This paper presents a privacy-preserving event detection scheme based on measurements made by a network of sensors. A diameter-like decision statistic made up of the marginal types of the measurements observed by the sensors is employed. The proposed detection scheme can achieve the best type-I error exponent as the type-II error rate is required to be negligible. Detection performance with finite-length observations is also demonstrated through a simulation example of spectrum sensing. Privacy protection is achieved by obfuscating the sensors marginal types with random zero-modulo-sum numbers that are generated and distributed via the exchange of encrypted messages among the sensors. The privacy-preserving performance against “honest but curious” adversaries, including colluding sensors, the fusion center, and external eavesdroppers, is analyzed through a series of cryptographic games. It is shown that the probability that any probabilistic polynomial time adversary successfully estimates the sensors measured types cannot be much better than independent guessing, when there are at least two noncolluding sensors.

Federated learning (FL) allows multiple parties (distributed devices) to train a machine learning model without sharing raw data. How to effectively and efficiently utilize the resources on devices and the central server is a highly interesting yet challenging problem. In this paper, we propose an efficient split federated learning algorithm (ESFL) to take full advantage of the powerful computing capabilities at a central server under a split federated learning framework with heterogeneous end devices (EDs). By splitting the model into different submodels between the server and EDs, our approach jointly optimizes user-side workload and server-side computing resource allocation by considering users’ heterogeneity. We formulate the whole optimization problem as a mixed-integer non-linear program, which is an NP-hard problem, and develop an iterative approach to obtain an approximate solution efficiently. Extensive simulations have been conducted to validate the significantly increased efficiency of our ESFL approach compared with standard federated learning, split learning, and splitfed learning.

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.

In this work, we consider target parameter estimation of phase-modulated continuous-wave (PMCW) multiple-input multiple-output (MIMO) radars with few-bit analog-to-digital converters (ADCs). We formulate the estimation problem as a sparse signal recovery problem and modify the fast iterative shrinkage-thresholding algorithm (FISTA) to solve it. The ℓ2,1-norm is adopted to promote the sparsity in the range-Doppler-angle domain. Simulation results show that using few-bit ADCs can achieve comparable performance to many-bit ADCs when targets are widely separated. However, if targets are spaced closely, performance losses can occur when 1-bit ADCs are applied.

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.

This work presents a new methodology for obtaining information theoretic necessary conditions directly from general operational requirements. This methodology is based on the construction of a discrete random variable that, when conditioned upon, ensures information stability of quasi-images. The induced information stability allows a more direct way to develop information theoretic necessary conditions from operational requirements beyond using Fano's inequality. That is, while Fano's inequality uses the probability of error to establish an upper bound on the entropy of a random variable given its estimator, the proposed new methodology can be applied to arbitrary operational requirements to obtain corresponding conditions on information theoretic quantities. To demonstrate its power, this new methodology is employed, to derive new necessary conditions for keyed authentication over a discrete memoryless channels and to establish the capacity region subject to finite leakage and finite error of the wiretap channel under two different secrecy metrics. These examples establish the usefulness of the proposed methodology.

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.

In this paper we classify what arbitrary sources can be transmitted over a discrete memoryless broadcast channel with confidential communications (DM-BCC). Despite allowing completely arbitrary sources and finite error, we show that necessary and sufficient conditions can be expressed in terms of traditional channel capacity regions. As a by-product we also determine the (ε, δ) -capacity region, and show that even in this more general setting source-channel separation is optimal for the DM-BCC as originally defined.

This paper employs equal-image-size source partitioning techniques to derive the capacities of the general discrete memoryless wiretap channel (DM-WTC) under four different secrecy criteria. These criteria respectively specify requirements on the expected values and tail probabilities of the differences, in absolute value and in exponent, between the joint probability of the secret message and the eavesdropper's observation and the corresponding probability if they were independent. Some of these criteria reduce back to the standard leakage and variation distance constraints that have been previously considered in the literature. The capacities under these secrecy criteria are found to be different when non-vanishing error and secrecy tolerances are allowed. Based on these new results, we are able to conclude that the strong converse property generally holds for the DM-WTC only under the two secrecy criteria based on constraining the tail probabilities. Under the secrecy criteria based on the expected values, an interesting phase change phenomenon is observed as the tolerance values vary.

This paper investigates the problem of information stabilization of the images of source sets over discrete memoryless channels (DMCs). It is shown that if the minimum image cardinality of a source set over a DMC has a specific entropy characterization, then the image of this source set will be information stable. In many applications, this requirement on the source set can be satisfied using the method of equal-image-size source partitioning. A construction of a strong secrecy subcode from a weak secrecy code for the wiretap channel is provided as an example to illustrate the use of the information stabilization technique.

We consider an amplify-and-forward relay network composed of a source, two relays, and a destination. In this network, the two relays are untrusted in the sense that they may perform Byzantine attacks by forwarding altered symbols to the destination. Note that every symbol received by the destination may be altered, and hence, no clean reference observation is available to the destination. For this network, we identify a large family of Byzantine attacks that can be detected in the physical layer. We further investigate how the channel conditions impact the detection against this family of attacks. In particular, we prove that all Byzantine attacks in this family can be detected with asymptotically small miss detection and false alarm probabilities by using a sufficiently large number of channel observations if and only if the network satisfies a non-manipulability condition. No pre-shared secret or secret transmission is needed for the detection of these attacks, demonstrating the value of this physical-layer security technique for counteracting Byzantine attacks.

In this paper we investigate the image size characterization problem. We show that any arbitrary source set may be decomposed into sets whose image size characterization is the same as its entropy characterization. We also show that the number of these sets required is small enough that one may consider that from a coding perspective the achievable entropy region and achievable exponent region are equal. This has an impact on many source networks and network problems whose solution heretofore could not have the image size characterization applied to them.

The goal of this paper is to obtain the channel conditions (if exist) under which substitution attacks performed by relay node(s) in a relay network can be detected. The network model considered consists of a source node and a destination node. There are two independent transmission paths from the source to the destination, each via a potentially malicious relay which may perform substitution attacks by forwarding altered symbols to the destination. The destination attempts to detect any such malicious act of the relays by comparing the joint empirical distribution of the symbols received from the relays with known channel statistics along the two paths. Note that every symbol received by the destination may be altered, and hence no clean reference observation is available to the node. It is demonstrated that maliciousness of the relays can be asymptotically detected with sufficient channel observations if and only if the two relays do not collude and the network satisfies a non-manipulability condition.

This paper presents a random coding scheme with which two nodes can exchange information with guaranteed integrity over a two-way Byzantine relay. This coding scheme is employed to obtain an inner bound on the capacity region with information integrity. No pre-shared secret or secret transmission is needed for the proposed scheme. Hence the inner bound obtained is generally larger than those achieved based on secret transmission schemes. This approach advocates the separation of supporting information integrity and secrecy.

We consider the problem of two sources wanting to share information through a potentially untrustworthy intermediary node. We assume that the two sources transmit random symbols simultaneously and that the intermediary node relays the information in the amplify-and-forward manner. We show that under a certain sufficient condition on the channel, it is possible to asymptotically detect whether or not the intermediary node is degrading the channel by sending out manipulated symbols. This can be done solely by each source examining its received distribution conditioned on what it transmitted; thus allowing for a minimally invasive approach to determining if the intermediary node is acting maliciously. More specifically, we model the potential malicious action of the intermediate node by an “attack” channel. An estimate of the attack channel is obtained from the received conditional distribution empirically observed by a source node. We show that the estimated attack channel converges in probability to the true attack channel if the intermediate node is not acting maliciously. Otherwise there is a separation between the estimated and true attacking channels with high probability. This result provides us a clear-cut criterion to determine whether the intermediate node is malicious or not.

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.

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.

Coding for the causal cognitive radio channel, with the cognitive source subjected to a half-duplex constraint, is studied. A discrete memoryless channel model incorporating the half-duplex constraint is presented, and a new achievable rate region is derived for this channel. It is proved that this rate region contains the previously known causal achievable rate region of for Gaussian channels.

Cooperative transmission protocols using a flow optimization approach for a general multi-node half-duplex wireless relay network are presented. The proposed design involves solving a convex flow optimization problem on a graph that models the relay network. Two protocols are developed using the techniques of broadcasting (BC), multiple-access (MA), and time sharing (TS), and both are shown to achieve the optimal diversity-multiplexing tradeoff (DMT). Simulation results are used to quantify the performances of the proposed protocols in terms of outage probabilities, and to compare them against the max-flow-min-cut bound.

The problem of state estimation with stochastic uncertainties in the initial state, model noise, and measurement noise is considered using the restricted risk Bayes approach. It is assumed that the a priori distributions of these quantities are not perfectly known, but that some information about them may be available. While offering robustness, the restricted risk Bayes approach incorporates the available a priori information to give less conservative state estimators than the Gamma-minimax approach popular in the literature. When attention is restricted to linear estimators based on a quadratic loss function, a systematic method to derive restricted risk Bayes estimators is proposed. Applying to the filtering problem, the restricted risk Bayes approach provides us with a robust method to calibrate the Kalman filter (KF), considering the presence of stochastic uncertainties. This method is illustrated with a target tracking example and a wireless channel tracking example for which the Bayes, minimax, and restricted risk Bayes estimators are derived and their performance is compared.

We investigate the relaying problem in parallel relay networks consisting of a source sending information to a destination via multiple relays. To exploit the broadcasting nature of the wireless channel, the source broadcasts to the relays and the relays forward the decoded information to the destination. The flow rates on all links in the network are selected to minimize the average transmit power required. We consider two optimal protocols, respectively in which the relays forward the decoded information phase-synchronously and phase-asynchronously. It turns out that not all relays forward information in the optimal phase-asynchronous protocol. Using this fact, we propose a sub-optimal protocol employing at most two relays. In phase-synchronous relaying, the optimal protocol gives around 1dB and over 3 dB improvements compared at the outage probability of 10-4with respect to the single-relay optimal protocol at low-rate and high-rate requirements, respectively. Again, we propose a two-relay sub-optimal protocol for phase-synchronous transmission. Simulation results indicate that these sub-optimal protocols give performances that are close to the performances of the optimal protocols and superior to that of the single-relay optimal protocol.

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 investigate the problem of flow optimization in a parallel relay network which consists of a single source sending information to a single destination through multiple relays. The source transmits to the relays using cooperative broadcast and the relays decode and forward the received information to the destination using multiple-access transmission. The relays are operating in half-duplex mode. The flow rates on all links in the network are assigned in a way such that the minimum average transmit power required is minimized. It turns out that not all relays participate in optimal transmission. Using this fact, we propose a sub-optimal relay protocol that employs at most two relays. Simulation results indicate that this sub-optimal protocol gives performance that is close to the performance of the optimal protocol employing multiple relays and superior to that obtained by existing single-relay selection protocols.

A pricing game is derived for cooperative transmission among selfish nodes. Each source node is assigned an orthogonal channel. By overhearing other channels, the source nodes can help relaying other nodes’ messages at a rate based on the received payments. At Nash Equilibrium, the total transmission power is minimized. We also propose a simplified implementation for low rate regime. Simulation results illustrate the significant improvement of power consumption over direct transmission scheme and the high convergence rate of our implementation.

In this paper, a cooperative transmission design for a multi-node wireless cluster network is presented. It is assumed that the nodes operate in half-duplex mode and that channel information is available at the nodes. The proposed design involves solving a convex flow optimization problem on a fully connected graph that models the cluster network. A much simpler generalized routing protocol based on the above design is also presented. Both the proposed flow-optimized protocol and the generalized routing protocol are shown to achieve the optimal diversity-multiplexing tradeoff for the cluster network. Moreover, simulation results are presented to quantify the gap between the performance of the proposed protocols and that of a max-flow-min-cut type bound, in terms of outage probability.

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.

The problem of state estimation with initial state uncertainty is approached from a statistical decision theory point of view. The initial state is regarded as deterministic and unknown. It is only known that the initial state vector belongs to a specified parameter set. The (frequentist) risk is considered as the performance measure and the minimax approach is adopted. Minimax estimators are derived for some important cases of unbounded parameter sets. If the parameter set is bounded, a method of finding estimators whose maximum risk is arbitrarily close to that of a minimax estimator is provided. This method is illustrated with an example in which an estimator whose maximum risk is at most 3% larger than that of a minimax estimator is derived.

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.

The problem of linear tracking of fast Rayleigh-faded MIMO channels is considered. Due to computational complexity limitations, Kalman filters based on low-order autoregressive (AR) models are often used although realistic Rayleigh-faded channels cannot be properly approximated by low-order AR models. By increasing the order of the AR model, the channel tracking performance is considerably improved, but the resulting computational complexity may become large. In this paper, the filters used to track the channel are restricted to have a recursive structure, based on the previous estimate and new observation. The knowledge of the autocorrelation function of the channel taps is used to derive filters that are significantly less complex than high-order AR model based Kalman filters at the price of only a minor degradation in performance.

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).

In this paper, we present a low complexity turbo equalization receiver for data transmission over time-varying frequency-selective fading channels. In the receiver, an adaptive equalizer using nonlinear Kalman filters with delay is coupled with a soft-in soft-cut (SISO) decoder to perform the reception process iteratively. The proposed adaptive equalizer jointly optimizes the estimates for channel taps and data symbols in each iteration with the assistance of a priori information for the data symbols supplied by the SISO decoder. In this way, the correlation between the estimates of data symbols and channel taps is taken into account in the equalization process. This correlation is usually ignored in many other turbo equalizers with separated channel estimation and data equalization. The complexity of the proposed equalizer does not grow exponentially with the modulation constellation size, and is usually lower than that of many maximum a posteriori equalizers with joint channel estimation and data detection. Performance comparison with different types of turbo equalizers over different channel conditions by Monte Carlo simulations demonstrates the advantage of the proposed turbo equalizer for fast time-varying fading channels

In this paper, we present a low complexity turbo equalization receiver for data transmission over time-varying frequency-selective fading channels. In the receiver, a fixed-lag Kalman equalizer jointly estimates the channel and equalizes the data symbols with the assistance of a priori information supplied by the decoder. The complexity of the proposed equalizer does not grow exponentially with the modulation constellation size, and is usually lower than that of many maximum a posteriori equalizers performing joint channel estimation and detection. Performance comparison with different types of turbo equalizers demonstrates the advantage of the proposed turbo equalizer

In this paper, we investigate the timing acquisition problem for transmitted reference (TR) ultra-wideband systems employing direct-sequence (DS) spreading. We show that a two-level DS signaling helps in achieving good acquisition performance. We propose a two-stage acquisition scheme which exploits the TR signal structure to achieve a significant improvement in the mean detection time performance when compared with a conventional single-stage acquisition scheme.

It has been shown that distributed turbo coding (DTC) can approach the capacity of a wireless relay network. In the existing DTC schemes, it is usually assumed that error-free decoding is performed at a relay. We refer to this type of DTC schemes as perfect DTC. In this paper, we propose a novel DTC scheme. For the proposed scheme, instead of making a decision on the transmitted information symbols at the relay as in perfect DTC, we calculate and forward the corresponding soft information. We derive parity symbol soft estimates for the interleaved source information when only the a posteriori probabilities of the information symbols are known. The results show that the proposed scheme can effectively mitigate error propagation due to erroneous decoding at the relay. Simulation results also confirm that the proposed scheme approaches the outage probability bound of a distributed two-hop relay network at high signal-to-noise ratios

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

The acquisition of ultra-wideband (UWB) signals is a potential bottleneck for system throughput in a packet-based network employing UWB signaling format in the physical layer. The problem is mainly due to the low received signal power and the fine time resolution which forces the acquisition system to process the signal over long periods of time before getting a reliable estimate of the timing of the signal. Hence, there is a need to develop more efficient acquisition schemes by taking into account the signal and channel characteristics. In this paper, we investigate two approaches, the square-and-integrate and the integrate-and-square, which collect the energy in the multipaths by performing equal-gain combining (EGC) to improve the acquisition performance. We define the hit set as the set of hypothesized phases which can guarantee adequate system performance after acquisition, and also study the effect of the EGC window length on the acquisition performance.

The usage of long spreading sequences and the fine timing resolution result in a large search space during acquisition in ultra-wideband (UWB) systems. This paper presents a two-stage signal acquisition scheme for UWB systems employing a hybrid signaling format involving direct sequence (DS) spreading and time hopping (TH), which significantly reduces the search space. The resulting acquisition system consists of two stages, one each for the acquisition of the TH and DS sequences. The dense multipath channel typical of UWB systems implies that there can exist more than one phase to which the receiver can lock on and achieve satisfactory demodulation performance subsequent to acquisition. We define the set of such phases as the hit set. The hybrid signaling format coupled with the multi-phase hit set help significantly improve the acquisition performance of the UWB system. The performance of the proposed acquisition system, measured in terms of the mean detection time, is evaluated analytically and supported by computer simulation

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.

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.

The IEEE 802.11 standard defines two coordination functions: distributed coordination function (DCF) and point coordination function (PCF). These coordination functions coordinate the shared wireless medium. The PCF uses a centralized polling-based channel access method to support time-bounded services. To design an efficient polling scheme, the point coordinator (PC) needs to obtain information about the current transmission status and channel condition for each station. To reduce overhead caused by polling frames, it is better to poll all stations using one polling frame containing the transmission schedule. In this paper, we propose an efficient polling scheme, referred to as two-step multipolling (TS-MP), for the PCF in wireless local area networks (WLANs). In this new scheme, we propose to use two multipolling frames with different purposes. The first frame is broadcast to collect information such as the numbers of pending frames and the physical-layer transmission rates for the communication links among all stations. The second frame contains a polling sequence for data transmissions designed based on the collected information. This frame is broadcast to all stations. Extensive simulation studies show that TS-MP not only overcomes the aforementioned deficiencies, but also help to implement rate adaptation over time-varying wireless channel.

The ultra-wideband (UWB) channel is characterized by the presence of dense multipath and robustness to multipath fading. By taking system performance subsequent to acquisition into account, it was shown recently that there are multiple phases (called the hit set) where a receiver lock can be considered as successful acquisition. In this case, the serial search may no longer be the optimal choice for the sequential search strategy in the acquisition system. In this letter, we consider the problem of finding better search strategies in the set of all search strategies which are permutations of the search space. The large size of the search space and the absence of any exploitable structure make the problem of finding the permutation search strategy which minimizes the mean detection time prohibitively complex. However, if we take the first-order approximation that the probabilities of detection of all the hit-set phases are equal, then there exists a permutation search strategy which minimizes the mean detection time. Since the actual probabilities of detection are not equal, this search strategy, although not optimal, serves as a useful heuristic solution to an otherwise intractable problem. Furthermore, we see that this search strategy has a simple Jump-by-H structure, and improves the mean detection time by a significant amount compared with the serial search.

The asymptotic performance of timing acquisition systems having fixed dwell time in multipath fading channels is investigated. The detrimental effect of the multipath channel fading on the acquisition performance is isolated by considering the asymptotic performance as the average signal-to-noise ratio (SNR) increases. It is found that for any threshold such that the average probability of false alarm is less than a given tolerance, the channel fading results in a lower bound on the asymptotic average probability of miss which is nontrivial for a variety of fading scenarios. A threshold-based direct-sequence spread-spectrum signal acquisition system is considered and it is found that the detrimental effect of channel fading on asymptotic acquisition performance, albeit nontrivial, is not very significant. The asymptotic acquisition performance of two threshold-based acquisition schemes for ultra-wideband (UWB) signals with time-hopping (TH) spreading are also evaluated and compared. For both schemes, the detrimental effect of the channel fading on the asymptotic acquisition performance turns out to be significant.

We present an orthogonal frequency-division multiplexing (OFDM) system with bit-interleaved space-frequency coded modulation for frequency-selective fading channels employing multiple transmit and receive antennas. OFDM is used to transform a frequency-selective fading channel into multiple flat fading channels, and space-frequency trellis coding combined with bit-interleaving is used to exploit space and frequency diversity. The performance of such an approach is evaluated by analytical bounds and simulation. The proposed scheme is an efficient method to employ multiple transmit antennas to increase the data rate and, at the same time, improve the performance by means of increased diversity obtained with bit-interleaved coded modulation and multiple receive antennas. A block precoding method is proposed to further improve the diversity order. An efficient sphere decoding algorithm is also developed for reducing the decoding complexity of the proposed scheme.

The IEEE 802.11 standard defines a centralized polling-based channel access method, the point coordination function (PCF), to support time-bounded services. In this paper, we propose an efficient polling scheme, referred to as two-step multipolling (TS-MP), for the PCF in WLANs. In this new scheme, we propose to use two multi-polling frames for different purposes. The first frame is broadcasted to collect information such as the numbers of pending frames and the physical layer transmission rates for the communication links among all stations. The second frame is broadcasted with a polling sequence for data transmissions designed by utilizing the collected information. Extensive simulation studies show that TS-MP not only overcomes PCFs deficiencies, but also helps to implement rate adaptation over a time-varying wireless channel.

Wireless sensor networks (WSNs) are appealing in obtaining fine-granular observations about the physical world. Due to the fact that WSNs are composed of a large number of low-cost but energy-constrained sensor nodes, along with the notorious time-varying and error-prone nature of wireless links, scalable, robust, and energy-efficient data disseminating techniques are requisite for the emerging WSN applications such as environment monitoring and surveillance. To meet this challenging demand, we propose a hybrid data dissemination framework for WSNs in this paper. In particular, we conceptually partition a whole sensor field into several functional regions and apply different routing schemes to different regions in order to provide better performance in terms of reliability and fair energy usage. For this purpose, we also propose a novel zone flooding scheme, essentially a combination of geometric routing and flooding techniques. Our scheme features low overhead, high reliability, good scalability, and notable flexibility. Simulation studies are carried out to validate the effectiveness and efficiency of our scheme.

We address the problem of optimal training sequence design for MIMO systems over frequency flat fading channels in the presence of colored interference that is composed of the thermal noise and jamming signals transmitted by multiple jammers. We employ a training based channel estimation approach. During the training period, we obtain the information of the channel parameters by using a Bayesian (MMSE) channel estimator based on the received training block. We note that the mean square error (MSE) of the channel estimator depends on the choice of the training sequence set. We design the optimal training sequence set that minimizes the MSE of the channel estimator under a total transmit power constraint. In order to obtain the advantage of the optimal training sequence design, the transmitter requires long-term statistics of the interference correlation. Hence this information needs to be estimated at the receiver and fed back to the transmitter. We develop a feedback strategy that can reduce the estimation error of the short-term channel parameters with a minimal amount of information from the receiver.

The problem of estimating the location and time of origin of an instantaneous source of a particular gas using a simple sensor network is investigated in this paper. Here, the gas spreads by diffusion and the sensors make a binary decision on the existence of the gas by measuring its concentration in their immediate vicinity. The inability of the sensors to go beyond a binary resolution of the concentration justifies their classification as dumb. In this paper, it is restricted to the one-dimensional case where the sensors form a linear array. The analysis of the Cramer-Rao bound (CRB) to study the limits of estimation performance is numerically calculated. Based on the number of gas molecules the Poisson distribution by a Gaussian distribution with mean and variance is approximated.

In this paper, we investigate the asymptotic performance of threshold-based timing acquisition systems having fixed dwell time in multipath fading channels. We show that if the system involves the comparison of a decision statistic to a threshold in order to detect the true symbol timing, then it may not be possible to make the average probability of error in acquisition arbitrarily small, even if the signal-to-noise ratio increases without bound.

Low transmission power and a highly spread bandwidth makes the acquisition of ultra-wideband (UWB) signals a difficult problem. In a packet-based network employing UWB modulation in the physical layer, long preambles need to be prepended to each packet because the low signal power requires the receiver to process the signal for long periods of time in order to estimate the timing of the signal. The long spreading or hopping sequences used in UWB systems result in a large search space for the acquisition system at the receiver. This work presents a signal acquisition system for UWB which employs a hybrid signaling format involving direct sequence (DS) spreading and time hopping (TH), significantly reducing the search space in the UWB acquisition system. The acquisition system employs equal gain combining (EGC) which enables the utilization of the energy of the dense multipath, typical of a UWB channel. The performance of the acquisition system has been analytically evaluated and is corroborated through simulation.

The specification of high-rate wireless personal area network (HR WPAN) has been standardized by the IEEE 802.15.3 task group for communications of consumer electronics and portable communication devices and a final draft standard has been completed. The physical layer in IEEE 802.15.3 standard is designed to achieve data rates of 11-55Mbps. However, a MAC protocol in IEEE 802.15.3 standard does not specify the method to choose an appropriate data rate. In this paper, we propose a rate-adaptive medium access control (MAC) protocol for HR WPAN. The data rate for the next transmission is selected by channel prediction based on the currently received frame and informs the sender about the changed rate using a rate-adaptive acknowledgement (RA-ACK) frame. By overhearing the RA-ACK frame, a piconet controller can efficiently allocate channel times. In addition, we propose a constant physical layer frame length regardless of a data rate. In this way, the channel can be more effectively utilized by squeezing more bits into one transmission. The proposed scheme is evaluated under a time-correlated fading channel model in terms of the achieved throughput Simulation results show that this scheme achieves a much higher throughput than a non rate-adaptive MAC protocol in HR WPAN does.

We address the problems of channel estimation and optimal training sequence design for multiple-input multiple-output systems over flat fading channels in the presence of colored interference. In practice, knowledge of the unknown channel is often obtained by sending known training symbols to the receiver. During the training period, we obtain the best linear unbiased estimates of the channel parameters based on the received training block. We determine the optimal training sequence set that minimizes the mean square error of the channel estimator under a total transmit power constraint. In order to obtain the advantage of the optimal training sequence design, long-term statistics of the interference correlation are needed at the transmitter. Hence, this information needs to be estimated at the receiver and fed back to the transmitter. Obviously it is desirable that only a minimal amount of information needs to be fed back from the receiver to gain the advantage in reducing the estimation error of the short-term channel fading parameters. We develop such a feedback strategy in this paper.

In this paper, we consider power control and sequence allocation to meet signal-to-interference ratio (SIR) targets for users in a code-division multiple-access (CDMA) forward link. Particular attention is given to the case when the number of users is larger than the spreading gain. Users in the system are classified into two classes, namely, overfaded users and nonoverfaded users, according to their effective noise densities and SIR targets. Overfaded users are allocated orthogonal channels, and nonoverfaded users share the remaining channels. The spreading sequences allocated belong to the class of sequences which minimize the extended total squared correlation (ETSC). Power efficiency of this allocation scheme is examined through comparison to Lagrangian-based searching results. The proposed allocation scheme is shown to be effective under most channel conditions. Two adaptive algorithms are presented to construct the spreading sequences iteratively. One assumes fixed power allocation and adapts the sequences only, and the other adapts both transmission powers and sequences simultaneously. Convergence of the two adaptive algorithms and the performance of joint transmitter-receiver adaptation with imperfect real-time channel parameters estimation are examined via computer simulations.

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.

We present an orthogonal frequency-division multiplexing (OFDM) system with bit-interleaved space-frequency coded modulation for frequency selective fading channels employing multiple transmit and receive antenna. OFDM is used to transform a frequency selective fading channel into multiple flat fading channels, and space-frequency trellis coding combined with bit-interleaving is used to exploit space and frequency diversity. The performance of such an approach is evaluated by analytical bounds and simulation. With the use of space-frequency coding and BICM, we can provide increased rates and also improved performance by means of increased diversity.

Many rate-adaptive MAC protocols have been proposed in the past for wireless LANs over time-varying media to provide efficient channel usage and throughput enhancement. Most of these protocols are receiver-based and employ RTS/CTS collision avoidance handshakes specified in the distributed coordination function (DCF) of the IEEE802.11 MAC. However, these protocols do not consider the possible bursty transmission of fragments in a rate-adaptive fashion. In this paper, a rate-adaptive protocol with a dynamic fragmentation scheme is proposed in order to enhance the throughput by employing bursty fragment transmissions based on the channel condition. Instead of using one fragmentation threshold, multiple thresholds for different data rates are proposed so that more data can be transmitted at higher data rates when the channel is good. In the fragmentation scheme of IEEE802.11, all fragments are generated with equal size at the same time, and all fragments will not change until they are transmitted. In our proposed scheme, whenever the rate for the next transmission is chosen based on the channel condition estimated from the previous fragment transmission, a new fragment is generated using the fragment threshold for the new rate. In this way, the channel can be more effectively utilized to squeeze in more bits. This scheme is evaluated under a time-correlated fading channel model in terms of the achieved throughput. Simulation results show that this scheme achieves a much higher throughput than other rate-adaptive protocols do.

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.

The performance of several linear multiuser receivers including the matched filter receiver, the decorrelator receiver, and the MMSE receiver has been analyzed in CDMA systems with random sequences. Little work has been done for nonlinear decision feedback receivers. In this paper, we extend the results for linear multiuser receivers to an asynchronous CDMA system with an adaptive decision-feedback detector (DFD). The performance of the DFD using both deterministic sequences and random sequences is analyzed. With the assumption of perfect feedback (i.e., the receiver always makes correct decisions), the feedback part of the adaptive DFD can suppress the interference due to the previous symbols of all users completely and correspondingly the user capacity of the whole system increases greatly when compared with a system using an MMSE receiver.

A joint transmitter-receiver adaptive DS-CDMA system over a slow flat fading forward-link channel is considered. A set of spreading sequences is designed to support all users with a uniform target SIR. This set of sequences reduces to the optimum solution of the transmitter optimization problem of choosing a set of sequences to meet the SIR target with a minimum total transmission power when the channel reduces to an AWGN channel. The MMSE receiver is employed for signal reception and receiver weights of each user are adapted independently and simultaneously without information from other users. Estimates of the MSE at each receiver are sent back to the base-station. An adaptive algorithm is designed to estimate channel parameters using the feedback information and update the spreading sequences at the base-station. The algorithm gives a set of sequences which satisfies the target SIR and has total transmission power close to the theoretical total power after a moderate number of iterations. Simulation results show that performance improvement can be achieved with the proposed joint adaptation scheme.

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.

In this paper, maximum a posteriori (MAP) detection is applied to a direct-sequence code-division multiple-access (DS-CDMA) system jointly with identification and estimation of time-selective fading channels. By sampling the outputs of the matched filter and combining antenna array elements, strong and time-varying multiple-access interference (MAI) is characterized and suppressed instantaneously. The decision statistics for MAP detection are obtained from the conditional probability density function of the prediction error. The prediction is accomplished by approximating the fading channel with a constrained nonlinear state model. Unknown parameters such as auto-regressive (AR) process coefficients, noise covariance matrices, and the antenna array vector are estimated based on received sample vectors only. Also, differential modulation is applied to eliminate the need for pilot insertion. Through computer simulations, near-optimum bit error rates (BERs) are found.

The problem of transmitter adaptation in the form of adapting the spreading sequences and the transmission powers of different users for a multicode direct-sequence code division multiple access (DS-CDMA) system is considered. Particular attention is given to a distributed algorithm, which updates each pair of transmitter and receiver without information from other users. The transmitter adaptation problem and the algorithm are studied from the viewpoint of a single user, as well as the viewpoint of the whole system. The algorithm is shown to give either the optimal sequences or a choice of sequences that is close to the optimal one. Simulation results show that major improvement in performance can be obtained with the proposed transmission adaptation scheme. The effect of restricting the choice of sequences to polyphase sequences is also considered.

The problem of adapting the spreading sequences and the transmission powers of different users in a multicode direct-sequence code division multiple access (DS-CDMA) system is considered. Particular attention is given to a distributed algorithm which updates each pair of transmitter and receiver without information from other users. The sequence adaptation problem and the algorithm are studied from from the viewpoint of a single user as well as the viewpoint of the whole system. The algorithm is shown to give either the optimal sequences or sequences that are close to the optimal ones. The effect of restricting the choice of sequences to polyphase sequences is also considered.

A single-user adaptive multicode CDMA system over AWGN channels is presented. The adaptive system involves joint transmitter-receiver adaptation which allows the desired user to achieve a designated signal-to-noise ratio (SNR) with minimum transmission power. We assume that the adaptive transmitter and receiver have no prior knowledge of the spreading sequences of other users. During the training period, the receiver weights are adapted based on the RLS algorithm. Information about the MMSE error and weights collected at the receiver is employed to update the spreading sequences, which are fed back to the transmitter for the transmission of the next block of data. Simulation results show that both the transmitter and receiver can converge to the optimal solution. The proposed implementation is also shown to be immune to feedback delay.

In this paper, we consider fixed wireless access (FWA) systems with antenna arrays. We consider both the downlink and the uplink. Multiple antennas are used at the transmitters, as well as the receivers. We demonstrate that with antenna arrays, the user capacity of a system can be dramatically increased, allowing multiple users to use the same narrowband spectrum simultaneously. In general, it may be difficult to determine the optimal transmission vectors. We consider a simple algorithm that often yields desirable solutions. We also consider the special case of co-located users. The communication system then reduces to a point-to-point communication link where the optimal transmission vectors can be determined under some conditions.

We consider transmitter and receiver optimization in multicarrier code-division multiple-access (MC-CDMA) systems under Rayleigh fading channels. Receiver optimization is performed in a decentralized manner, while transmitter optimization can be performed through either centralized or decentralized control of the powers of different carriers. Results show that when the number of users is smaller than or equal to the number of carriers, each transmitter often tends to concentrate its power on a different carrier which does not suffer deep fading. The MC-CDMA system then tends to a frequency-division multiple-access system with near-optimal frequency assignment. When the number of users gets large, each user tends to choose more than one carrier, which do not suffer deep fading, while interference suppression is performed across the chosen carriers by the corresponding receiver.

A subspace-based linear minimum mean-squared error (MMSE) multiuser detection scheme is proposed for a multicarrier direct-sequence code-division multiple-access (MC-DS-CDMA) system. Typically, a MC-DS-CDMA system employs a band-limited chip waveform. The band-limited nature of the chip waveform causes problem in applying standard subspace techniques because no nonnull noise subspace can be formed. It is shown that channel and timing information needed for the construction of the linear MMSE detector can be identified by a multiple-signal-classification-like algorithm based on a finite-length truncation approximation of the chip waveform. In practice, since perturbed versions of the subspaces assumed in the finite-length truncation approximation are actually observed, and because of the band-limited property of the chip waveform, the accuracy of the channel estimation and, hence, the performance of the MMSE detector are degraded. This effect is investigated in this paper.

A decision-feedback maximum a posteriori (MAP) receiver is proposed for code-division multiple-access channels with time-selective fading. The receiver consists of a sequence-matched filter and a MAP demodulator. Output samples (more than one per symbol) from the matched filter are fed into the MAP demodulator. The MAP demodulator exploits the channel memory by delaying the decision and using a sequence of observations. This receiver also rejects multiple-access interference and estimates channel fading coefficients implicitly to give good demodulation decisions. Moreover, computer simulations are performed to evaluate the bit-error rate performance of the receiver under various channel conditions.

In this paper, we consider transmitter and receiver optimization in multicarrier code division multiple access (MC CDMA) systems. Receiver optimization is performed in a decentralized manner while transmitter optimization is performed through centralized control of the power of different carriers. Results show that when the number of users is smaller than or equal to the number of carriers, each transmitter should concentrate its power on a different carrier which does not suffer deep fading. The MC-CDMA system then tends to a frequency division multiple access system with near optimal frequency assignment. When the number of users gets large, each user tends to choose more than one carriers, which do not suffer deep fading, while interference suppression is performed across the chosen carriers by the corresponding receiver.

We consider subspace-based MMSE multiuser detection for multicarrier code division multiple access (MC-CDMA) in Rayleigh fading channels. The knowledge of the fading coefficients for all the carriers and the timing delay of the desired user is needed to construct the MMSE detector. A subspace-based channel estimation technique is developed to obtain the required information. Numerical results show that the proposed algorithm is robust to fading and moderate near-far situations.

The application of maximum a posteriori (MAP) detection to DS-CDMA systems in time-selective fading channels is investigated. By sampling the outputs of a matched filter and combining antenna array elements, strong multiple-access interference (MAI) is estimated and suppressed. By incorporating channel approximations, Kalman filtering, and the probability density of the prediction error, a joint channel estimation and MAP detection algorithm is developed. Unknown channel parameters are identified by using an algorithm similar to the extended Kalman filter (EKF). Also, differential modulation is applied to eliminate the need for pilot insertion. Through computer simulations, a near-optimum bit-error-rate (BER) performance is found.

We consider signal reception in multicarrier code-division multiple-access (MC-CDMA) systems. A blind adaptive algorithm is proposed to determine a weight vector which optimally combines the desired signal contributions from different carriers while suppressing noise and interference. No knowledge of the channel conditions (fading coefficients, signature sequences and timing of interferers, statistics of other noises, etc.) nor any training sequence is required. The performance is examined for Rayleigh fading channels. Results show that the proposed algorithm performs well and is robust to the near-far problem. Hence, the results show that MC-CDMA systems are attractive candidates for future CDMA systems.

A linear decentralized receiver capable of suppressing multiple-access interference (MAI) for asynchronous direct-sequence code-division multiple-access (DS-CDMA) systems with aperiodic random signature sequences is proposed. Performance bounds on this receiver are also obtained. Using them as performance measures, the problem of chip waveform selection in DS-CDMA systems with the proposed receiver under the near-far scenario is investigated. In particular, the performance of several practical chip waveforms is compared. An LMS-type adaptive algorithm is developed to obtain the parameters needed in the receiver, which only requires the signature sequence and coarse timing information of the desired user.

The application of a type-II hybrid ARQ protocol in a slotted direct-sequence spread-spectrum multiple-access (DS-SSMA) packet radio system is investigated. Both the static performance and the dynamic performance of such a system are analyzed. In the physical layer, packet error and packet success probabilities are computed using the improved Gaussian approximation technique, which accounts for the bit-to-bit error dependence within a packet. In the data-link layer, two-dimensional Markov chains are employed to model the system dynamics. Based on this model, the performance of the type-II hybrid ARQ protocol is upper and lower bounded by considering, respectively, a superior scheme and an inferior scheme. Steady state throughput and delay performances of the two bounding schemes are obtained. Moreover, it is shown that for each fixed input load, there is an optimal retransmission probability under the finite user population assumption. Bounds on this optimal retransmission probability are also given.

The stability of a slotted direct-sequence spread-spectrum multiple-access (DS-SSMA) packet radio network employing a type-II hybrid automatic-repeat-request (ARQ) protocol is considered. The equilibrium point analysis (EPA) technique is employed to approximately compute the system throughput and delay, and to analyze the system stability. It is found that the system exhibits bistable behavior in some situations. With this information, a desirable region of operation for the DS-SSMA network employing the type-II hybrid ARQ protocol is obtained.

A linear receiver for direct-sequence spread-spectrum multiple-access communication systems under the aperiodic random sequence model is considered. The receiver consists of the conventional matched filter followed by a tapped delay line with the provision of incorporating the use of antenna arrays. It has the ability of suppressing multiple-access interference (MAI) and narrowband interference in some weighted proportions, as well as combining multipath components without explicit estimation of any channel conditions. Under some specific simplified channel models, the receiver reduces to the minimum variance distortionless response beamformer, the RAKE receiver, a notch filter, or an MAI suppressor. The interference rejection capability is made possible through a suitable choice of weights in the tapped delay line. The optimal weights can be obtained by straightforward but computationally complex eigenanalysis. In order to reduce the computational complexity, a simple blind adaptive algorithm is also developed.