In this paper, a precoding vector based index modulation (PV-IM) scheme is proposed. In the proposed scheme, precoding vectors are designed to maximize the Euclidean distance between precoded patterns, and their indices are used for information transmission. The proposed PV-IM scheme achieves superior performance than the constellation modulation scheme in high-rate scenarios, and overcomes the shortcomings of spatial index modulation (SIM) schemes. In addition, for the reconfigurable intelligent surface (RIS)-assisted multi-user (MU) scenario, a RIS-MU-PV-IM scheme is proposed based on the PV-IM scheme, where inter-user interference (IUI) is eliminated. The achievable rate, bit error rate (BER), and computational complexity of the proposed two schemes are analyzed. The impacts of channel estimation errors to the proposed two schemes are discussed. Extensive simulations are conducted to demonstrate the superiority of the proposed schemes.

Using time-difference-of-arrival (TDOA) measurements from several sensors to locate a target is one of the most widely used wireless localization methods. A challenge for TDOA localization is that the measurement equations are highly nonlinear. The weighted least-squares (WLS) based method tends to incur the threshold effect, and the convex relaxation based method has a high computational complexity. This paper presents a new iterative method derived directly from maximum likelihood estimation (MLE), and it does not require any matrix operations in its iterations. In order to reduce the likelihood of reaching a local minimum or a saddle point, multiple initial values are randomly selected from the region of interest, and the one that results in the lowest cost function is chosen as the output. Besides, the theoretical bias and covariance matrix of the proposed estimator are derived. The proposed algorithm outperforms state-of-the-art methods and achieves the Cramer-Rao lower bounds (CRLB).

This paper develops an effective artificial intelligence (AI) based approach for estimating heart rate (HR) and breathing rate (BR) using FMCW radar. The method leverages spectrogram analysis and principal component analysis (PCA) to extract compact and informative features from radar signals. We design and train a feedforward dense neural network to jointly estimate heart and breathing rates using radar signals. The approach is evaluated using a publicly available dataset of radar recordings, with ground truth reference values obtained from a clinical-grade contact sensor. Experimental results demonstrate that the proposed model achieves excellent accuracy, with mean absolute errors below 1% for heart rate and approximately 2% for breathing rate, validating the effectiveness of the proposed approach for accurate, contactless monitoring of vital signs.

This paper investigates the problem of localizing a moving target by using asynchronous time-of-arrival (ATOA) measurements. The source’s moving velocity can be considered to be a constant within a sufficiently small observation period. Based on this assumption, we consider the use of ATOA measurements to jointly estimate the initial location and the velocity of the mobile source. We first formulate the maximum likelihood estimation (MLE) problem for such scenario. Since the MLE problem is difficult to solve analytically because of its highly non-linear and non-convex nature, we then develop a semidefinite programming (SDP)-based algorithm to solve the MLE problem. Because two equality constraints are relaxed into two inequality constraints, the solution provided by the SDP-based algorithm is still suboptimal. We thus develop an improved solution that takes the SDP-based solution as an initial value and iteratively calculates the unknown parameters in the form of fixed-point iteration (FPI). Finally, extensive simulation results are obtained to compare its performance with those of methods as well as the Cramér-Rao lower bounds (CRLB). Results show that the proposed algorithm is optimal and can reach the CRLB.

Indoor positioning systems (IPS) have gained significant attention in research due to the growing need for reliable location-based services in indoor settings where global navigation satellite systems are unreliable or unavailable. A major challenge in developing dependable IPS lies in accurately classifying line-of-sight (LOS) and non-LOS (NLOS) propagation conditions, which heavily influence positioning accuracy. Existing solutions often demand high-computational resources or are constrained by specific assumptions about the environment, limiting their broad applicability. This article proposes a novel mechanism that leverages the histogram characteristic of the signal phase in common signal modulation methods like quadrature amplitude modulation and phase shift keying to differentiate between LOS and NLOS conditions. We posit that the phase modulation forms a distinctive pattern in the histogram, serving as a reliable identifier for LOS/NLOS classification. Our approach’s effectiveness is validated through a series of experiments, demonstrating up to 100% real-time accuracy in LOS/NLOS identifications, resilience to noise, extensive operational range, and free of computing-intensive machine learning models.

Three-dimensional (3-D) target localization using one-dimensional (1-D) space angle (SA) measurements from linear arrays has recently gained significant attention. Each 1-D SA measurement defines a conical surface, and the intersection of multiple such surfaces determines the target's location in 3-D space. However, state-of-the-art methods for solving the 1-D SA localization problem are often either suboptimal or computationally intensive. In this paper, we propose a novel iterative weighted least squares (IWLS) algorithm to address the problem. To provide deeper insights, we present a geometric interpretation of the iterative process, highlighting its physical significance. Furthermore, we analyze the computational complexity of the proposed algorithm and compare it with existing methods. Simulation results demonstrate that the proposed algorithm not only achieves higher estimation accuracy but also requires less computational time compared to state-of-the-art approaches.

Virtual replicas of physical systems, known as Digital Twins (DT), can offer innovative solutions for optimizing and forecasting battery management systems (BMS). However, their security remains a major concern. A new type of attack called Time Tampering Black-Box Attack Genetic Algorithm (TTB-GA) is introduced in this paper to study security in DT Intelligent Transportation Systems (DT-ITS). TTB-GA exploits the sensitivity of time series data and effectively deceives prediction models by altering input data’s timing within realistic ranges. To enhance the efficiency of locating and querying, customized operators such as mutation and fitness are designed within the GA-based search framework. Our attack achieves a remarkable success rate of 98% for Long short-term memory (LSTM) and 96% for Gated Recurrent Unit (GRU) models, exposing a critical vulnerability in digital twin security. Furthermore, we demonstrate the limitations of a distributed detection scheme combining an Autoencoder, a Convolutional Neural Network (CNN), and an Extended Kalman Filter (EKF), emphasizing the need for a robust and adaptive defenses. By exposing a novel and highly effective attack method (TTB-GA) targeting temporal vulnerabilities in time series data, and emphasizing the limitations of existing defense mechanisms against such attacks, our research significantly contributes to digital twin security.

We present a classical signal processing based solution for breathing rate and heart rate estimation of a human being using measurements from a frequency modulated continuous wave (FMCW) radar. The proposed solution jointly estimates the respiration rate and its higher order harmonics, as well as the heart rate using the Newtonized orthogonal matching pursuit (NOMP) algorithm on the continuous line. Our simulation results demonstrate that the proposed solution significantly outperforms the benchmark Fast Fourier Transform (FFT) based estimation algorithm in terms of the root mean-squared error (RMSE). We also demonstrate the application of the proposed algorithm on real data captured using the Infineon Technologies 60 GHz FMCW radar BGT60TR13C development board where similar performance improvement is observed.

This work presents a new weighted least-squares (WLS) method for source localization using angle-of-arrival (AOA) and time-difference-of-arrival (TDOA) measurements. Previous studies have shown that combining these two independent types of measurements yields more reliable results, as evidenced by lower Cramér-Rao lower bounds (CRLB) compared to using a single type of measurement. Our newly developed WLS algorithm has excellent performance when the source is close to the sensors but encounters challenges when the source is distant. To address these limitations, we develop an improved solution that incorporates a one-dimensional search process along the distance between the reference node and the source node. This enhancement significantly improves the algorithm’s performance in ‘far-field’ (i.e., when the source is far away from the sensors) scenarios. Our extensive simulation results demonstrate that the proposed algorithms substantially outperform existing methods in terms of root mean-squared error (RMSE), establishing a new benchmark for accuracy and reliability in hybrid AOA-TDOA localization.

Reconfigurable intelligent surface (RIS)-assisted spatial index modulation (SIM) is a promising candidate for future wireless communication systems due to its high energy and spectrum efficiencies. When only one transmit antenna and one receive antenna are active in the RIS-assisted SIM, we develop a phase-alignment algorithm based on the signature constellation, which utilizes the signature constellation technology to achieve a good bit error rate (BER) performance with a low complexity. Furthermore, in the general scenario, we propose a novel optimization algorithm for RIS reflection coefficients, called maximum Euclidean distance-based low BER (MED-LBER) algorithm. The proposed algorithm aims to maximize the Euclidean distance between different received signals to improve the system performance. The achievable rate, BER performances, and computational complexities of the proposed algorithms are analyzed in detail. The impacts of imperfect channels on the performance of the proposed algorithms are studied. Extensive simulations are carried out to compare the performance of the proposed algorithms with existing algorithms, and demonstrate their superior BER performance.

Regulating illegal activities in cyberspace to balance user privacy and cyberspace governance has been a non-trivial challenge when designing anonymous authentication solutions. For example, while several existing anonymous authentication protocols support accountability, they either risk leaking users' private keys or incur significant overhead for accountability in each ongoing authentication, including in cloud service-based authentication schemes. Seeking to address these limitations, this paper proposes an auditable anonymous user authentication (A2UA) protocol based on blockchain for cloud services. The A2UA protocol mainly employs bilinear pairing, partial authentication factors, dynamic credits and fake-public keys (FPKs) to achieve anonymous mutual authentication between users and cloud service providers, and applies ring signature and blockchain to accomplish two-level accountability while maintaining user privacy. Our analysis results show that the A2UA protocol outperforms several other existing schemes in terms of security, computation and communication costs as well as security and privacy features. Additionally, it has good feasibility in terms of the Ethereum Gas cost as demonstrated in our evaluation.

For the sake of privacy, encrypting the content shared on the Internet is becoming popular. However, it brings a nontrivial challenge in regulating the illicit shared content (e.g., viruses, rumors, malicious code, etc.). To deal with it, lots of schemes have been proposed, which mainly rely on a third-party—regulatory authority (RA), to perform auditing, regulating or supervising exclusively. Although these schemes mitigate the problem of illicit shared content, they still suffer from the following two issues. On one hand, relying on a single RA alone may lead to the serious problems of injustice and inadequate regulating. On the other hand, users’ privacy is violated since an independent RA unconditionally inspects all the files shared by users. Therefore, we propose a joint regulating scheme (JRS) for secretly shared content based on threshold secret sharing algorithm and blockchain technology. To make the censor activities democratic and public, they are authorized by both the RAs and blockchain miners during which two threshold secret sharing algorithms are applied. Further, only the suspicious users (or files) are censored and the whole process is recorded as blockchain transactions to balance the user privacy and censoring fairness. At last, the results of security and performance analysis show that JRS can resist the known attacks and the cost is acceptable in practice.

Transmitter positioning plays an important role in many fields such as proactive cognitive radio, asset tracking, and navigation. In this paper, we propose a modified angle of arrival (AoA) based localization method that can be used for near and far field systems using N collinear antennas. We also propose a hybrid TDoA/modified AoA localization approach. Root Mean square error (RMSE) performance of the proposed algorithms is studied and it showed that the hybrid based method increases the maximum range of coverage beyond the maximum range covered by each of the standalone methods.

A new extreme learning machine (ELM) localization technique that uses received signal strength indicator fingerprints only is proposed for multifloor environments. This structured scheme forms multiple individual ELMs for the floors as well as for the geographically formed data clusters of each floor. Multifloor environments often have huge amount of training and online measurement data. To maximize efficiency, we develop a data preprocessing algorithm, aiming to: 1) efficiently extract out only the essential information from the vast amount of data sets and reduce the data dimension and 2) transform the floor-level data sets and positioning data sets of each floor into a proper structure that is suitable for the proposed ensemble ELM technique. The proposed solution is unique in that its offline phase exploits multiple individual ELMs for all floors to generate a set of floor-level classification functions with the preprocessed training data sets, and for each floor, it exploits multiple ELMs for the data clusters to generate a set of position regression functions. The online phase executes a coarse localization step to estimate the floor by using the floor-level classification functions and a refined step to estimate the position on the floor by using the position regression functions. The proposed algorithm and several existing algorithms are implemented to perform localization using the same measured datasets in a multistory building. For both floor estimation and localization on the floor, it outperforms existing schemes. For most cases, the performance gap is substantial.

Spatial domain modulation employs spatial degree of freedom to convey information bits. Traditional spatial domain modulation schemes include spatial modulation, spatial shift keying (SSK), and variations of these two schemes. To fully make use of the spatial degree of freedom and improve the achievable data rate of traditional spatial domain modulation schemes, we propose a successive-coded SSK (SC-SSK) modulation scheme. The core of the proposed SC-SSK scheme is a multiple step coded modulation strategy, in which different information bits are mapped to the designed pattern in each step. The constellation of the transmit signals is designed. A QR decomposition based successive detection algorithm is proposed for this particular coded modulation strategy. The achievable rate, the error rate performance, and the computational complexity of the proposed SC-SSK scheme are analyzed in detail. Simulations are carried out to compare the proposed the SC-SSK scheme with the reference spatial domain modulation schemes, and reveal the advantages of the proposed SC-SSK scheme.

This paper develops a simple and efficient method for source localization using signal time-of-arrival (TOA) measurements. There exist many TOA localization algorithms, most of which require matrix inversions. Their complexity often makes them unsuitable for cases when a large number of sources need to be localized simultaneously via many sensor nodes. The proposed algorithm, which requires addition, multiplication and taking root-squares only, has a lower complexity while it still performs better than existing schemes.

This paper investigates the problem of source localization using signal time-difference-of-arrival (TDOA) measurements in the presence of clock synchronization bias and sensor position errors. Our existing work has developed a unified solution for TDOA localization in the presence of sensor position errors but clock synchronization bias was not considered. Clock synchronization bias is a more complex problem often encountered in practical localization networks. This paper further generalizes this framework to include clock synchronization bias. The proposed technique employs multiple calibration emitters to simultaneously alleviate both the sensor position errors and clock synchronization bias. The maximum likelihood estimator (MLE) for this problem is optimal, but too complex to be applied in practice. We develop a semidefinite programming (SDP) based localization algorithm to effectively solve the MLE problem. This SDP algorithm can reach the Cramer-Rao lower bound when sensor position errors are not unrealistically large.

In intensity-modulation and direct-detection (IM/DD) multiple-input and multiple-output (MIMO) visible light communication (VLC) systems, spatial subchannels are usually correlated, and spatial modulation is a good choice to achieve the advantages of MIMO technology. Peak-to-average power ratio (PAPR) is a key issue in VLCs due to the limited linear dynamic range of light emitting diodes (LEDs). Single-carrier communication systems have a lower PAPR than orthogonal frequency division multiplexing (OFDM) communication systems. However, it is challenging to design a single-carrier spatial modulation for high-rate transmissions because of the time domain intersymbol interference. This paper develops an optical spatial modulation (OSM) scheme based on bipolar pulse amplitude modulation (PAM) and spatial elements for high-rate indoor VLC systems. Multiple data streams can be transmitted simultaneously in the proposed scheme. Based on the transmit strategy, we develop a low-complexity receiver algorithm that achieves better bit-error rate performance than reference schemes, and the proposed OSM scheme has a much lower PAPR than OFDM based OSM schemes. When the spatial subchannels are highly correlated, a spatial area division strategy is applied, and the receiver algorithm is investigated. The symbol-error rate expression of the proposed OSM scheme is derived, and the computational complexity is analyzed.

This paper investigates time-of-arrival (TOA) source node self-positioning with unknown clock skews in wireless sensor networks. For the source-to-anchor direction, source node clock skew does not affect the localization performance. When synchronized anchor nodes simultaneously transmit signals to a source node, the source node clock skew will degrade the localization performance. A semidefinite programming (SDP) algorithm that jointly estimates the source position and clock skew is proposed for the latter case. The proposed algorithm is better than the two kinds of existing schemes, namely, asynchronous TOA localization and TDOA localization. We also tune the algorithm to the case of anchor nodes position uncertainties. Simulation results validate the performance of the proposed algorithm.

This paper proposes an efficient method for multi-path mitigation in GNSS that uses BOC signals. This method determines the maximum width of a W2window in a CCRW receiver to mitigate multipath effects. The length of this window is iteratively reduced until it reaches a value with which the distortion produced by multipath is eliminated. This distortion is measured as the Euclidean distance between the actual discriminator (obtained for the incoming signal), and the local discriminator (generated with a local copy of the signal). The effectiveness of the proposed approach is demonstrated through simulations of multipath environments. The principal advantage of the proposed scheme is that it is simple to implement.

This paper establishes the applicability of observable block companion form linear Kalman innovation models, for secret key generation between communicating parties (Alice and Bob) in a multipath wireless channel. First, Kalman models are identified to describe the dynamics of the channel between both users, based on real measurements of the Received Signal Strength Indicator (RSSI) corresponding to various blocks of information. Afterwards, it was verified that the innovation errors exhibited a significant randomness content, and that there was high correlation between the parameters of Alice and Bob for the same block. In addition, improved values of maximum channel capacity for secret key generation were obtained. Additional features that make innovation Kalman models an excellent alternative for secret key generation include: simplicity of implementation, high computational efficiency, excellent performance in modeling time-varying systems, and they do not require to estimate the properties of the noise.

This work presents a target localization scheme in distributed multiple-input multiple-output (MIMO) radar system using bistatic range measurements. The localization approach consists of two phases. First, measurements are divided into multiple groups based on the various transmitter and receiver elements. For each group, an approximate maximum likelihood (AML) estimator is proposed to estimate the location of a target. Then, the estimation results from these different groups are combined to form the final estimate. The performance of the proposed algorithm is validated by simulation and is shown to reach the Cramer-Rao lower bound (CRLB) in a range of measurement noise levels.

The addition of analogue processing to the digital precoding, known as hybrid beamforming (HB), is an efficient solution for massive multiple‐input multiple‐output (MIMO) systems. The design of a phase shifter (PS) network plays an important role in the complete precoder operation because it necessitates accurate components for realising precise phases, and that can be costly. Finite resolution PSs are good alternatives because they need simpler hardware implementation than those with infinite resolution. However, the degradation of performance of a MIMO system with very low‐resolution PSs is significant. Although recent studies suggest adding extra radio frequency (RF) chains to substitute for the accuracy of the PSs, it is complex, expensive and not energy efficient. This study demonstrates that HB with low‐resolution PSs can realise a high performance without increasing the number of RF chains. The authors proposed solution relies on a proper selection of the weights of the RF beamformer, hence exploiting the structure of the multipath propagation channel to maximise the system capacity. They also show that separating antennas from each other by sufficient distance, results in a less correlated channel, and thus, a minimal loss in the capacity and the antenna gains are assured.

Lens-based millimeter-wave massive MIMO technologies could reduce the number of required radio frequency chains at the base station without a loss of performance, but require the beamspace channel information, which is often costly to obtain. In this paper, a low-complexity scheme to estimate the channel for lens-based 3D millimeter wave massive MIMO systems is proposed. Beamspace analysis shows that the main entries of the channel matrix form a dual crossing (DC) shape. Existing DC-based channel estimation algorithms have a very high computational complexity. The proposed algorithm eliminates the process of repeatedly selecting the main row and column that is required in existing algorithms, and provides a solution even when certain entries exceed the matrix boundary. It thus has a much lower computational complexity than existing algorithms. Additionally it achieves a smaller normalized mean-squared error of the channel estimates than existing DC-based algorithms.

The most state-of-art time-difference-of-arrival (TDOA) localization algorithms are performed under the assumption that all the nodes are synchronized. However, for a widely distributed wireless sensor networks (WSNs), time synchronization between all the nodes is not a trival problem. In this paper, we study the problem of source localization using signal TDOA measurements in the system of nodes part synchronization. Starting from the maximum likelihood estimator (MLE), we develop a semidefinite programming (SDP) approach. Besides, we extend the SDP algorithm to the case of non-accurate sensor position. Simulation results validate the localization performance of the proposed SDP algorithms.

A new joint synchronization and localization method for wireless sensor networks using two-way exchanged timestamps is proposed in this paper. The goal is to jointly localize and synchronize the source node, assuming that the locations and clock parameters of the anchor nodes are known. We first form the measurement model and derive the Cramér-Rao lower bound (CRLB). An analysis of the advantages and disadvantages of a recent scheme on joint synchronization and localization motivates us to develop a maximum likelihood estimator (MLE) that effectively resolves the issues of this existing scheme. A novel semidefinite programming method is then proposed to transform the nonconvex MLE problem into a convex optimization problem. Extensive simulation results are obtained to compare the synchronization and localization performances of proposed scheme and a few state-of-the-art existing schemes.

In order to tackle the exclusive characteristic in the screen content video, new coding tools such as intra block copy mode and palette mode are adopted in the screen content coding (SCC) based on high efficiency video coding (HEVC) standard. It results in high coding complexity for SCC and is hard to satisfy real time applications. An efficient intra coding algorithm for screen content video is proposed in this paper. Early skipping or early termination of coding unit (CU) partition and mode prediction is applied to speed up intra coding by exploiting the correlated information among luminance, gradient and neighboring CUs. Furthermore, the correlated information of hit rate and coding bit is revealed and properly used for fast CU depth decision. Experimental results demonstrate that the proposed algorithm obtains significant time saving with ignorable compression loss in comparison with several recent algorithms.

The layout of the anchors is one of the major factors that affect the positioning accuracy of timing-based localization systems. Existing anchor layout optimization typically resorts to the use of the Cramer-Rao lower bound (CRLB), which takes all the anchors into consideration to obtain the globally optimal layout (for some target locations only). Except for some special cases, the CRLB based globally optimal method generally requires brute-force searching. For networks that require more than a few anchors, this approach is too complex to be practical. The goal of this paper is to develop a simple anchor placement method based on the maximum range-measurement change criterion, with which the placement of each anchor is optimized by itself as it enters the network. Major advantages of the proposed technique include: a) it is suitable for any anchor layout scenarios; for example, to add new anchors to an existing network to meet increased performance and/or coverage requirements; to relocate some of the existing anchors; or to start placing anchors in a large network, and b) it is very easy to implement, but it performs very close to the CRLB-based approach.

In this paper we propose a low-computational-complexity channel estimation algorithm for the downlink of massive MIMO systems. This algorithm employs the expectation propagation and expectation maximization techniques, assuming a sparsity promoting conditional Gaussian prior distribution on the channels. Its computational complexity scales only linearly with the number of transmit antennas, the number of pilots, and the channel length. Compared with existing state-of-the-art algorithms, it has a lower pilot overhead and is much more computationally efficient. The channel estimation mean-squared errors with the proposed algorithm and the existing block iterative support detection (block-ISD) and basic pursuit (BP) methods are simulated and compared. Results show that the performance of the proposed algorithm approaches the benchmark performance, and is significantly better than that of block-ISD and BP.

Hybrid beamforming (HB) using both analog precoding at RF and digital precoding is an effective solution to reduce the complexity and power consumption of massive MIMO systems. Extensive work has determined that HB can achieve the performance of the optimal precoder, assuming optimal antennas implementation, ideal environment, and full rank effective channel. However, depending on the implementation techniques adopted for the RF precoder and other system parameters, such as the number of active RF chains, the limited distance between antennas, and the geometric placement of both ends of wireless systems, the effective channel matrix could be rank deficient, which degrades the performance of the system. This paper provides a new and complete set of solutions for HB that approaches the performance of a fully digital beamformer in terms of MIMO multiplexing gains, by taking careful consideration of the matrix of the effective channel, appropriately selecting independent columns of the analog precoder, calculating the least squares solution for the digital precoder, and selecting its digital gain based on the selected columns of the RF precoder and the effective channel.

A scheme that employs hierarchical modulation with network coding (HMNC) to minimize the number of transmission phases for information exchange among users in a multiuser relay network is developed in this paper. Specifically, for a network with multiple users and one relay, we exploit HM in all user nodes and design a joint HM and NC scheme at the relay, so that 'side-information' of a user node gained during other users' transmission phases is used efficiently to achieve a much higher system sum-rate than existing schemes while maintaining a comparative error performance. The bit error rate (BER) and the achievable sum-rate of the proposed scheme are analyzed analytically. These results can be used to optimize a network design for a proper tradeoff between reliability and effectiveness. The advantages of the proposed scheme in achievable sum- rate and BER over both AWGN and Rayleigh fading channels are verified through comparison with existing schemes that use only HM or only NC at the relay.

Existing finite field network coding (FFNC) can be applied in networks where all users have the same data rate and can thus use the same modulation type. In most practical scenarios, different users typically have different data rates. With simple changes such as zero-padding and repetition to the data sequences of different users received at relays, it is still possible to employ the existing FFNC scheme, but the network throughput and error performance will be compromised. In this paper, we design a network coding scheme for multiuser multiple-relay networks where users' data rates are different. Specifically, we develop a layered network coding approach that allows the use of the existing FFNC for each layer in a hierarchical structure and derive the corresponding decoding process. The bit error (BER) and computational complexity of the proposed scheme are derived. Because the proposed scheme could fully exploit the additional diversity gain from decoding the codewords in each layer separately, it achieves a better BER performance than the existing FFNC scheme, which is validated in simulation.

The accuracy of indoor positioning systems could be significantly reduced by non-line-of-sight (NLOS) propagation. The bulk of existing work on NLOS error mitigation for time-of-arrival (TOA) systems assumes that the NLOS links can be identified and/or the NLOS error statistics are known. To avoid requiring such information that is often unavailable in practice, recent work has applied convex optimization for NLOS error mitigation. However, convex optimization for NLOS error mitigation in TOA systems is often an infeasible problem. A strategy to reduce the infeasible problem probability is to relax the constraints for the optimization at the expenses of a reduced positioning accuracy. In this paper, we develop a soft-minimum method for NLOS error mitigation TOA systems. The major advantages of the proposed method include: 1) like existing convex optimization schemes, it does not require any a priori information about NLOS links or NLOS error statistics; 2) unlike existing convex optimization schemes, it does not have infeasibility issues; and 3) it results in a higher positioning accuracy than with existing convex optimization schemes.

Timing-based indoor positioning requires synchronization of the anchors that are distributed in space. Many synchronization techniques have been proposed, but implementing them in practice is extremely challenging, especially for networks with a large number of anchors. In this paper, a new synchronization-free localization model for timing-based indoor positioning is proposed. This scheme employs a repeater for a network; if there are many anchors, multiple repeaters can be used, and each repeater works with only a subset of its nearby anchors. We develop the mathematical model for the proposed scheme and derive its Cram'er-Rao lower bound (CRLB). To evaluate the localization performance loss in exchange for the synchronization-free property of the proposed scheme, we compare the CRLBs of the proposed scheme, and time-of-arrival (TOA) and time-difference-of-arrival (TDOA) schemes assuming perfect anchor synchronization. The simulated mean squared error (MSE) of the proposed scheme with nonlinear least-squares (NLLS) method approaches well the CRLB.

In this study, the authors propose a low‐complexity symbol‐level combining (SLC) scheme for Chase combining‐based hybrid automatic repeat request in multiple‐input multiple‐output systems with a linear receiver. In the proposed scheme, a subset of all row vectors in the channel matrix is selected and used for combining and detection of retransmitted symbols, where the Sherman–Morrison–Woodbury lemma is applied for the utilisation of each selected row vector. Therefore, compared with the existing SLC schemes using the entire channel matrix, the proposed scheme can have an advantage in computational complexity. Furthermore, they develop a row vector selection criterion for the proposed SLC scheme to calculate the amount of the signal‐to‐interference‐noise ratio improvement based on the squared norm of each row vector with a significantly low complexity. Simulation results verify that compared with the existing SLC schemes, the proposed SLC scheme achieves similar or better error performance, while its computational complexity is lower or in the worst‐case similar.

In indoor optical wireless communication systems with intensity modulation (IM) and direct detection (DD), diffuse links could be established through reflecting. For such a case, line-of-sight does not exist between the transmitter and receiver, and the channel delay spread will be large. The dispersion of the channel might cause inter-symbol interference. Also, the transmitted signal must be nonnegative. Thus most modulation schemes for radio communications cannot be used directly for such a system. This paper develops a new multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) IM/DD systems: real and imaginary coefficients separation (RIS) system. Two transmit data streams require only one inverse fast Fourier transform (IFFT) block, resulting in a low computational complexity. Compared with traditional OFDM based schemes, the RIS scheme achieves a better BER performance and requires fewer IFFT blocks at the transmitter. The transmitter architecture and receiver algorithm are analyzed in detail. BER performance and simulation results are provided.

The goal of this paper is to develop a hybrid automatic repeat request (HARQ) transmission state control algorithm for multiple-input multiple- output (MIMO) systems with interference cancellation (IC) detection to improve throughput. The HARQ transmission state is defined as the distribution of the initial packets and retransmission packets transmitted during a transmission time slot. In such a system, the retransmission packets normally have a lower error probability than initial packets. However, in terms of throughput, successful decoding of an initial packet is more rewarding than a retransmission packet. The proposed algorithm generates the transmission state in which initial packets and retransmission packets are sent together. The outcome is that it achieves a lower error probability for initial packets by exploiting the IC process and a significantly higher throughput than the conventional HARQ system, which is verified by simulation results.

An improved M‐ary phase position shift keying (MPPSK) modulation, aiming to increase the spectral and energy efficiencies of existing MPPSK schemes while preserving their low demodulation complexity and error performance, is proposed in this study. Specifically, an improved MPPSK with orthogonal signals called OI‐MPPSK is presented. For the proposed OI‐MPPSK, the authors develop two demodulation schemes that employ a special impact filter (SIF): (i) the orthogonal SIF correlator (OSC) scheme, which consists of the orthogonal transmission, the SIF and a correlator; (ii) the orthogonal SIF position (OSP) scheme, which is the same as the OSC scheme except that the coherent demodulator is replaced by exploiting position‐related information. As a result of exploiting the position‐related information in the proposed OI‐MPPSK scheme, the SER performance of the OSP‐based demodulator is superior to that of the OSC‐based demodulator.

A packet transmission strategy for multiple‐input multiple‐output systems with interference cancellation detection and hybrid automatic repeat request (HARQ) processes is proposed. The error probability and throughput of such a system depend on the choice of the set of packets to be transmitted in each packet transmission time interval, but there are no existing implementable strategies to optimise such choice of packets. In this study, the authors first define a concept of the effective interference level (EIL) and establish the relationship between the EIL and the effective signal‐to‐interference‐plus‐noise ratio. Then they show that choosing the set of packets that minimises the EIL successively from the lowest to the highest HARQ round leads to a lower packet error and higher system throughput than conventional HARQ, which is verified by simulation. Also, the proposed EIL‐based scheme uses only the acknowledgement feedback messages like a conventional HARQ scheme, because the number of HARQ rounds of each packet is the only required information to calculate the EIL. Simulation results show that the proposed scheme outperforms the conventional scheme in terms of throughput with the signal‐to‐noise ratio gain of about 4.2 dB at maximum.

In this paper, we describe the design of a 3 Giga-samples per second real-time multi-channel data-acquisition unit. We first introduce the technical challenges including synchronization, data transmission and printed circuit board design. Then we analyze the cause of issues in multi-channel synchronization, and develop a novel method to synchronize the channels and correctly save the data into RAM. We later discuss issues surrounding the unit's signal integrity and routing. We provide techniques and design procedures to properly mitigate these issues and guarantee the correct performance of the system. The DAU has been fabricated, and its performance is evaluated in this paper by sampling ultra-wide-band signals.

This paper proposes a novel unambiguous correlation function for sine-phased binary offset carrier (BOC) tracking. Modeling a BOC signal pulse as a sum of multiple rectangular pulses, correlating the multiple rectangular pulses with the received BOC signal, and combining the correlations, we construct an unambiguous correlation function with only a single main-peak. The proposed correlation function is confirmed from numerical results to provide an improved tracking performance over the conventional correlation functions.

Classification of line‐of‐sight (LOS) or non‐LOS (NLOS) propagation is critical for most pulsed ultrawideband localisation systems. In this letter, first, the authors propose a two‐dimensional (2D) LOS/NLOS classification scheme that uses skewness of the channel impulse/pulse response, which has not been used by existing work. The log‐likelihood ratio of the 2D LOS/NLOS classification is used to determine the weights for localisation. Then, the authors derive an iterative Gauss–Newton method to solve the location of the target, which provides a higher accuracy than the Gauss–Newton method used in existing work. Finally, they investigate improved localisation by incorporating the statistics of NLOS bias as a result of LOS/NLOS classification into the cost function, and derive the statistics of the corresponding errors of location estimates. The proposed 2D LOS/NLOS classification scheme is compared with an existing 3D scheme to demonstrate its effectiveness.

In visible light communication (VLC) systems with intensity modulation (IM) and direct detection (DD), the modulation bandwidth of light emitting diode (LED) is limited, and dispersion of the channel might cause inter-symbol interference. Also, the transmitted signal must be nonnegative. Thus most modulation schemes for radio communications cannot be used directly for such a system. This paper develops a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) VLC system that overcomes the modulation bandwidth limitation of LED and satisfies the requirements of the transmitted signal for IM/DD. Also, two transmit data streams require only one inverse discrete Fourier transform (IDFT) block, resulting in a low computational complexity. The transmitter architecture, receive algorithm, bit error rate performance, channel capacity analysis, and simulation results are provided.

This article studies adaptive modulation for QR decomposition and successive interference cancellation receivers in multiple‐input multiple‐output systems over slow‐ and fast‐fading channels. In slowly fading channels, adaptive modulation schemes with finite‐rate feedback under the constraints of a constant total transmit power, discrete‐rate and a target bit‐error‐rate (BER) are proposed. Specifically, the authors first develop adaptive modulation with modulation order feedback only. For power allocation and modulation order feedback, the authors establish an optimisation scheme that can be solved easily and analyse the effect of power‐level quantisation on the achievable data rates. For the fast fading channel case, the authors analyse the probability distribution of the ‘ R ’ matrix and derive a scheme that only requires feedback of the statistical information of the channel for adaptive modulation with optimal bit loading to guarantee that the BER target is met.

Data Centers face considerable challenges in seamless integration of telemetry and control functions. These functions are essential to management tasks related to power capping, cooling, reliability, predictability, survivability, and adaptability control. It is therefore essential to create an infrastructure of sensors that monitors the physical properties of the dynamically changing environment. The conventional approaches to support distributed sensor data collection and control using wired solutions are static, expensive, and non-scalable. In this paper sensors and control agents supporting this telemetry are a part of a dense and noisy network that are scattered across the data centers. We present an alternative approach for this unique environment using wireless sensor network to improve data efficiency and real-time delivery. We propose genetic algorithm (GA) approach for a densely populated sensor network to dynamically construct optimal collection trees through improved channel diversity that support context aware sensor data compression and reduced latency data delivery.

High-speed, low-power design of Viterbi decoders for trellis coded modulation (TCM) systems is presented in this paper. It is well known that the Viterbi decoder (VD) is the dominant module determining the overall power consumption of TCM decoders. We propose a pre-computation architecture incorporated with T-algorithm for VD, which can effectively reduce the power consumption without degrading the decoding speed much. A general solution to derive the optimal pre-computation steps is also given in the paper. Implementation result of a VD for a rate-3/4 convolutional code used in a TCM system shows that compared with the full trellis VD, the precomputation architecture reduces the power consumption by as much as 70% without performance loss, while the degradation in clock speed is negligible.

We study two power allocation (PA) schemes for distributed transmit diversity systems. We first derive the performance of the instantaneous channel gain feedback-based PA (ICG-PA) scheme in the presence of channel variation during feedback delay. We then study channel gain variance feedback-based PA (CGV-PA) to mitigate the performance degradation of ICG-PA caused by feedback delay. Finally, we derive design rules for optimum CGV-PA from a compact and accurate performance expression derived.

Information technology systems face considerable challenges in seamless integration of telemetry and control information. These are essential to various autonomic management functions related to power, thermal, reliability, predictability, survivability, and adaptability. Sensors and control agents supporting this telemetry are a part of large multiprocessor environments that are scattered across the platform. The conventional approaches to support distributed observability and control using wired solutions are static, expensive, and non-scalable. We present an alternative approach for this unique environment that replaces static wired sensors with dynamically reconfigurable wireless sensors. It employs a genetic algorithm based approach to optimize sensor node function assignment, clustering decisions, resource distribution, and route establishment for improved control quality. Based on this new, wireless sensor network approach, we evaluate the average data-flow delay characteristics between sensor and control end-points. We also investigate the "quality of control'' by measuring the conformity of the controlled objective to platform policy specifications (like power limits).

We propose a modified channel model for 60 GHz wireless systems. This model includes the effects of directional antennas and polarization. We study the statistics of the angular parameters of the channel model and simplify an existing channel model for practical applications. The effects of antenna beamwidth in commonly encountered scenarios are investigated. The results can be used as the basis for cost analysis. We also simulate the performance of the channel and compare our results with non-directional transmission.

This paper presents a memory-reduced VLSI architecture for the decoding of double-binary convolutional Turbo code (DB CTC) using maximum a posteriori probability (MAP) algorithm. For such kind of soft-in soft-out (SISO) decoding, the branch metrics (BMs) γ become the dominant factor in determining the overall required memory size inside the SISO decoder. We propose to decompose each BM into a information metric and a parity metric, which leads to 50% reduction of the memory size for BMs. We further modify the MAP algorithm based on the new formulation of BMs. The new MAP algorithm reveals that: 1) the partitioning of BMs does not introduce any computational overhead when the MAP algorithm is modified; 2) the extrinsic metrics are independent from a posteriori log-likelihood ration, which is attractive for low-power SISO decoder design.

Inversion of channel matrix is required for commonly used detection schemes in multiple-input multiple-output (MIMO) systems. In time-varying fading channels, frequent matrix inversion is computationally intensive for mobile terminals operating at high data rates. Several existing papers have addressed this problem for MIMO orthogonal frequency division multiplexing systems by employing interpolation since the channel coefficients are correlated in the frequency domain. The correlation of the channel in the time domain, i.e., the channel matrices at consecutive symbol intervals vary only slightly, could also be exploited. We propose an algorithm that exploits second-order extrapolation in the time domain to lower the computational complexity of matrix inversion. While existing schemes are mainly designed for linear MIMO detection, the proposed algorithm can be applied for both non-linear detection such as ordered successive interference cancelation (OSIC) and linear detection. The proposed scheme can be efficiently implemented with only addition and integer multiplication. Simulation results of the proposed scheme applied in MIMO OSIC detection demonstrate that it can significantly reduce the matrix inversion complexity while maintaining the system performance.

We develop a scheme to improve data throughput for multiuser cooperative relay communications operating in half-duplex mode. Cooperative relay, while effective in mitigating fading effects, might reduce the overall throughput of the network since it requires additionally resources for relay. In order to overcome this limitation, we develop a multiuser cooperative communication scheme that employs hierarchical modulation. This scheme exploits the different fading conditions for each user and allows the system to transmit two independent data streams simultaneously. Since the bit-error rate of the proposed system is a function of the distance parameters of hierarchical modulation, transmission reliability can be controlled flexibly by varying the distance parameter. We derive the error-rate expressions of the proposed scheme and compare its symbol-error rate performance for specific distance parameters with that of conventional relay schemes.

We propose a computationally efficient lattice reduction (LR) algorithm for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems in frequency-selective fading channels. In our proposed algorithm, we exploit the inherent feature of unimodular transformation matrix P that remains the same for frequency components which have relatively high amplitude correlation. We eliminate the redundant calculations by reducing brute-force LR iterations among adjacent subcarriers. We simulate the error performance and complexity of the proposed algorithm under various MIMO-OFDM system configurations. The results demonstrate that the proposed algorithm could significantly reduce the LR complexity by up to 90% multiplications and 99% divisions of brute-force LR while maintaining the system performance.

We propose a reduced-complexity genetic algorithm for intrusion detection of resource constrained multi-hop mobile sensor networks. Traditional intrusion detection mechanisms have limited applicability to the sensor networks due to scarce battery and processing resources. Therefore, an effective scheme would require a power efficient and lightweight approach to identify malicious attacks. The goal of this paper is to evaluate sensor node attributes by measuring the perceived threat and its suitability to host local monitoring node (LMN) that acts as trusted proxy agent for the sink and capable of securely monitoring its neighbors. Security attributes in conjunction with genetic algorithm jointly optimizes the placement of monitoring nodes (i.e., LMN) by dynamically evaluating node fitness by profiling workloads patterns, packet statistics, utilization data, battery status, and quality-of-service compliance.

A novel hard-decision decoding algorithm for low-density parity-check (LDPC) codes is proposed in this paper. This algorithm employs the correlation information among the column vectors of the parity-check matrix and syndrome vector for decoding. It does not require soft information, and has low decoding complexity. Simulation results show that the proposed decoding algorithm could provide an effective tradeoff between error performance and decoding complexity.

We propose a reduced-complexity genetic algorithm for dynamic deployment of resource constrained multi-hop mobile sensor networks. The goal of this paper is to achieve optimal coverage and improved battery life using dynamic power scaling (DPS) and improved fitness function. DPS exploits idle times, packet delay guarantees, performance and workload data using additional controls related to sensor power states and transmission power. The dynamic power scaling in conjunction with genetic algorithm jointly optimizes power states and topologies by dynamically monitoring workloads, packet arrivals, utilization data and quality-of-service compliance. This results in minimization of the power consumption of the sensor system while maximizing the sensor objectives.

This paper presents a reduced-complexity maximum a posteriori probability (MAP) channel estimator with iterative data detection for orthogonal frequency division multiplexing (OFDM) systems over mobile multiple-input multiple- output channels. The optimal MAP estimator needs to invert an NNTx NNTdata-dependent matrix each in OFDM symbol interval, where N is the number of subcarriers and NTis the number of transmit antennas. We derive an expectation maximization (EM) algorithm with low-rank approximation to avoid inverting large-size matrices, and thus drastically reduce the receiver complexity. In the iterative process, channel parameters are initially obtained by a least square (LS) estimator for temporary symbol decisions. Then, inter-carrier interference (ICI) due to fast fading is approximated and canceled. Finally, the temporary symbol decisions and the ICI-canceled received signals are processed by the EM-based MAP estimator to refine the channel state information for improved detection. The proposed scheme achieves about 2 dB gain over the LS scheme in channels with medium to high normalized Doppler shifts.

This letter proposes a hybrid decision-feedback equalizer (HDFE) for DS-CDMA systems. The proposed HDFE is carried out in two stages to improve the accuracy of the feedback signals by exploiting the spreading gain in the feedback filter. The spread signals for a symbol are buffered and then detected, after which re-spreading is applied to generate feedback signals at the chip level. Through the use of symbol detection for feedback filtering, more accurate feedback signals are achieved. Simulation results demonstrate the superior error performance of the proposed scheme over the frequency domain linear equalization (FD-LE) and RAKE schemes in highly dispersive channels.

Existing space-time codes have focused on multiple- antenna systems with linear modulation schemes such as phase- shift keying and quadrature amplitude modulation. Continuous phase modulation (CPM) is an attractive scheme for digital transmission because of its constant envelope which is needed for power efficient transmitters. Recent research has shown that space-time coded CPM can achieve transmit diversity to improve performance while maintaining the compact spectrum of CPM signals. However, these efforts mainly combine space- time coding (STC) with CPM to achieve spatial diversity at the cost of a high decoding complexity. In this paper, we design space-time block codes (STBC) for binary CPM with modulation index h = 1/2 and derive low-complexity receivers for these systems. The proposed scheme has a much lower decoding complexity than STC CPM with the Viterbi decoder and still achieves near-optimum error performances.

Ultrawideband communications often occur in heterogeneous networks where different receivers have different complexity and energy consumption requirements. In this case it is desirable to have a modulation scheme that works well with coherent receivers as well as simpler receivers, namely transmitted-reference (TR) receivers. In particular, we consider a TR scheme that employs slightly frequency-shifted reference (FSR) signals [15] and thus avoids one of the main drawbacks of conventional TR schemes, namely the need to implement a delay line. We propose and analyze a modulation scheme that works well with both FSR receivers (where it has the same performance as conventional TR modulation), and coherent receivers. Coherent receivers receiving conventional TR modulation suffer a 3 dB penalty, because they cannot make use of the energy invested into the reference pulse. Our proposed scheme avoids this drawback by including a data preprocessor that can be viewed as a nonsystematic rate-1/2 convolutional code with a high constraint length. These codes give 1.5 dB gain over our previously proposed constraint-length-two systematic codes at a BER of 1 times 10-4in 802.15.3a CM4 multipath fading channels.

This paper proposes a directional medium access control (DMAC) algorithm for wireless communication networks operating in the 60 GHz bands. Wireless communications using the 60 GHz spectrum must overcome many challenges that the conventional systems operating in the lower frequency bands do not encounter. These are mainly caused by the special characteristics of the 60 GHz signal such as its lack of penetration ability. Thus, information on whether the communications link has a line-of-sight (LOS) component or not is critical to optimize 60 GHz systems. We propose an efficient approach to determine the presence of a direct path between transmitter and receiver, which will be used to determine if the environment is LOS or non-LOS. We also propose a direction finding approach to be used with the proposed DMAC algorithm. We compare the performance of the proposed algorithm with that of the traditional MAC protocol when applied to 60 GHz systems, since there are no existing DMAC protocols that are specifically designed for 60 GHz communications.

We propose a reduced-complexity genetic algorithm for secure and dynamic deployment of resource constrained multi-hop mobile sensor networks. Mobility and security are relatively expensive operations since they involve both communication and computation. Furthermore, these operations have to co-exist with optimal node and route assignments. The goal of this paper is to achieve optimal secure coverage and improved battery life using dynamic re-locatability. The genetic algorithm is used to adaptively configure optimal position and security attributes by dynamically monitoring network traffic, packet integrity, and battery usage. This results in minimization of the power consumption of the sensor system while maximizing the sensor objectives (coverage and exposure).

This paper derives a phase-noise suppression scheme for orthogonal frequency division multiplexing (OFDM) systems. This scheme is a maximum likelihood approach that exploits the pilot subcarriers that exist in almost all practical OFDM systems. Compared with existing work, the proposed scheme has the following features: (a) we focus on phase-noise suppression for time-varying environments, which also cause intercarrier interference (ICI) along with phase noise. Most of the existing work considers quasi-static channels and tries to suppress the common phase error (CPE). As will be shown in this paper, in more realistic fast time-varying channels, the CPE term becomes much more complex and might significantly degrade the performance of estimators that assume a time-invariant channel, (b) the proposed algorithm is applicable for the two most common types of local oscillators: phase-locked and free-running, which have different phase-noise characteristics, (c) the proposed phase-noise suppression scheme does not require perfect channel equalization, whereas in some of the existing work the channel is assumed to be known a priori, and (d) doubly-selective fading is considered rather than assuming a time-invariant and/or flat- fading channel.

Many broadband wireless access (BWA) systems, such as IEEE 802.16e, support high-mobility users traveling at vehicular speeds. BWA systems capable of high data rates and low bit-error rates typically require micro-cell or pico- cell deployments. High-mobility users usually need to perform frequent handovers in smaller cell structures, which could drastically increase system overhead and thus degrade the overall network performance. This paper presents a new handover decision algorithm for BWA systems, called predictive base station switching (PBSS). PBSS makes use of the mobile speed and direction information to reduce the number of handovers without degrading the received signal level. It is demonstrated via simulation results that PBSS performs better than existing algorithms based on signal levels and distance information, even when the mobile stations move randomly or when accurate direction and speed information is unavailable.

Ad hoc wireless networks are more vulnerable to malicious attacks than traditional wired networks due to the silent nature of these attacks and the inability of the conventional intrusion detection systems (IDS) to detect them. These attacks operate under the threshold boundaries during an intrusion attempt and can only be identified by profiling the complete system activity in relation to a normal behavior. In this paper we discuss a control-theoretic Hidden Markov Model (HMM) strategy for intrusion detection using distributed observations across multiple nodes. This model consists of a distributed HMM engine that executes in a randomly selected monitor node and functions as a part of the feedback control engine. This drives the defensive response based on hysteresis to reduce the frequency of false positives, thereby avoiding inappropriate ad hoc responses.

This paper proposes a novel hybrid decision-feedback equalizer (HDFE) for direct sequence code-division multiple-access (DS-CDMA) systems to improve their performance in highly time-dispersive fading environments. In the proposed scheme, despreading and re-spreading are integrated in the feedback process to improve the accuracy of feedback signals. Instead of performing chip detection to obtain the instantaneous feedback signals as in the conventional HDFE, the authors buffer the spread signals for a symbol, carry out the despreading, and then apply symbol detection to derive the feedback signals. In the feedback process, re-spreading is applied since equalization must be implemented at 'chip-level'. Through the use of symbol detection and re-spreading, more accurate feedback signals are achieved. Additionally, the proposed method effectively mitigates the effect of error propagation that may dramatically degrade the performance of conventional decision-feedback equalization schemes. Simulation results demonstrate the superior error performances of the proposed scheme over the conventional HDFE and RAKE schemes in highly dispersive channels such as those described in the recommendation ITU-M.1225 for mobile communications.

We propose a practical SVD-based scheduling technique for MIMO broadcast channel. Multiuser diversity is exploited by scheduling transmissions simultaneously to a group of users who have the best instantaneous channel quality. In order to avoid the inter-user interference, we use a transmit preprocessing technique which decomposes the multiuser MIMO downlink channel into multiple parallel independent single-user MIMO channels. Simulation results show that the proposed suboptimal multiuser scheduling algorithm achieve almost the same bit error rate performance as the optimal scheduling algorithm.

This paper considers signaling schemes for heterogeneous ultrawideband communications networks that contain both coherent (rake) and transmitted-reference (TR) receivers. While coherent receivers are capable of receiving TR signals, they do so with a 3 dB penalty, because they cannot make use of the energy invested into the reference pulse. We propose a new signaling scheme that avoids this drawback, by encoding redundant information on the reference pulse. The resulting scheme does not affect the operation of a TR receiver, while recovering the 3 dB penalty and furthermore providing an additional 1.7 dB coding gain to a coherent uncoded binary scheme. This can be explained by interpreting the scheme as a trellis-coded modulation. We also provide an alternative implementation that can be viewed as a recursive systematic convolutional encoder. Combining this version further with a simple forward error correction encoder results in a concatenated code that can be decoded iteratively, providing a bit-error rate of 10-3at 2.8 dB signal-to-noise ratio in additive white Gaussian noise. The convergence behavior of this iterative code is analyzed by using extrinsic information transfer charts.

This paper begins with a review of CDMA based 2-3G systems from a network perspective. In particular, the challenges faced by current CDMA technologies are addressed. We will show that many advanced operational requirements in future 4G networks, such as high-speed burst traffic, cross layer network design, seamless integration of different networks with and without infrastructure, will make the current CDMA technologies unsuitable due to their rigid and voice-centric physical (PHY) layer architecture. To respond to the call for CDMA innovation, a new physical layer architecture, namely Orthogonal Complementary Coded CDMA with Offset Stacking (OCC-CDMA/OS) spreading scheme, is proposed in this paper for its possible applications in futuristic wireless networks. One of the most important features of OCC-CDMA/ OS PHY architecture is its unique elasticity, which facilitates implementation of a fully-adaptive CDMA transceiver to work harmonically with various advanced upper-layer designs in 4G networks. Many other technical issues on CDMA based 4G networks will also be discussed. It is concluded that OCC-CDMA/OS has a great potential for its applications in future 4G wireless.

This paper derives a maximum likelihood Doppler frequency estimator for orthogonal frequency division multiplexing (OFDM) systems in time-varying multipath channels. The proposed scheme is a frequency-domain approach that utilizes pilot subcarriers, which are commonly implemented in most practical systems. Time-varying fading causes intercarrier interference (ICI) in OFDM systems. Thus, in the proposed estimator, the effect of ICI is taken into consideration with a proper model for accurate results. The estimator can be implemented using a finite impulse response (FIR) filter bank whose coefficients can be pre-calculated and stored in order to lower the computational complexity. We evaluate various methods to improve the estimation accuracy and analyze their complexity-performance tradeoffs. We also derive the Cramér-Rao bound and provide simulation results to quantify the performance of the proposed algorithm.

In this paper we propose a reduced-complexity genetic algorithm for optimization of multi-hop sensor networks. The goal of the system is to generate optimal number of sensor-clusters with cluster-heads. It results in minimization of the power-consumption of the sensor-system while maximizing the sensor objectives (coverage and exposure). The genetic algorithm is used to adaptively create various components such as cluster-members, cluster-heads, and next-cluster. These components are then used to evaluate the average fitness of the system based on the sequence of communication links towards the sink.

Existing space-time codes have focused on multipleantenna systems with linear modulations such as phase-shift keying or quadrature amplitude modulation. Continuous phase modulation (CPM) is an attractive scheme for digital transmission because of its constant envelope which is needed for power-efficient transmitters. Recent research has shown that space-time coded CPM can achieve transmit diversity to improve performance while maintaining the compact spectrum of CPM signals. However, these efforts mainly combine space-time trellis code (STTC) with CPM to achieve spatial diversity at the cost of a high decoding complexity. In this paper, we design space-time block codes (STBC) for Gaussian minimum shift keying (GMSK), a special case of CPM with modulation index 1/2. This scheme has a much lower decoding complexity than STTC CPM and still maintains excellent diversity performances.

In an era of cooperating ad hoc networks and pervasive wireless connectivity, we are becoming more vulnerable to malicious attacks. Many of these attacks are silent in nature and cannot be detected by the conventional intrusion detection system (IDS) methods such as traffic monitoring, port scanning, or protocol violations. These sophisticated attacks operate under the threshold boundaries during an intrusion attempt and can only be identified by profiling the complete system activity in relation to a normal behavior. In this paper we discuss a hidden Markov model (HMM) strategy for intrusion detection using a multivariate Gaussian model for observations that are then used to predict an attack that exists in a form of a hidden state. This model is comprised of a self-organizing network for event clustering, an observation classifier, a drift detector, a profile estimator, a Gaussian mixture model (GMM) accelerator, and an HMM engine. We use this method to predict the intrusion states based on observation deviation from normal profiles or by fitting it into an appropriate attack profile.

We propose an ultra-wideband (UWB) scheme that employs chirp waveforms. Signals satisfying the Federal Communications Commission (FCC) requirements for UWB applications are formed by using multiple linear frequency-modulated (chirped) waveforms. This scheme has the merits of both the multiband orthogonal frequency-division multiplexing (OFDM) UWB scheme such as continuous-wave transmission, and the pulsed UWB scheme, such as accurate timing, imaging capabilities, and rich frequency diversity. Another advantage unique to the proposed scheme is that completely passive, low-cost implementation of matched filters/correlators using surface acoustic wave devices is possible, whereas OFDM-UWB must rely on high-speed sampling combined with powerful digital signal processing. We present the details of chirp waveforms for UWB signaling, explore the correlation properties of the multicodes, and study the receiver structures. We also derive the error performance of the proposed scheme in indoor lognormal fading environments and discuss issues with the proposed scheme.

In this paper, we study the impact of time-selective fading on quasi-orthogonal space-time (ST) coded orthogonal frequency-division multiplexing (OFDM) systems over frequency-selective Rayleigh fading channels. OFDM is robust against frequency-selective fading, but it is more vulnerable to time-selective fading than single-carrier systems. In ST-OFDM, channel time variations cause not only intercarrier interference among different subcarriers in one OFDM symbol, but also intertransmit-antenna interference. We quantify the impact of time-selective fading on the performance of quasi-orthogonal ST-OFDM systems by deriving, via an analytical approach, the expressions of carrier-to-interference and signal-to-interference-plus-noise ratios. We observe that system error performance is insensitive to changes in vehicle speeds and the channel power-delay profile, but very sensitive to changes in the number of subcarriers. We also evaluate the performance of five different detection schemes in the presence of time-selective fading. We show that although there exist differences in their relative performances, all these detection schemes suffer from an irreducible error floor.

Multiple-input multiple-output (MIMO) antennas can be combined with orthogonal frequency division multiplexing (OFDM) to achieve diversity gain and/or to increase system spectral efficiency through spatial multiplexing. In this letter, we derive the probability density function (pdf) expressions of the condition number (i.e., the maximum-to-minimum-singular-value ratio, MMSVR) of the channel state information (CSI) matrix. We show that this ratio is directly related to the noise enhancement in open-loop MIMO systems and provides a significant insight on the overall system capacity. The pdf of this ratio could be used to predict the relative performances of various MIMO configurations without complex system-level simulations. The pdf can also be used to compute the probability of whether certain channels fail in the high-throughput mode. Extensive simulations are performed to validate the accuracy of the closed-form pdf of the MMSVR derived in this letter

Orthogonal frequency division multiplexing (OFDM) is robust against frequency selective fading, but it is very vulnerable to time selective fading. In quasi-orthogonal space-time coded OFDM (ST-OFDM) systems, channel variations cause not only inter-carrier interference among different subcarriers in one OFDM block, but also inter-transmit-antenna interference (ITAI). When applied in fast fading channels, common ST-ODFM receivers usually suffer from an irreducible error floor. In this letter, we apply frequency-domain correlative coding combined with a modified decision-feedback detection scheme to effectively suppress the error floor of quasi-orthogonal ST-OFDM over fast fading channels. The effectiveness of the proposed scheme in mitigating the effects of channel time selectivity is demonstrated through comparison with existing schemes such as zero-forcing, two-stage zero-forcing, and sequential decision feedback estimation

The need for effective capture of multipath energy presents a key challenge to receiver design for pulsed ultra-wideband (UWB) systems operating in non-line-of-sight propagation environments. Conventional RAKE receivers can capture only a fraction of the received signal energy under practical implementation constraints, and have to deal with stringent synchronization and channel estimation requirements. Transmit-reference and autocorrelation receivers can effectively collect energy from all the received multipath components without explicit channel estimation, but the detection performance is limited by noise enhancement effects and the data rate drops by 50% because of pilot symbol overhead. In this paper, we develop decision-directed autocorrelation (DDA) receivers for effective multipath energy capture at low complexity. Operating in an adaptive decision-directed mode, the proposed DDA methods can considerably lower the noise level in the self-derived template waveform, thus improving overall detection performance. There is little loss in energy efficiency since no reference pilots are required during adaptation. Analytical performance analysis along with corroborating simulations is performed to evaluate the error performance of the proposed receivers in indoor lognormal fading channels

We analyzes the prerake diversity combining schemes for pulsed ultrawideband (UWB) systems to shift the signal processing needs from the receiver to the transmitter. We consider the more realistic case that received multipath pulses could overlap with one another and its optimization based on the zero-forcing and the eigenanalysis technique. We show that in the presence of inter-pulse interference, the optimum linear prerake combining scheme in the sense of maximizing the received SNR performs the same as a conventional rake receiver with maximal ratio combining. Since for UWB systems it is important to consider the effects of narrow-band interference (NBI), we also analyze the different behaviors of prerake and rake schemes in the presence of NBI

Receive diversity yields a higher signal-to-noise ratio (SNR) than transmit diversity when the total transmitted power and diversity order are the same. However, if the transmitter has complete or partial knowledge of channel, the SNR gap between these two schemes can be reduced. This paper introduces an adaptive power allocation scheme for space-time block coded (STBC) multiple-antenna systems to improve system performance. For any set of channel fading coefficients, the transmit power scaling factors are controlled by a single design parameter u. The proposed adaptive power allocation scheme improves the instantaneous SNR at the receiver. Special choices of u result in some existing STBC schemes. Performance gain of the proposed scheme over the conventional equal-power scheme under the condition of perfect and imperfect feedback is studied. The maximum achievable SNR gain limit over the conventional scheme is also derived.

Orthogonal space-time block codes provide full diversity, and maximum-likelihood (ML) decoding for orthogonal codes can be realized on a symbol-by-symbol basis. It has been shown that rate-one complex orthogonal codes do not exist for systems with more than two transmit antennas. For a general system with N transmit and M receive antennas, it is very desirable to design rate-one complex codes with full diversity. In this letter, we provide a systematic method of designing rate-one codes (real or complex) for a general multiple-input multiple-output system. Full diversity of these codes is then achieved by constellation rotation. A generalized, reduced-complexity decoding method for rate-one codes is also provided.

This paper presents a decision-directed (DD) maximum a posteriori probability (MAP) channel-estimation scheme for multiple-input multiple-output (MIMO) time-varying fading channels. With the estimate of the channel matrix for the current symbol interval, a zero-forcing (ZF) receiver is applied to detect the spatially multiplexed data on a symbol-by-symbol basis. Symbol decisions are then fed to the channel predictor for estimation of channel coefficients in future symbol intervals. Simulated error performance of a ZF receiver with the DD MAP and perfect channel estimates is provided and compared.

Multiple-input multiple-output (MIMO) techniques are applied to ultrawideband (UWB) systems to achieve high-rate communications over indoor wireless channels. The receiver employs a zero-forcing (ZF) scheme to separate N parallel transmitted data streams for each resolvable multipath component. A RAKE is then applied to combine the ZF paths carrying information of the same symbol to form the decision variable. Analytical error rate expression of an (N,M,L) system (N transmit antennas, M receive antennas, and L paths combined) over a pragmatic indoor log-normal fading channel is derived, which captures the diversity order by a single degree-of-freedom parameter.

This paper analyzes the impact of receive fading correlation on the error performance of a multiple-input multiple-output (MIMO) system that employs a zero-forcing detection scheme over frequency-nonselective Rayleigh fading channels. Error rate expressions as a function of the eigenvalues of the fading correlation matrix and the number of transmit and receive antennas are derived. Numerical results indicate that MIMO systems are resistant to receive fading correlation.

In this paper, the error performance of a frequency-hopped, multi-band ultra-wideband (UWB) system over indoor lognormal fading channels is analyzed. An equal gain combiner is adopted to combine the signal energy contained in a subset of the resolvable multipath components.

An analytical treatment of the performance of frequency hopped Gaussian frequency shift keying (GFSK) with differential detection in time-varying Rayleigh fading channels corrupted by additive white Gaussian noise (AWGN) is presented. Closed-form expressions for the bit error rate (BER) as a function of E/sub b//N/sub 0/, modulation index, channel Doppler shift, and the time-bandwidth product of the pre-modulation filter are derived. A pilot symbol-assisted scheme to lower the error floor caused by frequency hopping is analyzed.

This paper describes a differentially coherent decorrelating detector for a K-user reverse link code-division multiple-access environment that exhibits time-varying Rayleigh fading. The channel is modeled as providing only a single fading path for each user and with no additional means to achieve diversity. The design of the detector is based on using fractionally sampled matched filter outputs to simultaneously achieve two goals: 1) the novel realization of a one shot decorrelator with lower computational complexity and 2) the forming of the maximum-likelihood decision rule on the decorrelated outputs, which results in an effective increase of the correlation in the fading process. Analytical evaluation and simulation of the error probability of the detector demonstrates significant lowering of the error floor in comparison to the decorrelating detector that employs conventional differentially coherent detection.