the performance of the proposed scheme with that of conventional approaches, in which a predetermined set of bits is retransmitted in response to a packet failure. The results show that RB-HARQ schemes can achieve higher throughput than these conventional approaches in several scenarios.

Reliability-based hybrid ARQ (RB-HARQ) is a recently developed form of incremental-redundancy ARQ. The RB-HARQ technique can be used with codes that use soft-input, soft-output (SISO) decoders, such as convolutional codes and turbo codes. In RB-HARQ, the bits that are to be retransmitted are adaptively selected at the receiver based on the estimated bit reliabilities at the output of a SISO decoder. This technique has the potential to improve performance and minimize retransmission size by targeting those bits that are likely to be in error. It has already been shown that RB-HARQ achieves significant performance improvement provided that large retransmission-request (NACK) packets can be afforded on the feedback link. In this paper, we propose and evaluate the performance of a RB-HARQ technique that uses rate-compatible punctured convolutional (RCPC) codes in the forward channel and source coding in the feedback link. The proposed technique uses source coding to achieve small request packets, thus leading to better performance. The performance of the proposed technique is evaluated in terms of probability of bit error, probability of packet error and throughput. We also compare the performance of the proposed scheme with the common approach to hybrid-ARQ that uses punctured convolutional codes and code combining. The results show that the proposed RB-HARQ scheme achieves better performance than a hybrid-ARQ scheme that uses only RCPC codes.

Due to the salient characteristics such as the time-varying and error-prone wireless links, the dynamic and limited bandwidth, the time-varying traffic pattern and user locations, and the energy constraints, it is a challenging task to efficiently support heterogeneous traffic with different quality of service (CoS) requirements in multihop mobile ad hoc networks. In the last few years, many channel-dependent mechanisms are proposed to address this issue based on the cross-layer design philosophy. However, a lot of problems remain before more efficient solutions are found. One of the problems is how to alleviate the conflict between throughput and fairness for different prioritized traffic, especially how to avoid the bandwidth starvation problem for low-priority traffic when the high-priority traffic load is very high. In this paper, we propose a novel scheme named Courtesy Piggybacking to address this problem. With the recognition of interlayer coupling, our Courtesy Piggybacking scheme exploits the channel dynamics and stochastic traffic features to alleviate the conflict. The basic idea is to let the high-priority traffic help the low-priority traffic by sharing unused residual bandwidth with courtesy. Another noteworthy feature of the proposed scheme is its implementation simplicity: The scheme is easy to implement and is applicable in networks using either reservation-based or contention-based MAC protocols.

In this paper, we propose a network-based distributed antenna array approach, in which a bit-interleaved rectangular parity-check coded modulation with an iterative demodulation scheme is used. Different from the conventional multiple-array systems, this distributed array employs a pair of physically separated identical receiving nodes. These nodes receive the transmitted signal through independent channels. The each node demodulates and decodes the received signal in an iterative manner. At each iteration, the pair of nodes exchange the reliability measure of a small portion of the symbols to obtain spatial diversity. Simulation results show that significant diversity gain can be achieved at much lower traffic cost than maximal ratio combining.

Reliability-based hybrid ARQ (RB-HARQ) is a recently introduced approach to incremental-redundancy ARQ. In RB-HARQ, the bits that are to be retransmitted are adaptively selected at the receiver based on the estimated bit reliabilities. This technique has the potential to improve performance and minimize retransmission size by targeting those bits that are likely to be in error. However, previous versions of the RB-HARQ algorithm have resulted in large request (NACK) packets that made the technique appropriate only for systems that can tolerate large request packets on the feedback link. In this paper, we show that RB-HARQ is effective with convolutional codes, and we exploit the time-correlation properties of these codes to significantly reduce the size of the retransmission requests.

We investigate reliability exchange schemes that allow a group of radios to act as a distributed antenna array in which radio links are used to exchange information between the various radios. We consider a scenario in which multiple nodes receive independent copies of the same message. Each node independently decodes its message and then participates in a process of "smart" information exchange with the other nodes. Each node transmits its estimates of the a posteriori probabilities of some set of bits, and these estimates are used as a priori information by other receivers. The a priori information is used to perform maximum a posteriori decoding on the received sequence. This process of decoding and information exchange can be repeated several times. Simulation results show that the performance can be significantly improved by careful selection of the bits for which information is exchanged.

We propose a new form of incremental-redundancy hybrid ARQ for use with codes that use soft-input, soft-output decoders, such as turbo codes. The new ARQ scheme determines the reliability of bits in the iterative decoding process based on the magnitude of the soft outputs of the decoder, which are the a posteriori log-likelihood ratios. We show that the bits with the smallest magnitudes are not only likely to be in error, but are linked to a set of weak bits that limit the convergence of the iterative decoding algorithm. The new ARQ scheme requests additional information for some subset of these weak bits. We note that the hybrid ARQ scheme we propose is particularly appropriate for use on channels in which there is some asymmetry, as the negative acknowledgements are considerably larger than those used in conventional ARQ schemes. The hybrid-ARQ schemes presented in this paper provide significant performance gains and can be used to achieve performance close to the channel capacity.

We compare the performance of several different decoding strategies for concatenated codes based on a serial concatenation of a rectangular parity-check code (RPCC) with a turbo code. These concatenated codes are referred to as RPCC+turbo codes. RPCC+turbo codes have been shown to outperform turbo codes significantly in several scenarios (see Shea, J.M., Proc. 2001 IEEE Int. Symp. Information Theory, p.144, 2001; Shea and Wong, T.F., Proc. 2001 IEEE Military Commun. Conf., 2001). One particularly useful application is to replace a turbo code with an RPCC+turbo code based on constituent codes of smaller memory. This combination can provide comparable or better performance while also achieving a lower decoder complexity (see Shea and Wong, 2001). However, the complexity of the iterative MAP decoder for such a code is still relatively high. We compare several different decoding strategies for the RPCC+turbo code that offer various trade-offs between performance and complexity.

We investigate the use of a class of multi-dimensional parity-check (MDPC) codes as a simple and spectrally efficient means to obtain diversity in Rayleigh fading channels. We demonstrate that the MDPC codes can provide a maximum of 4 degrees of diversity, requiring only a minimal amount of added redundancy. We also propose two techniques, namely parallel and serial code concatenation, to improve the performance of the MDPC codes in Rayleigh fading channels. In the parallel concatenation technique, multiple MDPC codes are parallel concatenated to improve the performance in low signal-to-noise ratio regions. In the serial concatenation technique, a standard convolutional code is employed as an outer code to increase the maximum degree of diversity and provide further coding gain.

The characteristics of mobile wireless communication channels fluctuate for many reasons, including movement of the radios, changes in path attenuation, and variations in interference. Several adaptive signaling techniques have been proposed for use in wideband code-division multiple-access (CDMA) systems including adaptive data rates, adaptive spreading code rates, discontinuous transmission, and multicode CDMA. We introduce adaptive signaling techniques that use nonuniform phase-shift-key (PSK) modulation. These techniques have several advantages for use in CDMA communications, and they support multimedia transmission by simultaneously delivering different types of traffic, each with its own required quality of service. The signaling methods that we propose deliver a basic message at a specified error rate and simultaneously deliver an additional message by exploiting any extra capability that is available. We show that by adapting the location of the points in a PSK constellation, the throughput can be maximized for the additional message while maintaining an acceptable error rate for the basic message. Responses to larger changes in channel quality are accomplished by adapting the PSK constellation size, signaling rate, and error-correcting code. Examples of adaptive signaling schemes that employ nonuniform PSK constellations are presented, including an application to a cellular CDMA system.

It is a common requirement in a mobile wireless communication network that a radio must be capable of simultaneously transmitting a message to two or more neighbors in the network. Some of the intended recipients may be more capable than others in the sense that their communication links from the transmitter have less interference, fading, or attenuation. Because it is desirable that a multicast or broadcast transmission be received successfully by all radios for which it is intended, the usual approach is to limit the transmission rate to that which can be demodulated by the least capable among these radios. Nonuniform nonbinary phase-shift-key (PSK) signal constellations can be designed to increase the throughput of multicast transmissions by delivering additional information to more-capable receivers along with the multicast message. This additional throughput can be employed to transmit multimedia messages (e.g., voice and data) to the more-capable receivers. In this paper, we determine the error probabilities for coherent demodulation of nonuniform PSK signals and noncoherent demodulation of nonuniform differential PSK signals. Because the PSK constellations have a constant envelope, they are better for use in mobile wireless communication networks than the constellations based on quadrature-amplitude modulation that have been proposed in previous publications.

Broadcast or multicast signaling can be employed in a wireless communication network to transmit a message to multiple neighbors simultaneously. The capabilities of the intended recipients may vary in the sense that the communication links to some neighbors may have less interference or attenuation than the links to others. We have previously proposed the use of nonuniform phase-shift key (PSK) signal constellations to allow a transmitter to deliver a basic message to each of the intended receivers and an additional message to the more-capable receivers. In this paper, convolutional coding and nonuniform PSK modulation are combined to provide greater efficiency and increased flexibility. The primary goal of multicast transmission, which is for each designated neighbor to have an acceptable probability of receiving the multicast message correctly, is achieved in a way that permits inclusion of multimedia messages for the more-capable receivers. Performance results and tradeoffs are presented for hard- and soft-decision decoding of convolutionally encoded coherent M-ary PSK multicast transmissions. Our results show that convolutional coding can be used with nonuniform PSK modulation to transmit additional information in mobile communication systems with little degradation to the basic information.