In this paper, we propose a platoon access authentication system for initial access process in autonomous vehicle platoons (AVPs) in which post-quantum encryption and signal processing techniques are employed to protect against both active and passive cyber-physical attacks. To avoid passive quantum cyber attacks, a quasi-cyclic moderate-density parity-check code is used to encode and decode AVP messages. Moreover, an independent component analysis-based signal separation technique is employed to eliminate the effect of high-power active cyber attacks on AVP messages. To measure the reliability of the system, we derive an analytical expression for the system failure probability, taking into account the influence of both the cyber and physical planes. The simulations show that the proposed system is effective against attacks and can help reduce system failures caused by intentional and unintentional adverse cyber-physical effects. The proposed system offers a potential solution to the challenge of protecting initial access while maintaining ultra-reliable low-latency communications between AVPs and the infrastructure.

Machine learning models that use deep neural networks (DNNs) are vulnerable to backdoor attacks. An adversary carrying out a backdoor attack embeds a predefined perturbation called a trigger into a small subset of input samples and trains the DNN such that the presence of the trigger in the input results in an adversary-desired output class. Such adversarial retraining however needs to ensure that outputs for inputs without the trigger remain unaffected and provide high classification accuracy on clean samples. Existing defenses against backdoor attacks are computationally expensive, and their success has been demonstrated primarily on image-based inputs. The increasing popularity of deploying pretrained DNNs to reduce costs of re/training large models makes defense mechanisms that aim to detect 'suspicious' input samples preferable.

The reduced-capability new radio (NR RedCap) was introduced in 3GPP Rel-17 to cater to the use cases that are not yet best served by current NR specifications, such as smart grid and industrial wireless sensors. For the grant-free access system in smart grid, the resistance to impulse noise is a key issue. By using fractional low-order covariance and constant modulus based tensor decomposition, this paper skillfully enables user identification in this scenario while suppressing the effect of impulse noise. The proposed scheme uses spread spectrum signal as the pilot signal. And the user identity is represented jointly by the spread spectrum sequence and information codes. In this condition, we start by transforming the pilot signals into a tensor. The fractional low-order covariance is then used to suppress the impulse noise, and the constant modulus is used to improve the performance of the algorithm during the iterative process of tensor decomposition. Finally the sensor identity is confirmed by the decomposition result. Simulation results show that the proposed scheme can greatly improve the performance of user identification under impulse noise channel. Specifically, the identification rate of the proposed algorithm valued 99.815% outperformed that of AMP valued 89.1471% when generalized signal-to-noise ratio GSNR = 0 dB. In addition, the proposed scheme can also correctly estimate the channel gain from the sensors to the base station in impulsive noise environment.

For the grant-free random access system in the Internet of Thing (IoT) scenario, the recovery of the pilot sequence and the identification of the IoT device is a crucial issue. Contrapose the problem that the existing grant-free access schemes cannot accurately recover the pilot sequence in the intensive industrial zone with impulse noise, this paper proposes to use spread spectrum signal as pilot signal and proposes an estimation algorithm based on joint k-means and M estimation accordingly. This algorithm dynamically suppresses the influence of noise with adaptive weighted function according to the estimated noise energy in the iterative process. First, the received signal is segmented to obtain samples. Second, the samples are clustered using the K-means algorithm. In the iterative process of the algorithm, cluster centers are used to estimate the energy of signal noise. According to the estimation result of the noise energy, the adaptive weighted function is used to dynamically update the cluster centers and the similarity between samples and cluster centers. Finally, assigning +1 or −1 to the samples according to the clustering results, and then the estimation of pseudo-code sequence (PN sequence) is realized while impulse noise is suppressed. Simulation results show that the proposed algorithm can greatly improve the performance of PN sequence estimation under impulse noise channel. The bit error ratio (BER) of the proposed algorithm valued 0.008 outperformed that of EVD valued 0.3 when the generalized signal-to-noise ratio (GSNR) is −4dB. In particular, the proposed algorithm has better performance when the noise distribution has heavier tails, which is different from traditional algorithms.

Secure ultrareliable low-latency communication (URLLC) has become a crucial requirement of mission-critical Internet of Things (IoT) applications and use cases, including automotive driving, remote surgery, and many others. However, it is still challenging to protect initial access of massive IoT devices over wireless channels, especially when malicious quantum adversaries paralyze the initial access by overhearing and tampering critical wireless messages, i.e., preambles. We propose a nested hash access system with post-quantum encryption to solve this issue. The system performs random repetition coding and nested hash coding on multidomain physical-layer resources to encode and decode preambles precisely and resiliently. Particularly, a subtle compression and encryption mechanism based on quasi-cyclic (QC)-moderate-density parity-check (MDPC) code is proposed between repetition and hashing operations to avoid passive eavesdropping during the preamble encoding process. We show that the code information can be maintained at 128-bit or higher privacy level, depending on the length of repetition code. Besides, the preamble decoding process can be proved secure agaisnt active attacks with a tolerable loss of decoding errors. Then, we formulate two nonconvex integer programming problems, each problem corresponding to the minimization of upper bound of preamble decoding error in an example application scenario. Finally, we can derive the expressions of system failure probability to evaluate the reliability of URLLC system under mission-critical IoT scenarios. Simulation results show the effectiveness of our proposed scheme despite attack.

One of the greatest challenges in vehicle-to-everything(V2X) communications lies in protecting vehicle authentication during initial access against advanced quantum cyber-physical attack (CPA), as well as maintaining ultra-reliable low-latency communications with each other and the infrastructure. In this paper, we propose a vehicle initial access authentication system which exploits post-quantum encryption and signal processing technique to defend against both active and passive quantum CPA. The system encodes/decodes the physical layer bits of messages using quasi-cyclic moderate-density parity-check code to avoid quantum passive cyber attacks while eliminating the influence of high-power active cyber attacks on bits by employing the independent component analysis based signal separation technique. We define the system failure probability to measure the reliability, by considering both the cyber and physical plane influence, such as asynchronous access delay caused by mobility and communications, wireless channel fading and the uncertain bit generation induced by traffic hazards. Simulations show the effectiveness of our proposed system against attacks and indicate how the adverse cyber-physical effects, either being intentional or unintentional, can be avoided subtly to reduce system failures.

Industrial Internet of Things (IIoT), a core enabler of Industry 4.0, is evolving rapidly to tackle the challenges imposed by explosive real-time manufacturing data in the context of Internet and telecommunication industry. 5G technology is the key to addressing such challenges. This is done by bypassing upper authentication protocols and supporting small data transmission during initial access, which, however, causes serious security breaches in IIoT device authentication. To solve this, in this article propose a secure cross-layer authentication framework based on quantum walk on circles. The system performs random hash coding on multidomain physical-layer resources to encode and decode device identifiers securely, while using a quantum walk based privacy-preserving protocol to maintain code privacy at arbitrary high level, being controlled by the number of occupied physical resources. The upper bound of decoding errors is derived and a nonconvex integer programming problem of minimizing the bound is formulated to characterize the security performance. The space of one-time keys for encryption is also derived that show how high privacy and scalability advantage is maintained against classical and quantum computers. Finally, we derive novel expressions of failure probability of this new authentication system and numerically show that our scheme can bring ultrahigh level of security and privacy protection with low latency despite attack.

Wireless channel state information (CSI) from intelligent vehicles to the roadside unit (RSU) is a must for vehicleto-infrastructure (V2I) communications in Internet of Vehicles, but easily suffers the risks of being attacked due to the publicly known and deterministic characteristic of PHY-layer pilots that are employed for CSI acquisition. This incurs the issue of wireless pilot authentication (WPA), that is, verifying the authenticity of pilots and claimed CSIs. In this paper, we, for multiantenna V2I orthogonal frequency division multiplexed communications, develop a PHY-layer cover-free (PHY-CF) coding theory to build up a secure WPA (SWPA) protocol. Here, we encode and convey vehicle pilot signals into diversified subcarrier activation patterns (SAPs) on the time-frequency domain by employing cover-free coding. We redesign the decoding procedure using the signal independence characteristic such that those encoded SAPs, though camouflaged by malicious signals and superimposed onto each other in wireless environment, could be separated, identified and decoded into the original pilots securely. For this protocol, we prove that perfect pilot conveying and separation could be both guaranteed. We formulate the pilot identification error probability (IEP) and show how PHY-CF coding could help position the location of attacker and reduce IEP to further achieve ultrasecurity. Considering 20 MHz long-term evolution bandwidth, we prove that the number of co-time co-frequency vehicles that are securely authenticated achieves up to 19 × X for X serving sectors of base station type RSU and the latency time of uplink data access is up to 1.5 ms, thus furthering the autonomous driving. Computer simulations comprehensively verify those benefits of proposed SWPA protocol.

In wireless orthogonal frequency-division multiplexing communications systems, pilot tones, due to their publicly known and deterministic characteristic, suffer significant jamming/nulling/spoofing risks. Thus, the convectional channel training protocol using pilot tones could be attacked and paralyzed, which raises the issue of anti-attack channel training authentication (CTA), i.e., verifying the claims of identities of pilot tones and channel estimation samples. In this paper, we consider one-ring scattering scenarios with large-scale uniform linear arrays (ULA) and develop an independence-checking coding (ICC) theory to build a secure and stable CTA protocol, namely, ICC-based CTA (ICC-CTA) protocol. In this protocol, the pilot tones are not only merely randomized and inserted into subcarriers but also encoded as diversified subcarrier activation patterns (SAPs) simultaneously. Those encoded SAPs, though camouflaged by malicious signals, can be identified and decoded into original pilots for high-accuracy channel impulse response (CIR) estimation. The CTA security is first characterized by the error probability of identifying legitimate CIR estimation samples. We prove that the identification error probability (IEP) is equal to zero under the continuously distributed mean angle of arrival (AoA) and also derive a closed-form expression of IEP under the discretely distributed case. The CTA instability is formulated as the function of probability of stably estimating CIR against all available diversified SAPs. A realistic tradeoff between the CTA security and instability under the discretely distributed AoA is identified and an optimally stable tradeoff problem is formulated, with the objective of optimizing the code rate to maximize security while maintaining maximum stability for ever. Solving this, we derive the closed-form expression of optimal code rate. Numerical results finally validate the resilience of proposed ICC-CTA protocol.

Due to the publicly known and deterministic characteristic of pilot tones, pilot authentication (PA) in multi-user multi-antenna orthogonal frequency-division multiplexing systems is very susceptible to the jamming/nulling/spoofing behaviors. To solve this, in this paper, we develop a hierarchical 2-D feature (H2DF) coding theory that exploits the hidden pilot signal features, i.e., the energy feature and independence feature, to secure pilot information coding which is applied between legitimate parties through a well-designed five-layer hierarchical coding model to achieve secure multiuser PA (SMPA). The reliability of SMPA is characterized using the identification error probability (IEP) of pilot encoding and decoding with the exact closed-form upper and lower bounds. However, this phenomenon of non-tight bounds brings about the risk of long-term instability in SMPA. Therefore, a reliability bound contraction theory is developed to shrink the bound interval, and practically, this is done by an easy-to-implement technique, namely, codebook partition within the H2DF code. In this process, a tradeoff between the upper and lower bounds of IEP is identified and a problem of optimal upper and lower bound tradeoff is formulated, with the objective of optimizing the cardinality of sub-codebooks such that the upper and lower bounds coincide. Solving this, we finally derive an exact closed-form expression for IEP, which realizes a stable and highly reliable SMPA. Numerical results validate the stability and resilience of H2DF coding in SMPA.

Due to the publicly-known deterministic character- istic of pilot tones, pilot-aware attack, by jamming, nulling and spoofing pilot tones, can significantly paralyze the uplink channel training in large-scale MISO-OFDM systems. To solve this, we in this paper develop an independence-checking coding based (ICCB) uplink training architecture for one-ring scattering scenarios allowing for uniform linear arrays (ULA) deployment. Here, we not only insert randomized pilots on subcarriers for channel impulse response (CIR) estimation, but also diversify and encode subcarrier activation patterns (SAPs) to convey those pilots simultaneously. The coded SAPs, though interfered by arbitrary unknown SAPs in wireless environment, are qualified to be reliably identified and decoded into the original pilots by checking the hidden channel independence existing in sub- carriers. Specifically, an independence-checking coding (ICC) theory is formulated to support the encoding/decoding process in this architecture. The optimal ICC code is further devel- oped for guaranteeing a well-imposed estimation of CIR while maximizing the code rate. Based on this code, the identification error probability (IEP) is characterized to evaluate the reliability of this architecture. Interestingly, we discover the principle of IEP reduction by exploiting the array spatial correlation, and prove that zero- IEP, i.e., perfect reliability, can be guaranteed under continuously-distributed mean angle of arrival (AoA). Besides this, a novel closed form of IEP expression is derived in discretely-distributed case. Simulation results finally verify the effectiveness of the proposed architecture.

Conventional time-division duplex (TDD) orthogonal frequency division multiplexing (TDD-OFDM) system is vulnerable to the pilot spoofing attack as it mainly relies on employing the deterministic pilot to capture the channel state information (CSI). To solve the abovementioned issue, we in this paper propose an independent component analysis (ICA) based channel identification and estimation (ICA-CIE) mechanism which uses randomized pilot to paralyze the pilot spoofing attack. Specifically, we first convert the pilot spoofing attack to the pilot jamming attack by exploiting pilot randomization. Then, an eigenstructure-based detector (EID) is proposed to realize efficient pilot jamming attack detection. In particular, on one hand, Least Square (LS) method is adopted if no jamming attack is detected. On the other hand, if jamming attack is detected, we further design a channelseparation oriented joint approximate diagonalization of eigenmatrices (CS-JADE) algorithm for channel estimation and identification. Therein, an optimization problem is first formulated to optimize the fourth-order statistical information of the observation data, after which a pilot signal reconstruction scheme is further developed to help identify true sub-channels from the optimization output. Simulation results demonstrate that our proposed ICA-CIE mechanism can achieve highly-accurate channel estimation for the legitimate transceiver pair only by using 6 OFDM symbols within the coherence time. Moreover, we also observe that the estimation accuracy of our proposed mechanism is immune to Eve's transmit power, which further verifies superiority of our proposed mechanism.

A pilot spoofer can paralyze the channel estimation in multi-user orthogonal frequency-division multiplexing (OFDM) systems by using the same publicly known pilot tones as legitimate nodes. This causes the problem of pilot authentication (PA). To solve this, we propose, for a two-user multi-antenna OFDM system, a code-frequency block group (CFBG) coding-based PA mechanism. Here multi-user pilot information, after being randomized independently to avoid being spoofed, is converted into activation patterns of subcarrier-block groups on code-frequency domain. Those patterns, though overlapped and interfered mutually in the wireless transmission environment, are qualified to be separated and identified as the original pilots with high accuracy, by exploiting CFBG coding theory and channel characteristic. Particularly, we develop the CFBG code through two steps, i.e., 1) devising an ordered signal detection technique to recognize the number of signals coexisting on each subcarrier block, and encoding each subcarrier block with the detected number and 2) constructing a zero-false-drop code and block detection-based code via k-dimensional Latin hypercubes and integrating those two codes into the CFBG code. This code can bring a desirable pilot separation error probability, inversely proportional to the number of occupied subcarriers and antennas with a power of k. To apply the code to PA, a scheme of pilot conveying, separation, and identification is proposed. Based on this novel PA, a joint channel estimation and identification mechanism is proposed to achieve high-precision channel recovery and simultaneously enhance PA without occupying extra resources. Simulation results verify the effectiveness of our proposed mechanism.

We in this paper introduce an advanced eavesdropper that aims to paralyze the artificial-noise-aided secure communications. We consider the M-1-2 Gaussian MISO wiretap channel, which consists of a M-antenna transmitter, a single-antenna receiver, and a two-antenna eavesdropper. This type of eavesdropper, by adopting an optimal Grassmann manifold (OGM) filtering structure, can reduce the maximum achievable secrecy rate (MASR) to be zero by using only two receive antennas, regardless of the number of antennas at the transmitter. Specifically, the eavesdropper exploits linear filters to serially recover the legitimate information symbols and intends to find the optimal filter that minimizes the mean-square error (MSE) in estimating the symbols. During the process, a convex semidefinite programming (SDP) problem with constraints on the filter matrix can be formulated and solved. Interestingly, the resulted optimal filters constitute a complex Grassmann manifold on the matrix space. Based on the filters, a novel expression of MASR is derived and further verified to be zero under the noiseless environment. Besides this, an achievable variable region (AVR) that induces zero MASR is presented analytically in the noisy case. Numerical results are provided to illustrate the huge disaster in the respect of secrecy rate.

We consider secure communications over MISO wiretap channels, in the presence of a passive eavesdropper with multiple antennas. In this scenario, an artificial-noise-resistant (ANR) eavesdropping behavior is introduced to invalidate the artificial noise (AN) scheme proposed by Goel et al. This novel eavesdropper, by exploiting the statistical filter derived from the collected signals, can completely eliminate the influence of AN by using only two receive antennas. In particular, the received signals are firstly syphered to eliminate the power influence of AN by a linear weight which is generated from the statistical estimation for the signal covariance matrix. In comparison with the original legitimate signals, the weighted signals are however imposed by a phase difference which can be then erased by a weight vector inferred from the available information at the eavesdropper. Based on the two filtering processes, we derive a novel expression of achievable secrecy rate and give an analytical expression for the zero-secrecy-rate distance of eavesdropper to the transmitter. Finally, we characterize the expression of maximum achievable secrecy rate (MASR) and show that the optimal power allocation strategy under an ANR eavesdropping behavior is transformed into no allocation of transmission power to AN. Numerical results are presented to illustrate the damage caused by the investigated eavesdropping behavior. Interestingly, the consequence of AN elimination is not influenced even under large number of transmit antennas.

We propose a joint rate and power adaptation scheme to maximize the decoding quality for scalable video coding (SVC)-based video transmissions over multi-input multioutput (MIMO) systems. The rate adaptation in our proposed scheme includes selection of the best modulation and coding schemes, set of spatial channels, number of SVC layers (source coding rates), and their corresponding application layer forward error correction (APP-FEC) coding rates. The power adaptation involves the proper allocation of the power to each antenna in the MIMO system. SVC-based video transmissions require unequal error protection (UEP) for different SVC layers due to the inter-layer dependency. In most of the previous works, the bit stream of each particular SVC layer is allocated to one spatial channel and the UEP is achieved by transmitting the more important SVC layers through the spatial channels with higher channel gains. However, in our proposed scheme, the bit stream of each particular SVC layer is distributed to multiple spatial channels so that additional diversity gain can be exploited by applying APP-FEC. The UEP can also be achieved by allocating different APP-FEC coding rates on each video layer. Moreover, transmit power allocation is also effectively and jointly determined to improve the system performance. The effectiveness and favorable performance of our proposed scheme are shown by simulations with H.264 SVC traces of high-definition video clips over MIMO systems.

We present a correction to the above-named work. In Table III,$d_{free}^{2}$for new codes with$L=32$should be 3.561 (instead of 3.667) and 3.233 (instead of 3.385) for TCM-DE and DTCM, respectively. The corresponding paragraph on the same page, “For$L=32$, the best$d'^{2}_{free}$is …… in simulations.” should be modified as “For$L=32$, the best$d'^{2}_{free}$is$5\Delta _{1}^{2}+2\Delta _{0}^{2}$(for instance, two paths (0,0,0,0,0,0) and (0,2,0,1,2,2), so the resulting minimum squared distance is$\min [\Delta _{2}^{2},d'^{2}_{free}=3.233]=3.233$for 8PSK. There are some codes that have the best$d'^{2}_{free}$and we choose (C0,C2),(C3,C1),(C3,C1),(C2,C0),(C2,C0),(C1,C3) and (C1,C3) for$\sigma ^{(1)},\cdots ,\sigma ^{(7)}$in simulations.”. In addition, the trellis diagram in Fig. 12(b) should be corrected to Fig. 1.

Bit-interleaved coded modulation with iterative decoding (BICM-ID) are suitable for continuous fading channels. In addition, BICM-ID using differential encoding can avoid the rate loss due to pilot symbols. Conventional differential encoding for uncoded modulation was used for BICM-ID. In this paper, we propose new differential encoding of 16APSK (amplitude and phase-shift keying) signals for BICM-ID. We first derive the probability of receiving signals conditioned on the transmission of input bits of general differential encoding. After that, we propose a new algorithm to optimize differential encoding for BICM-ID, and use it to find the differential encoding of 16APSK. Besides, code searches for the proposed differential encoding are performed. Simulation results show that the proposed differential encoding has better error performance than conventional differential encoding, and the searched new codes can further improve error performance.

We propose a forward error correction (FEC) coding rate adaptation scheme which maximizes the quality of experience (QoE), for scalable video coding (SVC) based video transmissions over multi-input multi-output (MIMO) systems. The proposed scheme adaptively selects the best set of spatial channels, number of video layers and their corresponding FEC coding rate according to channel state information (CSI) from the receiver. Unlike previous work, our proposed scheme distributes the FEC encoded bit streams to multiple spatial channels so that additional diversity gains can be obtained. Due to the complexity of the optimization, we decompose the original problem into several sub-problems, which can then be solved by a heuristic algorithm. The optimal solution can be found by choosing the best among all the candidate solutions obtained from the sub-problems. The effectiveness and superb performance of our proposed scheme can be demonstrated by many simulations with different videos and channel conditions.

Differential encoding (DE) is a classical technique at the transmitter that allows simple noncoherent detection at the receiver. On the other hand, trellis-coded modulation (TCM) is a bandwidth efficient technique which offers reliable data transmission. In this paper, we aim to find the best concatenation order of TCM and DE for channel phase coherence over N=2 symbols. Besides the well-known TCM followed by DE (called TCM-DE) , we propose a new trellis coding extension of DE which extends our earlier work, called differential trellis coded modulation (DTCM) . DTCM is TCM with DE defined in states where distinct states may have distinct DE functions. We propose design methods of DE functions for noncoherently non-catastrophic DTCM. For both TCM-DE and DTCM, we propose additive distance measures and set partitioning. Based on the proposed set partitioning, trellis codes are designed or searched for both TCM-DE and DTCM. Both minimum distances and simulation results show that TCM-DE outperforms DTCM and the obtained new codes are better than the original codes.

In this paper we propose a novel approach termed as dynamic copula time-frequency distribution (DCTFD) for the construction of positive time-frequency distributions (PTFDs). DCTFD models the dependency, i.e., correlation between time and frequency by a time-varying dependence parameter in copula function, and captures time-frequency dependency/correlation more accurately compared to static copula TFD (CTFD). In addition to presenting the under lying theory of the approach, a set of simulations are proved to demonstrate the advantages over CTFD and other classical methods, namely bivariate distributions.

Multiple-path source routing protocols allow a data source node to distribute the total traffic among available paths. In this paper, we consider the problem of jamming-aware source routing in which the source node performs traffic allocation based on empirical jamming statistics at individual network nodes. We formulate this traffic allocation as a lossy network flow optimization problem using portfolio selection theory from financial statistics. We show that in multisource networks, this centralized optimization problem can be solved using a distributed algorithm based on decomposition in network utility maximization (NUM). We demonstrate the network's ability to estimate the impact of jamming and incorporate these estimates into the traffic allocation problem. Finally, we simulate the achievable throughput using our proposed traffic allocation method in several scenarios.

In this work, a detector scheme for the detection of signal in a group of non-Gaussian narrowband interferences and white Gaussian noise is developed. Since there exists no closed-form probability distribution for this type of disturbance modeling, the key innovation lies in the use of characteristic function rather than the probability distribution to both design and implement the detector. Parameter estimation is performed at first step to find the unknown disturbance parameters. The utilized detector uses these parameters to form an approximately Gaussian distributed test statistic based on the empirical characteristic function of received data. Performance of the detector is investigated by means of both analytical and Monte Carlo simulations.

In this article, we address the problem of target detection in Wireless Sensor Networks (WSNs). We formulate the target detection problem as a line-set intersection problem and use integral geometry to analytically characterize the probability of target detection for both stochastic and deterministic deployments. Compared to previous work, we analyze WSNs where sensors have heterogeneous sensing capabilities. For the stochastic case, we evaluate the probability that the target is detected by at least k sensors and compute the free path until the target is first detected. For the deterministic case, we show an analogy between the target detection problem and the problem of minimizing the average symbol error probability in 2D digital modulation schemes. Motivated by this analogy, we propose a heuristic sensor placement algorithm, called DATE, that makes use of well-known signal constellations for determining good WSN constellations. We also propose a heuristic called CDATE for connected WSN constellations, that yields high target detection probability.

We present a framework for throughput optimization for multipath unicast routing in wireless networks in the presence of probabilistic jamming. The framework introduces a statistical characterization into the maximum network flow problem to compensate for the reduction in network flow due to the loss of jammed packets. We map the problem of throughput optimization under probabilistic jamming to that of optimal investment portfolio selection, treating the network throughput as the return on financial investments and using a common portfolio selection framework from financial statistics. Based on the portfolio selection framework, we present approaches to maximize expected throughput and to minimize throughput variance. We include both a detailed example and a simulation study to illustrate the application of the throughput optimization framework.

We propose a new model for investigating the impact of complex imperfect channel state information (CSI) over Nakagami-m fading channels. The phase difference between two correlated complex Nakagami random variables (RVs) is proposed and its statistical properties are investigated. A closed-form expression for the distribution is obtained using an approach from [1] and depends on the Nakagami-m parameter and the power correlation coefficient (p) between two correlated complex RVs. A simple approximation is given when p is close to unity. The proposed phase difference is shown to accurately approximate that of the Ricean. We derive the joint density function of this phase difference and its associated correlated envelopes. This is given in a closed form in terms of a generalized hypergeometric function, but the RVs can be easily generated for simulation. We analyze the impact of imperfect CSI on the bit error rate (BER) of uncoded and coded modulation. For uncoded modulation, the average BER and a closed-form expression of the asymptotic BER or error floor are obtained. For coded modulation, we determine the error free feedback bound of bit-interleaved coded modulation with iterative decoding for both perfect and imperfect CSI. We show that imperfect phase estimation is the major cause of the error floor.

Target detection and field surveillance are among the most prominent applications of Sensor Networks (SN). The quality of detection achieved by a SN can be quantified by evaluating the probability of detecting a mobile target crossing a Field of Interest (FoI). In this paper, we analytically evaluate the detection probability of mobile targets when N sensors are stochastically deployed to monitor a Fol. We map the target detection problem to a line-set intersection problem and derive analytical formulas using tools from Integral Geometry and Geometric Probability. We show that the detection probability depends on the length of the perimeters of the sensing areas of the sensors and not their shape. Hence, compared to prior work, our formulation allows us to consider a heterogeneous sensing model, where each sensor can have an arbitrary sensing area. We also evaluate the mean free path until a target is first detected.

Voice over IP (VoIP) has become the fastest growing wireless alternative to conventional telephony service by way of ongoing deployment of WLAN hotspots and even powerful WiMAX coverage. Resulting from the wired/wireless combined best-effort based heterogeneous IP networks which provide more fluctuation in available bandwidth and end-to-end delay, the performance of VoIP quality, especially using the handheld wireless devices, has been greatly degraded due to frequent packet loss and longer delays. This paper proposes a real-time embedded packet train probing scheme for estimating end-to-end available bandwidth so as to accomplish effective congestion control. By trading acceptable delays with adaptive packetization of voice bitstreams, as well as adaptive insertion of forward error correction (FEC) packets, an optimized system driven QoS approach for VoIP can thus be achieved.

In a wireless network environment, common channel errors, due to multipath fading, shadowing and attenuation, may cause bit errors and packet loss quite different from the packet loss caused by network congestion. In congestion control, the packet loss information can serve as an index of network congestion for effective rate adjustment; therefore, wireless packet loss can mistakenly lead to dramatic performance degradation. The paper proposes a packet loss classification algorithm based on detecting the trend in relative one-way trip time (ROTT) when it falls in the ambiguous zone where the packet loss classification is not straightforward. We show that the proposed algorithm greatly benefits rate-based congestion control algorithms for multimedia over IP networks.

In wireless communication, noise and channel fluctuation often cause bit errors and subsequently the packet loss, which has different characteristic from the loss from network congestion. For most congestion control algorithms, the packet loss information serves as an index of network congestion and is used for effective rate adjustment; therefore wireless packet loss can mistakenly lead to dramatic performance degradation. We discuss the reasons leading to packet loss and propose a packet loss classification (PLC) algorithm that is based on trend detection of relative one-way trip time. With the assistance of PLC, not only can the wireless loss be separated from the congestion loss, the wireless packet error rate can be also estimated. With the combined information, the new adaptive congestion control algorithm is constructed so that a receiver can acquire an appropriate share of bandwidth. The transmitted data is protected by adaptive maximum distance separable erasure codes according to the wireless channel condition and end-to-end available bandwidth

We consider the design of iteratively decoded bit-interleaved space-time coded modulation (BI-STCM) over fast Rayleigh-fading channels with N/sub t/ transmit and N/sub r/ receive antennas. We propose the design criterion to achieve the largest asymptotic coding gain inherited in the constellation labeling. In particular, for orthogonal space-time block codes, the labeling design criterion reduces to maximizing the (-N/sub t/N/sub r/)th power mean of the complete set of squared Euclidean distances associated with all "error-free feedback" events in the constellation. Based on this power mean criterion, we show that the labeling optimization problem falls into the category of quadratic assignment problems for constellations of any shape and with an arbitrary number of transmit and receive antennas. For a set of practical values of N/sub t/ and N/sub r/, we present optimal labeling maps for 8-PSK, 16-QAM, and 64-QAM constellations.

Pilot-symbol-assisted low-density parity-check (LDPC)-coded bit-interleaved coded modulation (BICM) is analyzed using the density evolution (DE) and the extrinsic information-transfer (EXIT) chart for correlated Rayleigh fading channels. The key parameter (the power correlation coefficient) is identified, and the threshold degradation is quantified. The optimal tradeoff of energy allocation between pilots and coded symbols is found to be sensitive to the normalized Doppler spread of the channel, the interpolation filter, the modulation scheme, and the pilot selection. In addition, a simple upper bound on the performance of any receiver that performs joint iterative decoding and channel estimation is derived. Extension to irregular code design is also discussed.

This letter provides a comparative study of joint channel estimation and low-density parity-check decoding algorithms for flat Rayleigh fading channels based on the receiver factor graphs. Two approaches for joint channel estimation and decoding are proposed. Intensive simulation studies are carried out to evaluate the receiver sensitivity to the choice of the factor graph. Results show that when channel statistical information is not available at the receiver, a low-pass filtering approach gives a more robust and simpler solution, and it is only 0.5 dB worse than the optimum Wiener filtering. All methods have about 2 dB improvements over the noniterative receivers.

In this paper we focus on the threshold computation and convergence analysis of regular LDPC coded BICM for Rayleigh fading channels. We compute the decoding threshold using discretized density evolution with and without channel state information. The convergence properties of DE are analyzed using extrinsic information transfer (EXIT) chart. The key parameter, the power correlation coefficient is identified and threshold degradation is quantified when perfect CSI is not available at the receiver. The optimal energy allocation between pilots and coded symbols is found to be sensitive to the normalized Doppler spread of the channel, the interpolation filter, modulation schemes and the pilot selection.

In this paper, we develop an analytical framework to quantify the effects of the channel estimation error on ultra-wideband systems operating in dense multipath environments in terms of the receiver performance, the receiver complexity and the channel estimation measurement. The focus of the paper is to characterize the SEP performance using the saddle-point approximation. We find that the performance of P-RAKE with a limited number of fingers degrades much less than the A-RAKE with imperfect channel estimation. And channel estimation by averaging two channel measurements greatly improves the performance with a small rate loss. Furthermore, the performance of the P-RAKE receiver with greater than four fingers is similar to that achievable by using a S-RAKE with the same number of fingers in the presence of channel estimation error.

We consider coded modulation with generalized selection combining (GSC) for bandwidth-efficient-coded modulation over Rayleigh fading channels. Our results show that reception diversity with generalized selection combining can conveniently trade off system complexity versus performance. We provide a number of new results by calculating the cutoff rate, and by deriving analytical upper bounds on symbol-interleaved trellis-coded modulation (TCM) and bit-interleaved-coded modulation (BICM) with GSC. All are verified by simulation. We show that our new bounds on TCM with GSC, which includes maximum ratio combining and selection combining as special cases, are tighter than the previously derived bounds. A new asymptotic analysis on the pairwise error probability, which can be used as a guideline for designing coded modulation over GSC channels, is also given. Finally, we show that BICM with iterative decoding (BICM-ID) can achieve significant coding gain over conventional coded modulation in a multiple-receiving-antenna channel.

We analyze the impact of imperfect channel state information (CSI) on the performance of bit-interleaved coded modulation with iterative decoding (BICM-ID) over fading channels. We develop a general, accurate and efficient theoretical error-free feedback bound (EF bound) to analyze the asymptotic bit-error rate (BER) of BICM-ID with imperfect CSI, and predict the BER floor due to channel estimation error. The convergence to the EF bound and the accuracy of the BER floor prediction are verified by simulation with various sets of code and channel parameters. These results are canonical, in that they apply to a variety of system configurations. Pilot symbol assisted modulation is used as a particular example for Rayleigh-fading channels.

We have suggested bit-interleaved coded modulation with soft decision iterative decoding (BICM-ID) for bandwidth-efficient transmission over Gaussian and fading channels. Unlike trellis coded modulation, BICM-ID has a small free Euclidean distance but large diversity order due to bit interleaving. With iterative decoding, soft bit decisions can be employed to significantly improve the conditional intersignal Euclidean distance. This leads to a large coding gain, comparable to that of turbo TCM, over both Gaussian and Rayleigh fading channels with much less system complexity. We address critical design issues to enhance the decoding performance and provide the analytical bounds on the performance with an ideal feedback assumption. We investigate the performance characteristics of BICM-ID through extensive simulations and show that at high signal to noise ratios, the performance of BICM-ID converges to the performance assuming error-free feedback.

We consider bit-interleaved coded modulation with iterative decoding (BICM-ID) for bandwidth-efficient transmission over Rayleigh fading channels. We propose the design criteria that utilize a large Hamming distance inherited in a low-rate code and a new labeling technique designed specifically for fading channels. This results in a large coding gain over noniterative coded modulation and performance close to that of "turbo" coded modulation with less complexity. We also show that BICM-ID designed for fading channels usually has a very good performance over the additive white Gaussian noise (AWGN) channel while the converse is difficult to achieve. When combined with signal space diversity, diversity order can be improved to twice the diversity order of conventional BICM-ID; therefore, the code complexity can further be reduced while maintaining the same level of performance. Specifically, with the bandwidth efficiency of 2 bits/s/Hz over Rayleigh fading channels, a bit error rate (BER) of 10/sup -6/ can be achieved with 16-QAM, a four-state rate 1/2 code at E/sub b//N/sub 0/ of about seven dB. We also derive performance bounds for BICM-ID with and without signal space diversity over Rayleigh fading channels, which can be easily extended for other types of fading channels.

Bit-interleaved coded modulation (BICM) was originally suggested by Zehavi (1992) to increase the time diversity of coded modulation over Rayleigh fading channels. In its typical design with Gray signal labeling, BICM causes a degradation over Gaussian channels, compared with the conventional trellis-coded modulation. We show that bit interleaving can actually be used to increase the Euclidean distance between the codewords of a convolutional code. With iterative decoding and careful design of signal labeling and interleaving, BICM can provide great performance even for Gaussian channels.

This paper considers bit-interleaved coded modulation (BICM) for bandwidth-efficient transmission using software radios. A simple iterative decoding (ID) method with hard-decision feedback is suggested to achieve better performance. The paper shows that convolutional codes with good Hamming-distance property can provide both high diversity order and large free Euclidean distance for BICM-ID. The method offers a common framework for coded modulation over channels with a variety of fading statistics. In addition, BICM-ID allows an efficient combination of punctured convolutional codes and multiphase/level modulation, and therefore provides a simple mechanism for variable-rate transmission.

We describe an efficient procedure to calculate the probability of error P/sub e/ for a quadrature amplitude modulation (QAM) communications system operating over a channel that introduces distortion, interference, and noise. The method is an extension of the saddlepoint integration technique introduced by Helstrom (1986) to efficiently evaluate P/sub e/ for one-dimensional pulse-amplitude modulation (PAM) systems with intersymbol interference (ISI) and crosstalk. We consider the effects of noise, random carrier phase offset, ISI, and crosstalk between the I and Q channels. The error probability is written as a double Laplace inversion integral and can be easily applied to any rectangular constellation. This integral is calculated by extending the saddlepoint integration technique to two complex dimensions. Results are presented for QAM systems with 16, 64, and 256 symbols. The technique can be directly extended to environments with cochannel interference consisting of other QAM signals.

It is shown that the CMLD (censored mean-level detector) is optimal in that the probability of detection is maximized for a given probability of false alarm when no contaminating signals are present in the reference cells. Since the probability of detection in this case is the same as the probability of detection for the MLD (mean-level detector) when k reference cells are used, and since the probability of detection of the MLD converges to the probability of detection of a fixed-threshold Neyman-Pearson test as the number of reference cells becomes large, then this is also true of the CMLD as k becomes large.>

Radar constant false alarm rate (CFAR) detectors, which are adaptive threshold detectors used to compensate for unknown noise environments, are discussed. Although the signal processing theory for CFAR detection is advanced, applications lag because of the high throughput required in radar. This intensive computational requirement (a data rate of at least 20 MHz for most search radars) cannot be met only by further advances in VLSI technology; parallel processing techniques are also needed. The feasibility of array processors based on VLSI technology enables the processing speed to increase by several orders of magnitude. One special-purpose VLSI architecture is the systolic array, which boasts massive concurrency. The concurrency in systolic arrays is derived from pipelined or parallel processing, and possibly both. Systolic array architectures are proposed for several important CFAR detectors.>

No abstract available.

A fast frequency-hopped (FFH) receiver which uses a prewhitening filter to reject narrowband interference is described. By using an appropriate fractional tap spacing, it is shown that interference can be estimated independently of the desired signal. Bit error rate results are presented for the receiver for linear square-law combining. The results compare favorably to those obtained by a near-optimal automatic gain-control (AGC) combining technique. The performance of the prewhitening filter interference rejection method is shown to be superior to that of a nonparametric self-normalizing receiver. Finally, simulation results for an FFH receiver using the complex least mean-square (LMS) algorithm to update the prewhitening filter coefficients are presented.>