This paper revisits both the uplink and downlink two-user multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) systems. We present a novel concept of matrix decomposition called simultaneous generalized triangular decomposition (SGTD). The main idea is to simultaneously decompose two matrices into predetermined triangular forms while providing flexibility in designing the ratios of the diagonal elements. For uplink MIMO-NOMA, the proposed SGTD enables interference-free transmission between users by transforming MIMO channels into two triangular forms and successively decoding and canceling data streams. Unlike existing simultaneous diagonalization or triangularization approaches with fixed diagonal values, the proposed method provides flexibility in adjusting the diagonal elements of the triangular matrices. This adaptability makes it particularly advantageous for meeting specific design requirements, such as maximizing the weighted sum rate and ensuring stable transmission across each spatial stream. As an example, an optimized design is provided to maximize the weighted sum rate within the proposed framework. A similar approach is also proposed to develop a new precoding design for downlink MIMO-NOMA. Extensive simulations demonstrate that, for both uplink and downlink scenarios, the proposed scheme outperforms state-of-the-art MIMO-NOMA and orthogonal multiple access (OMA) systems.

Researchers from both academia and industry have started exploring the potential of sixth generation cellular networks, envisioning novel concepts and futuristic capabilities. An empirical analysis of real-world fifth generation (5G) deployments serves a compass to direct the next stage of evolution and provides insights on the additional improvements required for the future services and applications. However, acquiring real-world measurement data at a city or county scale poses substantial challenges in terms of time and cost. To address this issue, this paper presents a practical and cost-effective data collection testbed and a methodology that harnesses the existing services provided by municipal council authorities, including curbside waste collections to generate large-scale realtime network coverage maps. Rich datasets of measurement data collected from multiple fourth generation (4G) and 5G cells over seven months in Nottingham, United Kingdom (UK) for all four major UK network operators, namely EE, Vodafone, O2, and Three Mobile, are provided. These large datasets can be utilized for analyzing network deployment options, coverage, and future service provisioning as well as designing and training artificial intelligence and machine learning algorithms to further optimize the mobile networks. In addition, the paper reviews the latest empirical 5G network analysis tools and techniques, which were not seen in previous generations.

The hybrid reconfigurable intelligent surface (RIS) architecture consisting of both active elements (AEs) and passive elements (PEs) is promising for use in milimeter wave wireless communication systems. In this paper, we propose a novel scheme for selection of AEs in this kind of RIS-aided system to enhance the channel estimation performance. The RIS is first partitioned into multiple subregions and an appropriate number of AEs are then selected strategically from each subregion according to some criteria. A greedy coordinate descent algorithm is also proposed to reduce the computational complexity of the selection process. With the selected AEs, channel estimation is performed between the user equipment and RIS based on compressed sensing. Computer simulation results demonstrate that the proposed AE selection scheme induces a significant performance improvement in channel estimation over the random AE selection approach.

Traditional grid-based compressed sensing algorithms usually suffer from the base mismatch effect in channel estimation problems. To address this, we propose a novel gridless uplink/downlink (UL/DL) channel estimation strategy for millimeter wave (mmWave) massive multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. By exploiting inherent sparsity in the angle-delay domain of the mmWave channel, we first formulate the UL channel estimation problem as a joint sparse signal recovery problem. Then, we introduce the reweighted atomic norm for enhancing angular resolution of the mmWave channel on continuous Fourier dictionaries; we suggest a novel reweighted atomic norm minimization (NRAM) algorithm to solve the channel estimation problem by leveraging the Hankel-Toeplitz block model with multiple measurement vectors (MMVs), and the original NRAM problem is approximated by the solution of a semi-definite programming (SDP) problem with structured sparsity, which is efficiently solved by a low-complexity alternating direction multiplier method (ADMM). Subsequently, in the frequency division duplex (FDD) system, we design a simplified DL channel estimation scheme by leveraging the angle-delay reciprocity of UL and DL channels. This scheme reconstructs the DL channel matrix using the angle and path delay estimated from the UL channel, along with the channel gain obtained through least squares (LS). Finally, simulation results validate that our proposed approach achieves superior channel estimation accuracy and reduces pilot overhead compared to conventional UL/DL channel estimation techniques.

This paper investigates the outage performance of a two-user downlink non-orthogonal multiple access (NOMA) system with imperfect channel state information at the transmitter (CSIT). A general closed-form outage probability expression is derived under consideration of imperfect successive interference cancellation (SIC) for both NOMA users based on instantaneous channel estimates and the corresponding mean-squared errors. With the derived expression, a low-complexity power allocation formula is proposed for outage balancing, i.e., minimizing the maximum user outage probability, in order to provide robustness against channel uncertainty. As compared with a previous iterative power allocation method for the same purpose, the proposed one involves much lower complexity and achieves a significantly better balance between the outage performance for the two users when there exist SIC errors.

This paper presents a time synchronization scheme for orthogonal time frequency space (OTFS) systems by utilizing an embedded impulse pilot structure within each OTFS block in the delay-Doppler domain. The time synchronization process is equivalent to a two-stage timing offset (TO) estimation process that operates in the delay-time domain according to two modified timing metrics. The first stage identifies TO in the delay dimension, while the second stage determines TO in the time dimension. As compared with a previous related method, the proposed one achieves better performance, in terms of the probability of perfect time synchronization and the TO estimation error, with only a slight increase in complexity. This improvement enables itself to work at lower pilot power and thus to relieve the peak-to-average power ratio issue associated with OTFS systems.

Lattice partition (LP) is a promising technique to design power-domain non-orthogonal multiple access (NOMA) systems because it can approach the capacity region with reduced receiver complexity. Most of LP-based NOMA works have been focused on outage and capacity analyses. In this letter, theoretical expressions of the bit error rate (BER) are derived for a two-user LP-based NOMA system using bipolar pulse amplitude modulation. The derived BERs agree well with computer simulation results. Since a two-dimensional LP-based NOMA signal can be decomposed into two orthogonal one-dimensional LP-based NOMA signals, the analytical results can be easily extended to a quadrature-amplitude modulation case.

This paper considers a two-user downlink multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) system using minimum mean-squared error (MMSE) detection under imperfect channel estimation. By taking account of both errors in channel estimation and MMSE detection, we derive approximated users' capacities and design a closed-form power allocation scheme to maximize the minimum (max-min) of them. The design problem is equivalent to max-min optimization of users' signal-to-interference-plus-noise ratios (SINRs), and the solution can be obtained by SINR balancing. The proposed power allocation scheme involves solving two quadratic equations, and is easy to implement in practical applications. As compared with an existing robust MIMO-NOMA power allocation method based on generalized singular value decomposition and SINR balancing, the proposed one offers slightly worse bit-error-rate performance with much lower complexity.

This paper presents a joint fine time synchronization and channel estimation scheme based on deep learning (DL) for wireless communication systems. The scheme adopts a specific training sequence structure with both cyclic prefixing and cyclic postfixing. It works excellently without setting a search range and a threshold as required by the conventional method based on the same training sequence structure. Simulation results demonstrate that the proposed DL-based scheme has significant performance gains for most cases as compared with the conventional method. With improved time synchronization, better channel estimation performance is achieved accordingly.

This paper presents a new power allocation method for two-user downlink non-orthogonal multiple access (NOMA) systems with imperfect channel estimation. Given channel estimates and the corresponding mean-squared error (MSE) information, capacity lower bounds are used to determine an upper bound of the system outage probability (SOP) based on the transmission rate requirements of both users. Subsequently, a closed-form power allocation solution is derived for the two users such that the SOP upper bound is minimized under a total power constraint. The solution requires only a few numerical operations to calculate the power allocation factor according to the MSE information of channel estimation. Its complexity is lower than existing closed-form or iterative solutions. Simulation results demonstrate that the proposed method achieves pretty good performance in terms of the SOP upper bound and the bit error rate for different transmission rate requirements.

This paper presents a new filter bank multicarrier (FBMC) transmission scheme that uses the real-valued discrete Hartley transform (DHT) for both multicarrier modulation and demodulation, rather than the complex-valued inverse discrete Fourier transform (IDFT) and DFT for multicarrier modulation and demodulation respectively in conventional FBMC systems. The DHT-FBMC scheme is with quadrature amplitude modulation (QAM) and adopts a pair of orthogonal or nearly orthogonal pulse shaping filters, one for even-numbered subcarriers and the other for odd-numbered subcarriers, to mitigate self-interference. The proposed method potentially has advantages in terms of performance and implementation, due to the fact that it possesses some distinct channel diversity on mirror-symmetrical subcarriers and involves identical real-valued transform operations at the transmitter and receiver. In contrast to existing DFT-FBMC systems using QAM or offset QAM (OQAM), the DHT-FBMC scheme using QAM achieves better bit-error-rate performance with comparable or reduced computational complexity.

In this paper, the problem of downlink non-orthogonal multiple access (NOMA) over slow fading channels is studied. Full-channel state information (CSI) is assumed at the receivers, while only the statistical CSI is assumed to be available at the transmitter. A novel lattice-partition-based scheme is proposed which, according to statistical CSI, employs discrete inputs from appropriately designed constellations carved from a lattice, rather than continuous Gaussian inputs as used in most existing works. Theoretical analysis shows that for any outage probability smaller than 63.21%, which covers almost all the cases of practical interest, the proposed scheme with single-user decoding, i.e., without successive interference cancellation (SIC) is able to approach the NOMA outage capacity region within a constant gap, independent of the signal-to-noise ratio, and the number of users. Simulation results fortify the effectiveness of the proposed scheme by showing that the approach without SIC can achieve outage rates that are very close to the outage capacity region and the gap becomes even smaller when SIC is employed.

In this paper, we develop a lattice-partition-based downlink non-orthogonal multiple access (NOMA) scheme for slow fading channels without successive interference cancellation (SIC) at the receivers. With the knowledge of statistical channel state information at the transmitter, our scheme uses a finite constellation drawn from an n-dimensional lattice and employs channel coding on top of it. The outage rates achieved by our scheme without SIC are analyzed and their gaps to the multiuser outage capacity are derived. We show, both theoretically and numerically, that our scheme without SIC is capable of approaching any point in the multiuser outage capacity region within a constant gap when the required outage probability is smaller than 63.21%, which covers almost all cases of practical interest. Simulation results based on various lattices are provided and demonstrate that the near-capacity performance can be attained by our NOMA scheme without SIC.

In this paper, we propose a new preamble design for channel estimation in filter bank multicarrier (FBMC) systems using offset quadrature amplitude modulation (OQAM). The proposed preamble structure is formed by duplicating a preamble unit (PU) defined as a 3×3 symbol matrix in a time-frequency lattice. The center element of the PU could be a real symbol "1" surrounded appropriately by imaginary symbols "j" and "-j" such that the mean-squared error (MSE) of channel estimation is minimized for the center subcarrier. The center element could also be an imaginary symbol "j" with surrounding symbols set as "1" or "-1" in a similar way for MSE minimization. The proposed preamble design can be regarded as an improved version of the extended interference approximation method with real or imaginary symbols (E-IAM-C) for channel estimation in FBMC/OQAM systems. With the estimated channel gains of all center subcarriers, we can calculate the remaining subcarriers' channel gains simply by linear interpolation. Theoretical analysis and simulation results show that the proposed preamble design for channel estimation outperforms E-IAM-C in terms of the MSE, bit error rate, and computational complexity.

In this paper, we investigate resource allocation for a downlink multicarrier non-orthogonal multiple access (NOMA) system with a base station and an even number of users, where every two users are grouped together to share some subcarriers for data transmission. We formulate an optimization problem in terms of subcarrier and power allocation to maximize the system capacity under a specific proportional user fairness constraint. For a given subcarrier allocation, we first derive an optimal power allocation factor for two users on a subcarrier subject to maximizing the minimum user capacity on the subcarrier. With such optimal power allocation factors for all subcarriers, a low-complexity suboptimal algorithm is then proposed for joint subcarrier and power allocation to meet the proportional user fairness constraint. Simulation results demonstrate that the proposed scheme provides better system capacity than the conventional orthogonal frequency division multiple access (OFDMA) scheme.

This paper presents a complex-valued discrete multicarrier modulation (MCM) system based on the real-valued discrete Hartley transform (DHT) and its inverse (IDHT). Unlike the conventional discrete Fourier transform (DFT), the DHT cannot diagonalize multipath fading channels due to its inherent properties, and this results in mutual interference between subcarriers of the same mirror-symmetrical pair. We explore this interference pattern in order to seek an optimal solution to utilize channel diversity for enhancing the bit error rate (BER) performance of the system. It is shown that the optimal channel diversity gain can be achieved via pairwise maximum likelihood (ML) detection, taking into account not only the subcarrier's own channel quality but also the channel state information of its mirror-symmetrical peer. Performance analysis indicates that DHT-based MCM can mitigate fast fading effects by averaging channel power gains of each mirror-symmetrical pair of subcarriers. Simulation results show that the proposed scheme has a substantial improvement in BER over the conventional DFT-based MCM system.

An eigenmode-selection approach was recently presented for relay precoding subject to the minimum/maximum sum of condition numbers of the effective multiple-input multiple-output (MIMO) channels in a two-way amplify-and-forward (AF) MIMO relay system. Although this method can achieve close-to-optimal performance, it would involve high search complexity for the solution in a relay precoding set of size 2·M!, where M is the degrees of freedom of the MIMO relay system. In this paper, we propose low-complexity relay precoder designs based on eigenmode selection for two-way AF MIMO relay systems. We first exploit the properties of condition numbers of the effective MIMO channels, and then present two set-reduction methods accordingly for eigenmode-selection precoding to minimize/maximize the sum of condition numbers. As compared with the original eigenmode-selection precoding scheme, the proposed designs reach similar performance but reduce the search complexity by a factor of M(M-1).

Cooperative relay systems have drawn much attention in recent years because they can use an appropriate number of relays to form a virtual multiple-input multiple-output (MIMO) scenario to improve communication links. Also, space frequency block coding (SFBC) is a prominent strategy for MIMO systems, and it has been widely adopted with orthogonal frequency division multiplexing (OFDM) to achieve both spatial and frequency diversity. One major problem associated with an SFBC-OFDM cooperative relay system is the existence of multiple carrier frequency offsets (CFOs), and this would cause serious intercarrier interference (ICI) and degrade the system performance greatly. In this paper, an improved transceiver design is proposed for two-relay SFBC-OFDM cooperative relay systems, where a modified SFBC encoder is adopted at the transmitter and a common CFO compensation unit, a modified SFBC decoder, and an iterative partial parallel interference cancellation (PIC) module are used at the receiver. The proposed design is computationally efficient and has a superior tolerance range of multiple CFOs. Simulation results demonstrate that it achieves better performance than previous related works.

In this paper, we first consider a downlink multiple- input multiple-output non-orthogonal multiple access (MIMO-NOMA) system with a base station and four users, where the users are equally divided into two clusters and inter-cluster interference is induced in transmission. Then we propose a joint clustering and precoding algorithm for the system such that not only the inter-cluster interference can be effectively eliminated but also the sum capacity can be enhanced. Specifically, a set of precoder pairs (one pair having two precoders for the two clusters) are constructed based on the eigenspaces of channel matrices, and one of them is selected to maximize the sum capacity. The proposed joint algorithm involves a high-complexity issue due to the need of exhaustive search for the best precoder pair. To reduce the search complexity, we explore the channel gain of each user and construct a reduced-size precoding set for selection. Combined with orthogonal frequency division multiplexing, the proposed four-user scheme is further extended to the general multiuser case, where every four users share a subcarrier for MIMO-NOMA transmission. Simulation results show that the proposed MIMO-NOMA scheme can provide more system capacity than a MIMO orthogonal multiple access approach.

In this paper, we present new relay precoder designs for two-way amplify-and-forward multiple-input multiple-output (MIMO) relay systems. We first derive the mean-squared error (MSE) matrices of the received signals at two terminals, and show that their behavior strongly depends on the singular values of the effective MIMO channels of the corresponding relay system. Motivated by this property, a set of relay precoders are constructed based on the singular vector subspaces of the MIMO channels, and one of them is selected for meeting a specific design criterion. Four design criteria are investigated, including the minimum sum of MSEs, the maximum sum of capacities, and the minimum or maximum sum of condition numbers, where the condition number is defined as the ratio of the largest to the smallest singular value of a MIMO channel. Compared to the conventional iterative methods, the proposed relay precoders based on minimizing the sum of MSEs or maximizing the sum of capacities achieve close performance while requiring much lower computational complexity. In contrast, the proposed designs based on minimizing or maximizing the sum of condition numbers provide further complexity reduction, with similar performance at high signal-to-noise ratios (SNRs) but a performance loss at low SNRs.

Space frequency block codes (SFBC) have been widely adopted with orthogonal frequency division multiplexing (OFDM) to achieve both spatial and frequency diversity. However, OFDM is very sensitive to carrier frequency offset (CFO), which would cause intercarrier interference (ICI) and degrade the system performance severely. In this paper, we propose a low-complexity partial parallel interference cancellation (PIC) based receiver with common CFO compensation, modified SFBC decoding, and iterative partial PIC for Alamouti coded SFBC-OFDM cooperative relay systems. For the proposed receiver, the received signal is first compensated by a common CFO value to mitigate the effect of different CFOs from the distributed relays, and then the result is processed by a modified SFBC decoder. The decoded data is subsequently fed back to reconstruct the ICI for use in the developed partial PIC procedure. As compared with a previous related work, the proposed partial PIC based receiver achieves better performance with lower computational complexity.

In this paper, we consider a two-way relay system where two terminals exchange their information via an amplify-and-forward relay in a bi-directional manner. Due to the two-way relay protocol, signals from both terminals travel through different cascaded channels, and this makes synchronization and channel estimation much more complicated than those in conventional one-way relay systems. To cope with these problems, we propose a joint time synchronization and channel estimation scheme based on a specific training sequence arrangement, where each terminal's training sequence consists of a perfect sequence (with an ideal auto-correlation function) attached by an appropriate cyclic prefix and postfix. The proposed scheme relies on a first channel tap selection process, whose performance is highly dependent on the choice of a threshold to distinguish the signal outputs from noise. By analyzing some possible probability density functions of the correlator output, we derive optimal thresholds for selection of the first channel tap. With these thresholds, the proposed scheme provides better time synchronization performance than the maximum-likelihood approach for low signal-to-noise ratio (SNR) cases; both have similar performance for high SNR cases. It is also shown that the proposed scheme involves much less computational complexity than the maximum-likelihood approach.

In this paper, we first propose a new cooperative multihop transmission structure for two-way amplify-and-forward (AF) relay networks, in which multiple single-antenna relays are considered and distributed between two sources. With the proposed transmission structure, a multihop network can be decomposed into several independent two-way two-hop AF relay systems. Based on the structure characteristics, we then present a cooperative two-way routing protocol based on geographic information, which mainly consists of a forwarder selection part and a relay selection part; the former aims to minimize the number of transmission hops, and the latter is used to improve the reliability of communication links. We obtain the coverage regions of available relays and forwarders based on an asymptotic symbol error probability (SEP) analysis, and then combine the results with geographic information for minimum-SEP relay selection and maximum-coverage forwarder selection. It is shown that the proposed approach provides better effective throughput performance than a related method. Simulation results are given to validate the analyses as well as to demonstrate the effectiveness of the proposed approach.

In this paper, we propose a 2×2 relay precoder design for two-way amplify-and-forward (AF) multiple-input multiple-output (MIMO) relay systems. By exploring the asymptotic behavior of the sum of mean-squared errors (sum-MSE) of the received signals at the two source nodes, we find that it is dominated by the smallest singular values (or the smallest eigenvalues) of the effective MIMO channels of the corresponding relay system. This implies that the sum-MSE performance strongly depends on the sum of the condition numbers of the effective MIMO channels, where the condition number of a MIMO channel is defined as the ratio of the largest to the smallest singular value. With this observation, unlike the conventional precoder designs that are obtained in an iterative manner based on minimizing the sum-MSE, the proposed design is derived by using the Gram-Schmidt process based on minimizing the sum of the condition numbers of the effective MIMO channels. Compared to conventional iterative methods, the proposed approach achieves close performance with much lower computational complexity for both perfect and imperfect channel estimations.

In this paper, we propose power allocation (PA) and jammer selection schemes based on a cooperative jamming strategy combined with a null-steering beamforming technique (CJ-NB strategy) for physical-layer security. Using the CJ-NB strategy, we first present an asymptotic optimal PA scheme, obtained by solving an achievable secrecy rate maximization problem, and then provide the corresponding achievable secrecy rate analysis. The analysis results show that the maximum achievable secrecy rate will become asymptotically saturated if the number of jammers is large enough. To avoid waste in the use of jammers, we also provide two jammer selection schemes that can determine the minimum number of jammers necessary to achieve almost the same secrecy rate as using all jammers for the CJ-NB strategy with the asymptotic PA scheme. One has lower computational complexity, and the other achieves better performance in reducing the number of jammers used. Finally, simulation results are given to demonstrate the effectiveness of the proposed schemes.

This letter presents a new positioning method based on recursive weighted least absolute value (RWLAV) optimization for wireless sensor networks. The proposed method is derived by minimizing a recursive-in-time cost function and can be realized in a decentralized and iterative manner. During each iteration, the target's location is computed by taking a weighted average (in terms of the measurement's reliability) of the previous location estimate and the local observation that is expressed as the difference between the previous location estimate and the current subgradient value. Computer simulation results show that the RWLAV method performs better than previous related methods.

This paper presents a new signal structure for spectrum sensing under active cognitive radio (CR) transmission (i.e., active sensing). Specifically, the known pilots used for the base station of primary users (PU) are duplicated and reallocated in the CR transmission signal properly so that there is no overlap between the reallocated pilot subcarriers and the original subcarriers. Given the CR signal structure, the signal received by a spectrum sensor of the CR system becomes correlated on the subcarriers when PU reoccupation occurs during the data-transmission periods, which makes it easy to detect PU activities by computing the spectral correlation function of the received signal. Both theoretical analyses and simulation results are given to demonstrate the effectiveness of the proposed active-sensing approach. The proposed method attains a detection probability of 0.99 and a false-alarm probability of 0.01 within 170 orthogonal frequency-division multiplexing symbols under a signal-to-noise ratio of -25dB and a signal-to-interference ratio of -20dB. The performance would be degraded under practical conditions, but is acceptable in most cases if the carrier frequency offset is less than 0.3. Compared with traditional cyclostationary feature detection, the proposed approach requires only about half the sensing time to achieve the same sensing accuracy, at about a 3% loss of throughput.

In this paper, we investigate a cooperative jamming strategy combined with a null-steering beamforming technique (CJ-NB strategy) for physical-layer security. To evaluate the achievable secrecy rate, the source input distribution is assumed to be Gaussian, and the achievable secrecy rate can be formulated as an optimization problem for power allocation (PA). By solving the problem, an asymptotically optimal PA is obtained with an exactly closed-form expression. In addition, we provide an asymptotic analysis of the achievable secrecy rate. The asymptotic result shows that the achievable secrecy rate is linearly proportional to the signal-to-noise ratio, but it will become saturated when the number of jammers is high enough. Therefore, we then develop a simple and efficient jammer selection algorithm to find an appropriate jamming set to achieve almost the same performance, but significantly reduce the number of jammers used compared with all the jammers performing the CJ-NB strategy. Finally, we provide simulation results to support our analyses.

In this paper, we propose a joint relay weighting (RW) and power allocation (PA) algorithm for a two-way amplify-and-forward relay system, in which each participating node is equipped with a single antenna, to minimize the sum of mean-squared errors (sum-MSE) of the received signals at two source nodes. The algorithm alternates between two parts: obtaining the optimal RW for a specific PA, which is derived as a closed-form solution, and searching the optimal PA under an obtained RW that minimizes the sum-MSE via a gradient-descent algorithm. It is shown that the diversity order of the system is one-half of the total number of relays. Computer simulation results show that the proposed RW-PA algorithm has better sum-MSE and sum of bit-error rates than the equal PA scheme.

In cognitive radio (CR) systems, the longer the sensing duration, the better the sensing performance will be; however, a long sensing duration would cause a large packet delay for CR transmission, which is not desirable for real-time applications. In this paper, we propose a media access control MAC layer model for CR networks and formulate a tradeoff problem between the sensing performance and the packet delay. We then consider quality of service metrics, including the packet drop rate and the achievable throughput when optimizing the sensing duration such that the average packet delay is minimized. Both theoretical and simulation results are given to demonstrate the effectiveness of the proposed approaches for CR networks.

In this paper, we investigate automatic repeat request (ARQ) protocols for a two-way amplify-and-forward relaying system. We first propose an outage-efficient ARQ protocol which exploits two-way retransmission for failure of reception at both terminals and one-way retransmission for failure of reception at only one terminal. This scheme significantly reduces the outage probability of the system at a cost of spectral efficiency loss due to the use of one-way retransmission. To fully utilize the channel resources, we also propose a spectral-efficient ARQ protocol that adopts two-way partial retransmission, instead of one-way retransmission, when reception failure occurs at only one terminal, where the corresponding source performs retransmission and the other source continues to transmit new data. Through an outage probability analysis, it is proved that both of the proposed ARQ protocols achieve full temporal diversity. Simulation results of them also show that the outage-efficient approach attains a lower outage probability, while the spectral-efficient approach achieves a higher effective throughput.

In this paper, we propose a synchronization scheme based on partial Zadoff-Chu sequences for cooperative MIMO systems. In the proposed training sequence design, partial Zadoff-Chu sequences are placed on disjoint sets of subcarriers in an interleaved manner. Such an arrangement not only guarantees frequency-domain training signal separation, but also produces separable time-domain training signals to lessen the mutual interference among the training signals in both the frequency domain and the time domain. Furthermore, propagation delays and carrier frequency offsets can be estimated solely in the time domain, while they are estimated in the time domain and the frequency domain, respectively, in most existing synchronization schemes for cooperative MIMO systems. The proposed training sequences also enjoy good auto-correlation and cross-correlation properties that improves synchronization performance.

This study presents an efficient location tracking algorithm to reduce the computational complexity of the conventional Kalman filtering algorithm. In the proposed location estimation and tracking approach, using the inherent message‐passing nature of factor graphs, the data information is passed efficiently between the variable nodes and the factor nodes by taking weights based on the message reliability, thus simplifying implementation of the Bayesian filtering approach for location tracking. Numerical simulations and experimental results show that the proposed location tracking scheme not only can achieve the location accuracy close to that of the Kalman filtering scheme, but also has lower computational complexity with decoupling approach.

In this paper, we investigate power allocation and relay selection problems for a two-way amplify-and-forward (AF) relaying system. We first derive asymptotic overall symbol error probabilities (AOSEPs) for the case of one relay cooperating with two sources with respect to the second-order channel statistics for both M-ary quadrature amplitude modulation (M-QAM) and M-ary phase-shift keying (M-PSK), and then present the corresponding optimal power allocation and relay selection schemes that minimize the AOSEPs. To achieve the full diversity order, we further propose alternative power allocation and relay selection methods by simply replacing the statistical channel information of the first scheme with instantaneous one. The diversity order of the second scheme is then verified by deriving the lower and upper bounds of the corresponding asymptotic overall outage probability. Computer simulation results are also given to support the analytical results.

In this paper, we propose an adaptive receiver for efficient intercarrier interference (ICI) cancellation in orthogonal frequency division multiplexing (OFDM) systems using two-path conjugate transmission. This receiver design is based on the phase rotated conjugate cancellation (PRCC) concept presented recently, where two individual phase rotations are employed on the two receive paths, rather than only one phase rotation is adopted for the two transmit paths in the PRCC scheme. We derive the optimal phase rotations using the criterion of maximizing the carrier-to-interference ratio, and then develop an adaptive normalized block least mean-squared algorithm to approach the optimal solutions. With such adaptive phase rotations in the receiver, the carrier frequency offset (CFO) variations due to the channel effect and the mismatch between oscillators at the transmitter and receiver can effectively be tracked without feeding back the CFO estimate to the transmitter as required in PRCC. Simulation results demonstrate that the proposed approach has better bit error rate performance than the PRCC and the conventional CC scheme for various time-varying channels, even when the CFO/channel estimation error is considered.

In this paper, we investigate the effect of channel estimation errors on the capacity of amplify-and-forward cooperative relay systems. Since an exact capacity expression in the presence of channel estimation errors is difficult to be found, we turn to derive its lower bound instead. Accordingly, by maximizing the derived lower bound, we propose power allocation schemes for both single-relay and multi-relay systems. For single-relay systems, an analytical solution for inequality constrained problem is too complicated to be obtained. Thus, we propose a gradient descent algorithm with a log-barrier function to solve the inequality constrained problem. For multi-relay systems, in terms of the channel estimates and the corresponding mean-squared errors, we provide a water-filling solution for the optimal power allocation among the relays. Simulation results show that the proposed power allocation schemes yield capacity gain compared with equal power allocation at low to medium signal-to-noise ratios.

In this paper, we propose an adaptive receiver design for OFDM-based cooperative relay systems using two-path conjugate transmission to achieve both diversity reception and intercarrier interference (ICI) cancellation. Considering that the relayed signals are affected by statistically independent channel fading gains and different frequency offsets, the proposed receiver applies not only phase rotations but also an amplitude scaling factor, whose values are optimized based on criteria of maximizing the carrier-to-interference ratio and minimizing the ICI power, respectively, on the two receiving paths to improve ICI cancellation performance. In order to track the channel and frequency offset variations under time-varying environments, we further develop an adaptive normalized block least mean-squared algorithm to update the phase rotations and the amplitude scaling. Simulation results demonstrate that the proposed adaptive receiver provides significant performance improvement over related works for OFDM-based cooperative relay systems.

In cooperative multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems, signals transmitted from cooperating terminals arrive at the receiver on distinct timing due to diverse propagation delays. Therefore, timing synchronization is even more challenging in cooperative MIMO systems than in centralized MIMO configurations. Up to the present, various training sequence designs, along with synchronization algorithms, have been proposed. Among these data-aided approaches, a timing synchronization scheme utilizing unequal period synchronization patterns (UPSPs) was proposed. In this paper, from a non-data-aided perspective, we propose a generalized interleaved carrier assignment scheme that makes the resultant random OFDM data symbols themselves become UPSP-like, and develop a blind timing synchronization scheme accordingly. Simulation results show that the proposed non-data-aided approach with majority vote refinement (MVR) can achieve better performance than the original UPSP-based approach.

In this paper, we propose a novel preamble design of Gaussian pulses, along with a synchronization scheme, for cooperative MIMO OFDM systems. In our preamble design, the training signals of cooperating nodes are well separated from each other in both time domain and frequency domain to suppress their mutual interference in both domains, whereas they are only separated in either of the two domains in the state of the art. Accordingly, multiple propagation delays and carrier frequency offsets (CFOs) can be jointly estimated using the proposed synchronization scheme, while they are separately estimated in time domain and frequency domain in conventional synchronization schemes. We also design a proper correlation window size for the proposed synchronization scheme to effectively reduce computational complexity as well as to maintain satisfactory performance. Computer simulations verify the superiority of the proposed approach over existing synchronization schemes.

Spectrum sensing is one of the major elements of cognitive radio (CR) systems. The periodic spectrum sensing frame structure can provide reliable sensing agility by introducing sensing quiet periods among signal frames to protect the primary users (PUs) from interference. However, arranging too many intra-frame sensing quiet periods on CR signaling may degrade the quality of service (QoS) of the CR network. To solve this problem, active sensing, performing spectrum sensing and transmitting data simultaneously, has been proposed to replace the intra-frame sensing. One drawback of active sensing is that the sensing performance becomes limited due to the interference from CR network transmissions. In this paper, a new CR signal structure for active sensing based on the cyclostationary properties is proposed, with which the active sensing performance can be further improved while maintaining the QoS of the CR system. Simulation results show that the proposed method significantly improves the detection performance of active sensing, especially when the signal strength from PUs is sufficiently low.

Although power allocation considerably affects the symbol error rate (SER) performance of a two-path successive relay system (TPSRS), it is not yet studied in a full interference cancellation (FIC) scenario. In this paper, we develop a suboptimal power allocation scheme for the TPSRS-FIC through minimizing an SER-based cost function. To obtain a closed-form power allocation solution, the cost function is defined as a part of the Taylor series expansion of the theoretical SER. Simulation results show that the proposed scheme can provide almost the lowest SER under limited power resources.

Cooperative geographic routing has emerged as an efficient, scalable routing paradigm that exploits the joint merit of cooperative diversity and position-aided localized operation to enhance the network performance. In terms of the hop efficiency, an existing scheme called Relay-Aware Cooperative Routing (RACR) has offered a cross-layer approach based on its quantitative study of how physical-layer cooperation leads to link-layer radio coverage extension, under the policy of equal power allocation (EPA) over the cooperating nodes. However, the effect of cooperation-based radio coverage extension dramatically varies with the power allocation policy in use. In this paper, we extend the RACR scheme by addressing a power-optimized cooperative geographic routing problem. With the joint optimization of relaying position and power allocation, the maximum cooperative transmission range is derived. We then, according to the result, present a modified cross-layer routing protocol taking into account the effectuation of optimal power allocation (OPA). Simulation results show that the proposed scheme effectively improves the coverage extension performance as well as reduces the average number of hops.

In this paper, we propose a two-phase cooperative transmission strategy using decode-and-forward (DF) relaying and cooperative null-steering beamforming (CN-SB) to overcome the multi-eavesdropper problem that reduces the secrecy capacity of wireless networks. First, two groups are built from all available relays-the jamming group and the cooperating group. Second, based on the proposed cooperative transmission strategy, we develop a new relay assignment and power allocation scheme to achieve a higher secrecy rate. Simulation results show that the secrecy rate of the proposed scheme linearly proportional to the signal-to-noise ratio (SNR), which is significantly larger than that of the scheme in which all relays perform CN-SB simultaneously in high SNR regions.

In time-varying flat-fading environments, time domain channel correlations are required for accurate channel estimation and interpolation. However, the correlation property, which depends on the Doppler spread, is hard to be extracted from corrupted channel responses within a short channel estimation interval. In this work, based on an approximate channel model via the Taylor expansion, we propose a joint channel and Doppler spread estimation scheme over time-varying flat-fading channels. It employs the expectation-maximization (EM) algorithm to iteratively attain the maximum-likelihood (ML) channel and Doppler spread estimates. Simulation results show that the proposed scheme achieves accurate performance of both channel estimation and Doppler spread estimation within a short estimation interval.

Spectrum sensing is an important issue in cognitive radio (CR) networks. In a periodic sensing frame structure, the spectrum sensing performance and the protection to the primary network improves while the sensing time increases. However, the longer the sensing time, the lower the throughput the CR network can achieve. In this paper, we formulate an optimization problem to balance the sensing-throughput tradeoff for a CR network with wideband spectrum sensing, where the combined aggregate throughput for all the two possible scenarios (instead of only one scenario used in previous related works) of the CR network is maximized under a given interference imposed on the primary network. To reduce the computational complexity, we further present a two-stage iterative algorithm to solve the optimization problem. Simulation results show that the achievable aggregate throughput of the proposed approach is much higher than those of the previous related works.

In this paper, we propose a novel preamble design of partial Zadoff-Chu sequences, along with a synchronization scheme, for cooperative MIMO OFDM systems. In our preamble design, the training signals of cooperating terminals are well separated from each other in both time domain and frequency domain to suppress their mutual interference in both domains, whereas they are only separated in either of the two domains in existing preamble designs. The time-domain separation feature enables joint estimation of multiple propagation delays and carrier frequency offsets (CFOs) without extra bandpass filters for training signal separation; the frequency-domain separation feature, on the other hand, is beneficial to integral CFO acquisition and channel estimation. To effectively reduce computational complexity as well as to maintain satisfactory performance, we design a proper correlation window size for the proposed synchronization scheme. Simulation results verify the superiority of the proposed approach over existing synchronization schemes for cooperative MIMO OFDM systems.

Partial transmit sequences (PTS) is an efficient technique to reduce the peak-to-average power ratio (PAPR) for orthogonal frequency division multiplexing (OFDM) systems. One main drawback of the conventional PTS method is the need of side information. When the side information is lost, the received data cannot be decoded correctly by the receiver. In this paper, we propose a new side-information free PTS scheme, where a difference vector along with an input data block is generated by using an extended constellation. After dividing the difference vector into some disjoint subblocks, the inverse fast Fourier transform of the input data block and that of each subblock of the difference vector are combined optimally to form a low-PAPR OFDM signal for transmission. Simulation results show that the proposed PTS scheme can achieve better PAPR reduction performance than the conventional PTS scheme, but it has lower computational complexity and does not need side information.

Cooperative communication for wireless networks has been extensively investigated from the perspective of physical-layer design. However, the impact of physical-layer cooperation on the network-layer routing design still remains unclear. In this paper, we examine the potential benefit of radio coverage extension from cooperation, and present how to incorporate this feature into the routing design. Specifically, with a series of mathematical formulations and derivations, we quantitatively identify direct and cooperative radio coverages based on the average symbol error rate (SER) performance requirement, elucidating how cooperative diversity gain can be translated into radio coverage extension. We then propose a cooperative geographic routing protocol with cross-layer design, namely the Relay-Aware Cooperative Routing (RACR) protocol, that exploits the merit of radio coverage extension for improving the non-cooperative geographic routing. Simulation results show that the RACR protocol performs significantly better than the non-cooperative geographic routing in terms of the average path length in dense ad hoc networks.

The time domain maximum likelihood (ML) Doppler spread estimation for OFDM systems provides an accurate estimation performance; however, it results in a much higher computation cost. We propose a low-complexity ML Doppler estimator based on a well-designed preamble sequence along with a suboptimal ML (SML) method to reduce the computational complexity of the optimal ML scheme. Because of the proposed preamble sequence, the received samples are able to be partitioned into uncorrelated subsets, yielding a substantial complexity reduction for the SML scheme. The simulation results show that the proposed estimator provides accurate and efficient Doppler spread estimation.

Spectrum sensing is one of the major elements of cognitive radio applications. A single secondary user (SU) usually cannot provide robust sensing capability due to channel effects. In order to overcome this problem, cooperative spectrum sensing techniques have been proposed. Because conventional cooperative spectrum sensing schemes assumed that all sensing nodes have the same sensing reliability, the SUs were assigned identical false-alarm probability even though some of them suffer deep fading, which may degrade their detection performance. In this study, we propose an adaptive credibility-based cooperative spectrum sensing technique, which evaluates the sensing reliability of SUs based on previous sensing performance, and adjusts the probability of false alarm of each SU individually. Assigning a higher false alarm probability for a more reliable SU can result in better detection performance. To verify the effectiveness of the proposed cooperative spectrum sensing technique, both the false alarm probability and the detection probability are simulated under Rayleigh fading channels, and the results show that the proposed approach outperforms any conventional detection method in terms of detection performance.

Cooperative beamforming is an energy-efficient cooperative transmission technique that cophases multiple received signals to increase received power at the destination. With perfect synchronization, a deterministic mainlobe in the direction of the destination can be guaranteed for any distribution of nodes. However, the sidelobes appear to be probabilistic in other directions. A high-power-level sidelobe may cause an unacceptable interference at an unintended receiver, thereby decreasing network capacity. In this paper, we propose a multi-relay selection scheme to control the sidelobes in cooperative beamforming systems. An optimization problem is formulated to minimize the average power over all unintended directions with a constraint of unit power gain pointing to the destination. To solve the problem efficiently, we propose a suboptimal solution that first finds the best reference relay and then selects the remaining relays accordingly. Simulation results show that the proposed multi-relay selection algorithm has lower average power over all unintended directions than both the nearest- and farthest-relays cases, where the performance is close to that of the exhaustive search approach.

In this paper, we propose an improved adaptive receiver in order to overcome the performance degradation problem encountered by the existing conjugate transmission schemes due to a time-varying frequency offset. We apply two different phase rotations on the two receiving paths instead of employing only one common phase rotation for both paths in the previous work. The two phase rotations are chosen properly based on the derived optimization results, such that an additional phase distortion on the detected symbol could be completely removed. For practical use, the block least mean-squared algorithm is applied to adaptively update the two phase rotations with the frequency offset variation. Computer simulation results show that the proposed scheme outperforms the existing works in terms of bit error rate performance, especially when a rapid frequency offset variation is considered.

This paper proposes low-complexity joint timing synchronization and channel estimation for multiple-input multiple-output orthogonal frequency-division multiplexing systems based on maximal length sequences. Under a Rayleigh channel assumption, an optimal threshold for the proposed joint scheme is derived, and a practical suboptimal threshold that requires neither pre-simulation nor prior information on the channel statistics is then presented. Furthermore, the performance of the proposed joint scheme is analyzed with respect to threshold selection, and the theoretical results match well the simulation results. It is shown that the proposed joint scheme enjoys much less computational complexity and better performance than a combination of typical synchronization and channel estimation schemes.

In distributed multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems, signals arrive at the receiver on different timing and are characterized by distinct carrier frequency offsets (CFOs), which makes synchronization rather challenging than that associated with centralized MIMO systems. Current solutions to this problem are mainly based on special preamble designs, where different training sequences are cascaded and then separately used to assist timing synchronization and CFO estimation. Such preamble designs not only increase system overhead but also burden the receivers with independent algorithms for timing synchronization and CFO estimation. In this paper, we propose a low-overhead (compact) preamble having the same length as one OFDM symbol, along with a unified algorithm for both timing synchronization and CFO estimation. Furthermore, the CFO estimation range can be flexibly extended to cope with larger CFOs in the proposed approach. Under the same training overhead and power consumption, simulation results indicate that the proposed approach outperforms a timing synchronization scheme that based on unequal period synchronization patterns.

A number of peak-to-average power ratio (PAPR) reduction techniques have been proposed for orthogonal frequency division multiplexing (OFDM) systems; however, most of them require transmitting side information and thus reduce the bandwidth efficiency. The existing constellation extension (CE) schemes do not need to transmit side information. In this paper, we propose an improved CE scheme for PAPR reduction of OFDM signals with 16-QAM modulation. The proposed CE scheme has four extendable constellation points, the four corners in the 16-QAM constellation, and each extendable constellation point has two possible extended constellation points. The proposed CE scheme, when compared with previous related CE schemes, has fewer extendable constellation points and more corresponding extended constellation points, resulting in better BER performance with almost the same PAPR reduction. Computer simulations are given to demonstrate the effectiveness of the proposed scheme.

Contention-based geographic relay selection for cooperative networks has been proposed as a state-free distributed scheme to efficiently select the best relay within a geographic area. The a priori choices for the relaying area cause different effects on the overall network performance. In this paper, we focus on the fundamental problem of predefining the relaying area and investigate its impact on the network performance. The previous work named CoopGeo, which is a cross-layer designed protocol including the relay and next hop selections, suggested the Reuleaux triangle as the relaying area, so as to avoid the hidden node problem in relay selection. However, it also leads to a certain loss of potential relays beneficial to the cooperation. Following the framework of CoopGeo, we develop a series of mathematical expressions for the relaying area, based on the average symbol error rate (SER) performance requirement. Further, the relaying area is derived and modeled as an ellipse-shaped region. Simulation results show that the CoopGeo using the proposed relaying area improves the network performance in terms of the delivery failure rate. The relaying area formulation and derivations provide a guideline regarding the design of the relaying area.

A number of peak-to-average power ratio (PAPR) reduction techniques have been proposed for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems; however, most of them involve very high computational complexity and are not applicable to MIMO-OFDM systems with space frequency block coding (SFBC). In this paper, we propose a low-complexity PAPR reduction scheme for SFBC MIMO-OFDM systems, where the input sequence is multiplied by a set of phase rotation vectors respectively and then each resulting sequence is decomposed into several sub-sequences based on the linear property of SFBC. After computing the inverse fast Fourier transform (IFFT) to convert each frequency-domain sub-sequence into a time-domain signal, we perform equivalent SFBC encoding operations in the time domain for generating candidate signal sets, where the one with the lowest maximum PAPR is selected for transmission. With the proposed scheme, we can generate a large number of candidate signal sets by computing only a few IFFTs. As compared to previous related schemes, the proposed one achieves similar PAPR reduction performance with much lower computational complexity.

This study presents an efficient location tracking algorithm to reduce the computational complexity of the conventional Kalman filtering (KF) algorithm. In the proposed training and tracking scheme, the authors replace the decision mode of the KF algorithm with an alpha–beta (α–β) algorithm to avoid repeatedly calculating the Kalman gain. After the mode with α–β – tracking, the exact information of the state and measurement noise parameters used in the KF algorithm is not required. Using the inherent fixed-coefficient feature of α–β filtering, the location information between the prediction phase and correction phase is efficiently cycled, thus simplifying implementation of the KF approach. Under a stationary environment, numerical simulations show that the proposed training and tracking approach not only can achieve the location accuracy close to the KF scheme but has much lower computational complexity.

This paper presents a joint subcarrier and power allocation algorithm for cooperative multiuser orthogonal frequency division multiplexing (MU-OFDM) cognitive radio (CR) systems. By simplifying a three-node relay network to a two node network with the equivalent channel gain, we formulate the resource allocation problem for a cooperative MU-OFDM CR system in a similar form to that for a non-cooperative MU OFDM CR system. With this problem formulation, a rule is derived for performing subcarrier assignment operations under a given power distribution, where the sum capacity optimization is alternated between the subcarrier and power to form a joint subcarrier and power allocation algorithm. To simplify the high complexity optimal power allocation algorithm (i.e., the iterative partitioned water-filling algorithm) for the joint scheme, we further develop a simple method for updating the water level when each subcarrier is assigned. Simulation results show that, with or without cooperative transmission, using the proposed method to update the water level achieves a system capacity close to that of the joint subcarrier and power allocation algorithm with the optimal power distribution. In addition, if the relay node is at the midpoint between the source and destination, the system capacity can reach its maximum value.

This paper develops a joint fine timing synchronization and channel estimation scheme for multiple-input multiple-output (MIMO) systems based on a well-designed training sequence arrangement. The proposed approach generalizes a first channel tap selection scheme and presents a majority vote refinement (MVR) of the timing estimates for different transmit-receive links. The MVR fully exploits the features of the training sequence arrangement and the MIMO diversity to improve timing synchronization as well as channel estimation. In addition, an optimal threshold for the proposed first channel tap selection scheme is derived based on a Rayleigh channel assumption. The optimal solution clearly reveals how the threshold should react to the channel statistics, the signal-to-noise ratio, the number of active transmit-antennas, and other design parameters. Based on this, a practical suboptimal threshold that requires neither pre-simulation nor prior information on the channel statistics is then proposed. Also, the performance of the proposed approach is analyzed with respect to threshold selection and MVR, and the theoretical results agree well with the simulation results in several channel models.

Cooperative relaying has been proposed as a promising transmission technique that effectively creates spatial diversity through cooperation among spatially distributed nodes. However, to achieve efficient communications while gaining full benefits from cooperation, more interactions at higher protocol layers, particularly the MAC (Medium Access Control) and network layers, are vitally required. This is ignored in most existing articles that mainly focus on physical (PHY)-layer relaying techniques. In this paper, we propose a novel cross-layer framework involving two levels of joint design-a MAC-network cross-layer design for forwarder selection (or termed routing) and a MAC-PHY for relay selection-over symbol-wise varying channels. Based on location knowledge and contention processes, the proposed cross-layer protocol, CoopGeo, aims at providing an efficient, distributed approach to select next hops and optimal relays to form a communication path. Simulation results demonstrate that CoopGeo not only operates properly with varying densities of nodes, but performs significantly better than the existing protocol BOSS in terms of the packet error rate, transmission error probability, and saturated throughput.

In this paper, we present a simple method of selecting the partial cancellation factors (PCFs) for a two-stage, hard-decision, partial parallel interference cancellation (PPIC) detector for direct-sequence code-division multiple access (DS-CDMA) systems. Using Price's theorem, we derive a range of the optimal PCF for each PPIC stage in multipath fading environments, where the lower and upper bounds can be explicitly calculated from the processing gain and the number of active users of the DS-CDMA system considered. Computer simulation results show that, using the average of the lower and upper bounds as the PCF for each PPIC stage, the bit error rate (BER) performance closely approximates that of the real optimal PCFs. Moreover, a multistage PPIC detector using the proposed PCFs in the first two stages achieves its BER performance limit with fewer stages. That is, the proposed PCF selection method reduces the complexity of a PPIC detector and provides the same BER performance. This makes the proposed PCFs attractive for use in PPIC receivers in DS-CDMA systems.

In cooperative relay systems, relayed signals propagate through different channels and are received at the destination node with distinct timing and carrier frequency offsets (CFOs). This feature makes synchronization a rather challenging task as compared with centralized multiple-input multiple-output systems. Unlike conventional preamble designs with good correlation properties only in time domain or frequency domain, a new preamble that has good correlation properties in both time domain and frequency domain is proposed for synchronization in orthogonal frequency-division multiplexing (OFDM) based cooperative relay systems. According to the proposed preamble, a synchronization scheme is developed and a practical threshold is derived that jointly considers the statistic distribution of the correlation function output and the inevitable interference originated from residual CFOs to assist fine timing synchronization. Simulation results verify that the proposed scheme provides notable performance improvement as compared with a previous related work.

This paper presents a joint subcarrier and power allocation algorithm for multiuser orthogonal frequency division multiplexing (MU-OFDM) cognitive radio (CR) systems, where the peak power constraint is used to protect the primary user. We first derive a rule for subcarrier allocation to maximize the sum capacity for a given power distribution. With this rule, we form a joint subcarrier and power allocation algorithm in which the sum capacity optimization can be alternated between the subcarrier and power. To simplify the high-complexity optimal power allocation algorithm (i.e., the iterative partitioned water-filling algorithm) for the joint scheme, we develop a simple method for updating the water level when each subcarrier is allocated to a secondary user. Simulation results show that using the proposed low-complexity method to update the water level achieves a system capacity close to that of the joint subcarrier and power allocation algorithm with optimal power distribution.

Most of geographic routing approaches in wireless ad hoc and sensor networks do not take into consideration the medium access control (MAC) and physical layers when designing a routing protocol. In this paper, we focus on a cross-layer framework design that exploits the synergies between network, MAC, and physical layers. In the proposed CoopGeo, we use a beaconless forwarding scheme where the next hop is selected through a contention process based on the geographic position of nodes. We optimize this Network-MAC layer interaction using a cooperative relaying technique with a relay selection scheme also based on geographic information in order to improve the system performance in terms of reliability.

This paper presents an efficient power allocation algorithm based on primary user (PU) activity for orthogonal frequency division multiplexing cognitive radio systems. Because of PU activity, the power allocation optimization problem becomes maximizing the sum expected capacity (i.e., the sum capacity minus the expected capacity loss), rather than maximizing the sum capacity in the traditional power allocation optimization problem. To solve this problem efficiently, we first transform the expected capacity loss into the peak power constraint and then reformulate the problem as maximizing the sum capacity under the peak power constraint. With this problem reformulation, the optimal power distribution can be reached by iteratively performing the water-filling (WF) algorithm. Instead of using the WF algorithm, we also propose a simple method to update the water level. Simulation results show that the proposed approach achieves a sum expected capacity close to that of the optimal solution, regardless of the change in the probability that the PU will reoccupy the subcarriers.

This paper presents an improved version of the opportunistic multipath (OM) proposed by Ribeiro et al. for cooperative communications. First, we generalize the OM scheme by using two groups of relays instead of using two relays for a source, so that inter-relay diversity can be achieved during the transmission between the two groups. Then, we propose a signal retransmission scheme for the relays based on the generalized OM (GOM) approach, where a relay in one group that fails to decode a symbol received from the source at the nth time slot can re-decode the symbol received from relays in the other group at the (n+2)th time slot and retransmit the correctly decoded symbol to the destination at the (n+3)th time slot. The proposed retransmission strategy retains the same data rate with only one time slot delayed to recover all the symbols, as compared with the original OM scheme. Computer simulation results show that both the proposed schemes effectively improve the system performance and that the retransmission strategy achieves better performance than the GOM scheme over poor channel links between one relay group and the destination.

Cooperative orthogonal frequency division multiplexing (OFDM) systems have been shown to be fertile in both spatial and frequency diversities and can provide high transmission throughputs. In this paper, we aim at developing a cooperative space-frequency block coded (SFBC) OFDM system by using Alamouti's coding scheme. With the selective decode-and-forward relaying strategy, we first derive the equivalent channel power gain in a cooperative SFBC-OFDM system based on the channel state information and the predefined transmission rate on each subcarrier. Then, we employ subcarrier permutation to find the optimal pairing mechanism between the broadcasting phase and the forwarding phase such that the total transmission power is minimized. Simulation results show that the proposed cooperative SFBC-OFDM system using subcarrier permutation can provide obvious performance improvement over existing cooperative OFDM systems without SFBC.

In this paper, we propose a reduced-complexity decentralized positioning (RCDP) algorithm for target positioning and tracking in wireless sensor networks. The proposed approach formulates the receiver signal strength (RSS) estimation error as a nonlinear least squares (NLS) problem using the RSS information of the local sensor nodes, and then applies the RCDP algorithm iteratively to estimate the target location. In the localization process, a participating sensor node updates the target's estimated location and then passes the updated estimate on to the next participating sensor node, which calculates a new estimated target location. We also perform a convergence analysis of the RCDP-based method based on the mathematical proofs to guarantee that the proposed iterative localization process converges. Computer simulation results show that our proposed method has a higher estimation accuracy and a better tracking efficiency than previous related methods in both stationary and moving target scenarios.

This paper aims to investigate an efficient power allocation algorithm for multiuser orthogonal frequency division multiplexing (MU-OFDM) cognitive radio (CR) systems that uses the peak power constraint to protect the primary users. Under this constraint, the high-complexity optimal power allocation algorithm for OFDM-based CR systems is not suited to determine the power distribution because the algorithm must iteratively perform the standard water-filling (WF) to determine whether or not the power in each assigned subcarrier is greater than the peak power. Instead of using the WF algorithm, we use the conditions that the optimal power distribution should be satisfied to design a simple method for fulfilling the peak power constraint in each assigned subcarrier and then updating the water level. Simulation results indicate that using the proposed efficient method to update the water level achieves a system capacity close to that of the optimal power allocation algorithm.

In this paper, we first investigate two efficient inter-carrier interference (ICI) self-cancellation schemes for orthogonal frequency division multiplexing (OFDM) systems, conjugate cancellation (CC) and phase-rotated conjugate cancellation (PRCC), by examining their system structures and performances. Then, we propose an adaptive receiver design based on conjugate transmission for ICI self-cancellation in OFDM systems. Compared to PRCC, the proposed receiver not only saves the signaling overhead by omitting the need to feed the frequency offset estimate back to the transmitter, but also has the frequency tracking capability by adopting the normalized block least mean-squared algorithm in the update process for the artificial phase rotation factor. Computer simulations show that the proposed scheme can provide better bit-error-rate performance over both CC and PRCC. Besides, even if the frequency offset estimation error is considered, the proposed scheme is shown to be more robust than the other methods.

In terms of the location-aware applications for wireless sensor networks, it is crucial to improve the measurement reliability of the received physical signal as well as the target positioning and tracking performance in a real environment. In the localization process, reflection, scattering, and other physical phenomena have a negative impact on the measurement reliability and the estimation accuracy at local sensor nodes. In this paper, we describe using a particle filter to increase the received signal strength (RSS) measurement reliability of each local sensor node and then use the least mean squares (LMS) algorithm to estimate the path loss exponent of the distance-dependent path loss model in our laboratory environment. Using the Industrial Technology Research Institute (ITRI) sensor platform, the experimental results show that the proposed LMS-based method can reduce the average noise variance by approximately 1 dB. Then the filtered RSS samples and the estimated path loss exponent are applied in the proposed weighted sign algorithm (WSA), which are implemented in the ITRI sensor platform for target positioning and tracking in our laboratory surroundings. The location estimation of a target is formulated as a weighted least squares (WLS) problem, and then is solved based on the WSA in an iterative and decentralized manner. Experimental results demonstrate that the proposed WSA-based positioning and tracking scheme achieves a maximum error distance of approximately 1.7 meters, average error distances of approximately 0.96 meters (positioning case) and 1.38 meters (tracking case), which are not far from those obtained from computer simulations (0.67 meters and 0.91 meters, respectively).

In this paper, we propose a general phase rotated conjugate cancellation (PRCC) scheme for intercarrier interference (ICI) cancellation in orthogonal frequency division multiplexing (OFDM) systems. We also derive the optimal phase rotation for this general scheme such that the carrier-to-interference ratio would be maximized. It is shown that the previous conjugate cancellation (CC) scheme is equivalent to a special case of our proposed scheme. The general PRCC scheme not only inherits advantages of the conventional CC scheme, such as backward compatibility with the existing OFDM systems, low receiver complexity, and two-path diversity, but also provides better performance, especially at high frequency offset situations.

In this paper, a reduced-complexity partial transmit sequences (PTS) scheme is proposed to resolve the intrinsic high peak-to-average power ratio (PAPR) problem of orthogonal frequency division multiplexing (OFDM) systems. In the proposed PTS scheme, a cost function Qnis generated by summing the power of the time-domain samples at time n in each subblock. Only those samples with Qngreater than or equal to a preset threshold are used for peak power calculation during the process of selecting a candidate signal with the lowest PAPR for transmission. As compared to the conventional PTS scheme, the proposed one achieves almost the same PAPR reduction performance with much lower computational complexity.

Based on the requirements of low energy consumption and high bandwidth efficiency, a primary area of study is how to improve the estimation accuracy and tracking performance for target localization in wireless sensor networks. In this paper, we propose a weighted sign algorithm (WSA) for positioning and tracking in wireless sensor networks. In terms of the reliability of distance estimation, the location estimation of a target is formulated as a weighted least squares (WLS) problem, which is solved based on the WSA in an iterative and decentralized manner. We also propose a cooperative message-passing algorithm for inter-sensor information exchange, adaptively picking the participating sensor nodes, and making the paths for cyclic routing in the network. On each routing path, a target's location estimate is updated on each cycle and continues among the participating sensor nodes that surround the target. To ensure that the WSA-based scheme has a convergence behavior, a convergence analysis is given. Computer simulation results demonstrate that, as compared with previous methods, our proposed scheme has a faster convergence rate, better location accuracy, and improved tracking performance.

This paper presents a cooperative single-input multiple-output (SIMO) transmission scheme for wireless sensor networks (WSNs), where the number of antennas and the constellation size of modulation are jointly optimized for different transmission distances such that the energy consumption is minimized. As compared to previous cooperative MIMO schemes for WSNs, the proposed one achieves higher energy efficiency and has a smaller critical distance above which cooperative MIMO/SIMO outperforms single-input single-output (SISO). The proposed optimization method is further extended to a clustered multi-hop WSN scenario. Through joint optimization of the number of transmitter antennas, the number of receiver antennas, the constellation size, and the hop length, we derive an energy-efficient clustered cooperative SIMO multi-hop scheme. Numerical results show that the proposed scheme not only reduces the overall energy consumption but also balances the energy consumption among clusters.

Sensing of orthogonal frequency division multiplexing (OFDM) signals at low signal-to-noise ratio (SNR) is of great importance for cognitive radio (CR) communications due to the wide applications of OFDM in many existing and evolving broadband wireless communications. In-band pilots, multiplexed with the data-carrying subcarriers, provides one distinct feature of OFDM signals. The objective of this paper is to investigate the application of in-band pilots in OFDM signal spectrum sensing, particularly when synchronization is not achievable at very low SNR. In this paper, the proposed sensing technique is to match the received OFDM signals with a self-defined pilot tone filter. Due to the extremely low requirement on sensing SNR for CR applications, synchronization of the sensing receiver and OFDM signals usually is not achievable. As a result, carrier frequency offset (CFO) and timing offset have to be dealt with during the sensing process. With the hybrid domain signal processing, the proposed sensing technique is very robust to both timing and frequency offset. We also apply the proposed technique to DVB-T to verify our proposal and subsequent analysis. Robust performance with very low false alarm probability and short sensing time were achieved under various channel conditions including Rician and Rayleigh channels, in the presence of random timing offset and CFO.

An adaptive Orthogonal Frequency Division Multiplexing (OFDM) system, with a preceded cyclic prefix (PCP), was proposed earlier to address the recent need of robust and flexible transmission technique in cognitive radio (CR) communications [1]. Identification of PCP-OFDM signals is therefore of great importance for the design of fair spectrum sharing mechanism, particularly at very low signal-to-noise ratio (SNR)when synchronization is not achievable. The preceded cyclic prefix, multiplexed with the data-carrying OFDM signals, provides one unique and recognizable feature of PCP-OFDM signals. In this paper, a robust PCP-OFDM signal identification technique is proposed under very low SNR in the presence of unknown timing and carrier frequency offset (CFO). Robust performance with very low false alarm probability and short sensing time was achieved under various channel conditions including Rician, Rayleigh and the additive white Gaussian noise (AWGN) channels.

In this paper, we propose a novel relay selection scheme based on geographical information, aiming to minimize the symbol error probability (SEP) for wireless ad hoc relay networks. The proposed scheme utilizes only the source-relay and relay-destination distances as selection criteria to choose the best relay. In particular, such geographical information is often available during network initialization. Thus, the proposed scheme does not need extra procedures to examine which relay has the best channel quality and, hence, reduces significantly the computational complexity. By contrast, most existing relay selection schemes rely on strict channel state information (CSI) and coherent time intervals, drastically increasing the difficulty in practical realizations, especially for large relay networks in which the fading channels are sufficiently fast-varying. In our scheme, the accuracy of the distance information is the main factor resulting in non-best relay selection. An ideal scheme (in which the distances between nodes are exact) and a practical scheme (in which there exists distance estimation errors) will be discussed respectively. Simulation results demonstrate the proposed relay selection method can efficiently improve the SEP performance and outperform the random relay selection scheme.

Modulation constellation extension (CE) schemes provide good peak-to-average power ratio (PAPR) reduction performance for orthogonal frequency division multiplexing (OFDM) signals. However, they usually require a complicated algorithm to find the optimal signal for transmission. In this paper, we propose a low-complexity CE scheme to reduce the PAPR of OFDM signals, in which some low-complexity conversion matrices are used to generate multiple candidate signals for selection. Also, we develop a mechanism to limit the increase in the average transmitted power that results from the constellation extension to an acceptable level. As compared to the related work using the CE technique, the proposed CE scheme can achieve close PAPR reduction performance with much lower computational complexity and lower transmitted power.

The geometric sequence has been shown feasible for large carrier frequency offset (CFO) acquisition, while the modulatable orthogonal sequence (MOS) has been used to assist joint time synchronization and channel estimation in orthogonal frequency-division multiplexing (OFDM) systems. This paper first proposes a method to make an MOS partially geometric. Consequently, the partially geometric MOS can be utilized to accomplish large CFO acquisition, time synchronization, and channel estimation concurrently. Based on the partially geometric MOS, we propose a large CFO acquisition technique, which is able to cooperate with a conventional joint time synchronization and channel estimation scheme. Finally, computer simulations demonstrate the performance of the proposed technique.

This paper presents a low-complexity incremental (LCI) algorithm for target positioning and tracking in wireless sensor networks. The proposed positioning scheme calculates the estimated location of a target as a nonlinear least squares (NLS) problem based on the distance estimation and solves the optimization problem in an iterative manner using the LCI algorithm. In the decentralized scheme, a participating sensor estimates a target's current location, and then passes that information on to the next participating sensor, which calculates the target's newest location estimate. In addition, a convergence analysis is given to show the convergence behavior of the LCI-based method. Computer simulation results demonstrate that the proposed algorithm has higher estimation accuracy than previous related algorithms in both stationary and moving target scenarios.

In this paper, we propose a novel and efficient relay selection protocol based on geographical information for cluster-based cooperative wireless sensor networks (WSNs). Multihop transmission is realized by concatenation of single cluster-to-cluster hops, where each cluster-to-cluster scheme forms the simplified cooperative network that consists of a single source- destination pair and a set of available relays. With the relay selection mechanism, the source in each cluster-to-cluster hop selects an optimum relay to execute the cooperative diversity transmission via the simple adaptive decode-and-forward (DF) strategy. The proposed relay selection protocol is designed for minimum symbol error probability (SEP) at the destination by utilizing only geographical information among nodes as selection criteria. In particular, such geographical information is often available during network initialization, and its state required to be maintained is minimum. Therefore, the proposed protocol can efficiently perform relay selection without complicated procedures that examine out the optimum relay by channel estimations, and hence it reduces significantly the computational complexity and is applicable to a fast-varying environment. Simulation results demonstrate the proposed relay selection protocol can efficiently improve the system performance and outperform the random relay selection protocol in terms of symbol error probability.

There have been a set of conversion matrices proposed recently by Wang and Ouyang to simplify the inverse fast Fourier transform (IFFT) computation involved in the selected mapping (SLM) scheme for reduction of the peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. As compared to the conventional SLM scheme, the modified approach achieves close PAPR reduction with much lower complexity but degraded bit error rate (BER) performance. In this paper, we propose a new set of conversion matrices for the SLM scheme such that the complexity can be reduced without sacrificing the BER performance. It is shown that the improved SLM method has better BER performance and lower complexity than the previous work by Wang and Ouyang, at the cost of a slight PAPR reduction loss.

In this paper, we present an improved version of partial parallel interference cancellation (PPIC), called variancereduced PPIC (VRPPIC), for multicarrier code division multiple access uplink systems. The VRPPIC detector is a combination of the PPIC receiver and a new bit estimator, where a simplified realization is derived for the main PPIC operations and soft decisions from PPIC are linearly combined by the bit estimator using appropriate weighting factors (derived from the PPIC weighting factors) to reduce the conditional variance of the final signal estimate. Also, we derive an optimal weighting factor (OWF) selection algorithm for VRPPIC based on minimizing a monotonically increasing conditional variance function. The derived OWFs for all the interference cancellation stages are equal and can easily be obtained from a linear function of the number of active users. Simulation results show that VRPPIC with the proposed OWFs significantly outperforms VRPPIC (or PPIC) with randomly selected weighting factors in multipath Rayleigh fading channels.

This paper addresses training-sequence-based joint fine time adjustment and channel estimation for orthogonal frequency-division multiplexing systems. The proposed approach first derives an optimized threshold that adapts to the channel statistic and the signal-to-noise ratio. Then a practical suboptimal threshold is presented to avoid the estimation of the channel statistic. The suboptimal threshold requires no pre-simulations and performs as well as the optimal one. For performance analysis, the probability of perfect fine time adjustment given a particular threshold is also derived. The theoretical results agree well with the simulation results in both Rayleigh and Ricean channels.

The selected mapping (SLM) is a major scheme for peak-to-average power ratio (PAPR) reduction in orthogonal frequency division multiplexing (OFDM) systems. It has been shown that the complexity of the traditional SLM scheme can be substantially reduced by adopting the conversion vectors to replace the inverse fast Fourier transform (IFFT) operations. Each conversion vector is obtained by taking the IFFT of the phase rotation vector. Unfortunately, the corresponding phase rotation vectors of the conversion vectors in do not have equal magnitude, leading to significant degradation in bit error rate (BER) performance. This drawback can be remedied by adopting the perfect sequences as the conversion vectors. This paper presents two novel classes of perfect sequences, which are shown to be compositions of certain base vectors and their cyclic-shift versions. Then, two novel low-complexity SLM schemes are proposed by utilizing the special structures of the perfect sequences. The BER performances of both the proposed schemes are exactly the same as the traditional SLM scheme.

This paper presents a weighted extended Kalman filter (WEKF) for target tracking in wireless sensor networks, where the location estimation is formulated as a weighted least squares (WLS) problem by taking weights of the local estimates based on the reliability of distance estimation and the WLS problem is solved in an iterative, decentralized manner based on the WEKF. We adopt a message passing (MP) algorithm for inter-sensor- node communication and for adaptively selecting the participating sensor nodes as the target moves around the area. During each iteration, a participating sensor node computes a target's location estimate and passes it on to the next participating sensor node for processing to generate a new location estimate. The update process is circulated among the participating sensor nodes in the close vicinity of the target. To show the convergence behavior of the WEKF-based method, a convergence analysis is given. Computer simulation results demonstrate that the proposed scheme has better location accuracy and tracking performance than previous related methods.

In this paper, we propose a modified incremental subgradient (MIG) algorithm with a variable step size for positioning and tracking a target in wireless sensor networks. The proposed positioning scheme formulates location estimation as a nonlinear least-squares problem using the received signal strength, and then applies the MIG algorithm with a fixed step size to solve the problem. This scheme can be realized in an iterative, decentralized manner to improve both bandwidth and energy efficiencies. To track a moving target, we further present a step-size adjustment mechanism based on the velocity of the target. In addition, a convergence analysis is given for the MIG-based positioning process. As compared with related positioning and tracking methods, the proposed scheme has better location accuracy and tracking performance.

Multiuser orthogonal frequency division multiplexing (MU-OFDM) is a promising technique for future wide-area mobile communications, which can provide scalable high data rate transmission. In this paper, we propose a low-complexity iterative power allocation algorithm with proportional rate constraints. After appropriate subcarrier allocation with equal power distribution, the proposed algorithm can achieve proportional rates among users in a few iterations by determining each user's power subject to the rate constraints and then equally distributing it to the corresponding subcarriers. Simulation results show that, for the equal rate case, the proposed approach achieves more than 98% of the minimum user's capacity provided by a near-optimal power allocation algorithm when the number of subcarriers is 128. When the number of subcarriers increases to 1024, the proposed method approaches the optimal performance.

In this paper, we propose a weighted incremental subgradient (WIG) algorithm for positioning and tracking in wireless sensor networks. We formulate the location estimation of a target as a weighted least squares (WLS) problem by taking weights of the local estimates based on the reliability information of distance estimation, and then solve the WLS problem in an iterative, decentralized manner using the WIG algorithm, where a message-passing algorithm is used for inter-sensor communication and for adaptively selecting the participating sensors as the target moves around the area. During each iteration, a participating sensor estimates a current target's location, which is passed to the next participating sensor for making new estimation. The update process continues among the participating sensors in the close vicinity of the target. In addition, a convergence analysis of the WIG algorithm is given to show that the proposed iterative positioning process converges. Computer simulation results demonstrate that, as compared with previous methods, our proposed scheme has a faster convergence rate and higher estimation accuracy in both stationary and moving target scenarios.

This paper proposes a new joint time synchronization and channel estimation scheme based on a conventional training sequence. The training sequence is composed of a maximal length sequence attached by both cyclic prefix and postfix. By analyzing the probability density functions of the corresponding correlator outputs at different time indexes, an optimal threshold is derived to distinguish the correct time index from its preceding ones. Based on the optimal threshold, the correct time index in conjunction with the channel impulse response can be estimated jointly. The proposed joint scheme involves low complexity and shows superiority over a lately-proposed one.

In this paper, we propose a general phase rotated conjugate cancellation (PRCC) scheme for intercarrier interference (ICI) cancellation in orthogonal frequency division multiplexing (OFDM) systems. It is shown that the previous conjugate cancellation (CQ scheme is equivalent to a special case of our proposed scheme. The general PRCC scheme contains advantages of the conventional CC scheme, such as backward compatibility with the existing OFDM systems, low receiver complexity, and two-path diversity, but provides better performance, especially at high frequency offset situations.

A decentralized sensor positioning algorithm is proposed using an adaptive weighted-interpolation method. The proposed method utilizes in-network processing among sensors to compute the location of the target, which is in contrast to most existing algorithms that rely on the joint processing of raw measurements from all sensors at a central server. Specifically, the target location is computed by taking the weighted average of the local estimates based on the sensors' reliability. The average is attained iteratively with each iteration being performed by a different sensor in the network. During each iteration, a sensor computes a new estimate of the target's location based on its own observation and the most recent update passed over by the sensor responsible for the previous iteration. The newest location estimate and the update process is circulated among the sensors in the close-vicinity of the target, similar to that of a token- ring topology. A message-passing protocol is proposed for the inter-sensor communication and is used to adaptively select the participating sensors as the target moves around the area. Energy and bandwidth efficiency is achieved since the system need not expend large amounts of resources in transmitting the raw data to the central server. Simulation results demonstrate the fast convergence of the iterative method and the effectiveness of the proposed positioning scheme compared to other methods.

In this paper, we present a positioning and tracking scheme based on adaptive weighted interpolation and Kalman filtering for wireless sensor networks. The proposed positioning method formulates location estimation as a weighted least squares problem by taking weights based on the reliability of distance estimation. This method can be realized in an iterative, decentralized manner to improve both bandwidth and energy efficiencies. To improve the location accuracy, a Kalman filter is employed at the central server to track variations of the location estimate computed from the proposed positioning method. As compared with a previous positioning approach based on the projection onto convex sets, the proposed scheme has faster convergence speed and better location accuracy. Computer simulation results show that more than 90 percent of the location estimates computed from the proposed approach have error distances less than 2.5 meters.

To approximate the exact peaks of continuous-time orthogonal frequency division multiplexing (OFDM) signals, four times oversampling is usually employed for discrete-time OFDM signals in various peak-to-average power ratio (PAPR) reduction schemes. Such an oversampling process would significantly increase the computational complexity, especially for a selected mapping scheme where a number of IFFT blocks may be used. In this paper, we present a low-complexity PAPR estimation scheme with two times oversampling based on "peak-search-and-partial-interpolation" (PSPI). As compared to the PAPR estimation method with four times oversampling, the proposed one achieves similar performance with only about half computational complexity. It is also shown that, with no significant increase in the computational complexity, the proposed PSPI scheme with two times oversampling has better PAPR estimation performance than the previous PSPI work without oversampling.

A novel structure of training symbol is proposed for orthogonal frequency division multiplexing (OFDM) systems. With the proposed training symbol, which has repeated sample blocks and a sign pattern on each block, both timing offset and frequency offset estimations can be obtained. In particular, the frequency synchronization is accomplished using two successive stages to obtain both the fractional and integral parts of frequency offset with an estimation range of plusmnN/4 sub-carrier spacing. Simulation experiments demonstrate that the performance of the proposed scheme is, in most of the investigated cases, substantially superior to the traditional schemes, or has negligible differences. In addition, the proposed synchronization mechanism has a relatively low system complexity, making a good comprise between performance and complexity.

One major drawback of orthogonal frequency division multiplexing schemes is the high peak-to-average power ratio (PAPR) of the output signal. Selected mapping (SLM) and partial transmit sequences (PTS) are two important techniques for reducing PAPR, but they need to transmit side information to indicate how the transmitter generates the signals. Guided scrambling (GS) SLM and GS-PTS techniques use augmenting bits to set the scrambler's initial condition. With different patterns of the augmenting bits, different candidate signals can be generated. GS-SLM and GS-PTS do not require the transmission of side information, but they still need a bank of inverse fast Fourier transforms (IFFT's), i.e., involving high computational complexity. In this paper, we focus on reducing the high computational complexity of the GS-SLM and GS-PTS methods. We separate the operations of the augmented data word into the operations of the augmenting bits and the operations of the source data word. Different augmenting bits are processed in advance and the results are saved into a read-only memory (ROM). The proposed methods only need one IFFT, few adders, and a ROM and thus significantly reduce the computational complexity of the original GS-SLM and GS-PTS methods. The simulation results also show that the proposed GS-SLM and GS-PTS methods have almost the same PAPR reduction performance as the original ones.

This paper presents an optimal weighting factor (OWF) selection algorithm for the variance-reduced partial parallel interference cancellation (VRPPIC) technique proposed by Wang and Wu in multicarrier code division multiple access systems. In this approach, a monotonically increasing conditional variance function of weighting factors derived from the VRPPIC operations is minimized under a system loading constraint so that the OWFs can be easily obtained. Simulation results show that the proposed algorithm can effectively enhance the system performance.

This paper presents a new scheme for positioning and tracking mobile nodes based on adaptive weighted interpolation and alpha-beta (alpha-beta) filtering in wireless sensor networks. The proposed positioning method formulates location estimation as a weighted least squares problem, which can be solved in an iterative, decentralized manner. With such estimated location information, an alpha-beta tracking algorithm is further employed at a central processor to improve the location accuracy. As compared with the Kalman filtering approach, the proposed alpha-beta tracking method achieves reasonably good performance with much lower computational complexity and no need of exact information about the state and measurement noise parameters. Computer simulation results show that more than 90 percent of the estimated locations have error distances less than 2.5 meters.

In this paper, we extend a training sequence structure, which was originally designed for orthogonal frequency division multiplexing (OFDM) systems, into multiple-input multiple-output (MIMO) scenario. Unlike conventional training sequence structures for MIMO-OFDM systems, the proposed modification eliminates the interference among training sequences transmitted by different antennas, and can be constructed from the same orthogonal sequence. Furthermore, the unique structure enables a low-complexity joint time synchronization and channel estimation scheme that requires only a correlator and a comparator. With the same training sequence length, computer simulation results show that the proposed joint scheme outperforms conventional synchronization and channel estimation methods by orders in MIMO-OFDM systems.

The high peak-to-average power ratio (PAPR) feature is one main drawback associated with orthogonal frequency division multiplexing (OFDM) systems. To overcome this problem, many approaches have been presented in the literature, such as the selected mapping technique, the partial transmit sequence technique, the linear nonsymmetrical transform (LNST), and the exponential companding transform (Exp-CT). However, most of them involve high computational complexity. In this paper, we propose a new low-complexity companding transform scheme for PAPR reduction. From computer simulations, the proposed low-complexity scheme can successfully reduce the PAPR value with a lower bit error rate than the Exp-CT scheme and smaller spectrum side-lobe generation than the LNST and Exp-CT schemes. It is useful for physical realization of an OFDM system.

Space division multiple access in conjunction with OFDM main drawback associated with orthogonal frequency division efficiency and system capacity. This combination is approaches have been presented in the literature, such as future WLAN implementations. One drawback of OFDM systems is the high peak to average power ratio, which imposes (LNST), and the exponential companding transform (Exp-CT). However, most of them involve high computational complexity. In this paper, we propose a new low-complexity companding transform scheme for PAPR reduction. From computer simulations, the proposed low-complexity scheme nonlinear distortion over the recovered symbols. The error rate than the Exp-CT scheme and smaller spectrum side-lobe generation than the LNST and Exp-CT schemes. It is useful for physical realization of an OFDM system. of the cancellation technique at channel estimation accuracy

In this paper, a novel training sequence structure along with a joint time synchronization and channel estimation scheme for orthogonal frequency division multiplexing (OFDM) systems is proposed. The proposed training sequence structure is composed of an orthogonal sequence attached by cyclic prefix and cyclic postfix. Both the lengths of the cyclic extensions attached are chosen to be longer than the maximum delay spread of the wireless channel. Based on the unique structure of the training sequence, we present a low-complexity joint time synchronization and channel estimation scheme. Unlike conventional methods, which require either discrete Fourier transform (DFT) operations or matrix inversions to acquire channel impulse response (CIR) information, the proposed scheme requires only a correlator and a comparator. At the expense of the same training sequence overheads, computer simulation results show that the proposed joint scheme outperforms conventional time synchronization methods by orders. Furthermore, the overall bit error rate (BER) performance of the proposed joint scheme is shown to be close to the ultimate bound characterized by perfect synchronization and channel estimation. The proposed joint scheme also provides significant BER performance gain as compared to a scheme that properly combines a conventional synchronization method with a DFT-based channel estimation method.

In this paper, we propose a multiple-pulse interference (MPI) cancellation scheme for ultra-wideband systems using pulse shape modulation. The proposed scheme is based on a similar concept to parallel interference cancellation for code-division multipleaccess systems, where a specific training sequence structure is used to estimate the channel information and interference for MPI cancellation. Computer simulation results are given to show that it has much better performance than the maximum ratio combining scheme in different scenarios.

This paper presents algorithms for calibrating and tracking the location of a mobile terminal based on radio propagation modeling (RPM) and Kalman filtering for indoor wireless local area networks (WLANs). In this Kalman filter-based (KF-based) tracking algorithm, the observed location information is extracted from the empirical and RPM positioning methods. Not only can the proposed RPM algorithm calibrate the change of different environmental conditions in a real dynamic environment but also the KF-based tracking algorithm can reduce the location error with smaller sampling time and vanquish the phenomenon of the aliasing in the signal space. Our experimental results show that more than 90 percent of the estimated locations have error distances less than 2.3 meters.

This paper presents an adaptive location estimator based on radio propagation modeling and Kalman filtering for indoor wireless local area networks. In this positioning scheme, the location of a mobile terminal is extracted from the constant-velocity trajectory by linear equations and the radio propagation model by nonlinear equations. Results from simulation exhibit that the positioning error can be reduced with smaller sampling time of the Kalman filter. The simulation results also show that more than 95 percent of the estimated locations have error distances less than 1.55 meters.

In this paper, we propose a new intercarrier interference (ICI) suppression scheme for orthogonal frequency division multiplexing (OFDM) systems. The proposed approach can be regarded as an improved version of the method using correlative coding, where the data samples of the tail subcarriers in an OFDM symbol are encoded with the data samples of the head ones in the same OFDM symbol, instead of being encoded with those of the subsequent OFDM symbol for the original approach. For low complexity, the modified correlative coding scheme is realized as a windowing function, where the parameters are optimized through theoretical analysis. A demodulation algorithm which does not need prior information of the transmit sequence is also developed. Computer simulation results show that the proposed scheme not only achieves better performance in ICI suppression, but also prevents error propagation through OFDM symbols. The penalty is only a slight increase in the computational complexity at the receiver.

The high peak-to-average power ratio (PAPR) of the output signal for the transmitter is one of the main drawbacks of orthogonal frequency division multiplexing (OFDM) systems. To properly approximate the exact peaks of the continuous-time OFDM signal, L (usually ges 4) times oversampling is generally used for the discrete-time OFDM signal in many PAPR reduction schemes. However, the oversampling process increases the computational complexity. In this paper, we propose a low-complexity PAPR estimation method-peak-search-and- partial-interpolation" (PSPI) scheme-to efficiently estimate the PAPR value for the discrete-time OFDM signal. Instead of doing L times oversampling, the proposed PSPI method interpolates the 2(L-1) neighboring samples of L times oversampling for each searched peak of the original discrete-time OFDM signal. The simulation results illustrate that the proposed PSPI method can achieve well-approximated results as good as those of the scheme with four times oversampling, but with much lower computational complexity.

This paper presents an indoor location scheme based on wireless local area networks, where the position of a mobile terminal is estimated according to the measured signal-to-noise ratio (SNR) information from multiple access points. With the antenna pattern-measurement method for measuring the SNRs, pretty good location estimates can be obtained. Our experimental results show that more than 85 percent of the estimated locations have error distances less than two meters.

This paper presents a new low-complexity method for realizing the main partial parallel interference cancellation (PPIC) operations proposed by Divsalar et al for multicarrier code division multiple access (MC-CDMA) systems. Based on this approach, K multiplications of the original scheme are replaced with K additions for each interference cancellation (IC) stage and two equivalent PPIC-based multiuser detectors of lower complexity are presented. Also, a new bit estimator is derived for PPIC-based multiuser detectors to reduce the variances of the final signal estimates. The bit estimator linearly combines soft information of each IC stage using weighting factors derived from those for PPIC. Computer simulation results show that a PPIC-based multiuser detector with the bit estimator has performance gain over the original one.

We propose a new symbol time estimator utilizing a specifically designed pilot symbol for orthogonal frequency division multiplexing systems. The proposed estimator consists of two stages of estimation (coarse-to-fine). In the stage of coarse estimation, the redundant information contained within the cyclic prefix is used for rough symbol time estimation. In the stage of fine estimation, the merit of the designed pilot symbol structure is utilized to generate a fine symbol time estimate. Computer simulation results show that, although the new estimator has a slightly larger variance than a recently described method by H. Minn et al. (see IEEE Commun. Lett., vol.4, p.242-4, 2000) for additive white Gaussian noise channels, it has a significantly smaller variance and a smaller bias (i.e., the mean of the estimation error) for intersymbol interference channels. The new method also involves less computational complexity than previous related approaches.

One major drawback of orthogonal frequency division multiplexing is the high peak-to-average power ratio (PAPR). The selective mapping (SLM) approach provides good performance for PAPR reduction, but it may suffer from the high computational complexity of the bank of inverse fast Fourier transforms (IFFTs). We propose two low-complexity conversions to replace half of the IFFTs in the SLM method. Computer simulation results and complexity analyses show that, with the two proposed conversions, we can reduce about half of the computational complexity of the SLM approach and get better performance for PAPR reduction.

In this paper, we present a new all-digital carrier recovery loop for high-order quadrature amplitude modulation (QAM) signal constellations. The proposed approach is a blind phase-frequency detector structure that consists of a phase detector, a phase offset estimator, a frequency offset estimator, and a digital control oscillator. As compared with previous related approaches, the proposed algorithm provides a wider acquisition range of /spl plusmn/400 kHz and a more accurate estimation of frequency and phase offsets. These features are demonstrated by simulation results of the DOCSIS (Data-Over-Cable Service Interface Specifications) cable modem system.

A low-complexity power control scheme for direct-sequence code-division multiple access systems is presented. In the proposed structure, we exploit the interference cancellation capability of the turbo partial parallel interference cancellation (TPPIC) algorithm presented by Wu and Wang (see Proc. 2001 IEEE Global Telecommun. Conf (Globecom 2001), San Antonio, TX, Nov. 2001, p.244-248). A new method for parameter estimation is also presented and is integrated with the powerful TPPIC in power control algorithm design. Computer simulation results show that this new approach significantly outperforms the previous scheme using conventional parallel interference cancellation, where both involve the same order of complexity. As compared to the more complicated power control methods using minimum mean-squared error (MMSE) filtering, the proposed approach still provides better performance but involves much less complexity.

We propose a low-complexity distributed power control scheme with adaptive interference suppression for direct-sequence code-division multiple access wireless communication systems. The proposed method can be regarded as an improved version of the adaptive power control scheme presented by Wang et al. (see Proc. 2000 IEEE Int. Symp. Circuit and System (ISCAS 2000), Sydney, Australia, May 2001, p.286-89). In the proposed structure, a new strategy is developed for estimating the required parameters for power control such that extra power consumption due to improper measuring can be alleviated. Computer simulation results support that the improved power control scheme performs much better than the original one, where both involve the same order of complexity. As compared to the complicated instantaneous minimum mean-squared error (MMSE) scheme presented by Ulukus and Yates (see ACM Wireless Networks, vol.4, p.489-96, 1998), the proposed adaptive method achieves similar convergence performance but involves much less complexity.

A low-complexity multiuser receiver for turbo-coded DS-CDMA systems is presented to perform jointly iterative multiuser detection and turbo decoding. The proposed approach consists of a new multistage partial parallel interference cancellation (NPPIC) detector and K single-user turbo decoders, where K is the number of active CDMA users. The NPPIC detector is derived based on the single-user maximum a posteriori criterion and has a similar simple structure to the conventional partial parallel interference cancellation scheme presented by Divsalar et al. (see IEEE Trans. Commun., vol.46, p.258-268, Feb. 1998). A prominent feature of this detector is that it delivers interference-cancelled soft outputs to the turbo decoders and utilizes the soft information from the turbo decoders' output. Extensive computer simulations demonstrate that the cooperation between NPPIC and turbo decoding offers significant performance gain over the traditional non-iterative receivers and performs comparably to some existing iterative schemes of much higher complexity.

This paper presents a new VLSI architecture for computing the N-point discrete Fourier transform (DFT) of real data and the corresponding inverse (IDFT) based on the discrete Hartley transform, where N is a power of two. The architecture includes two real multipliers, three real adders, six memory-based buffers, two ROMs, and some simple logic circuits, making itself suitable for single-chip implementation. It is capable of evaluating one DFT sample or one IDFT sample every (log/sub 2/N+1)//sub 2/ clock cycles on average. Under 0.35 /spl mu/m CMOS technology, the proposed design can operate at a clock rate of 100 MHz to reach a throughput of 20M transform samples per second for N=512. The processing speed will be higher if more advanced CMOS technology is adopted to implement the same circuit. Such low-complexity and high-throughput feature supports that the proposed design is well suited for use in discrete multitone based very high-speed digital subscriber line transceivers.

This paper presents a new soft-input soft-output multistage partial parallel interference cancellation (PPIC) detector for direct-sequence code-division multiple-access (DS-CDMA) systems. The proposed detector has a similar simple structure to the conventional PPIC scheme presented by Divsalar et al. (1998). A new way of reliability iterating is derived based on the single-user maximum a posteriori (MAP) criterion. At each stage, extrinsic information is extracted and then used as the a priori information for the next stage. Extensive computer simulations have shown that the proposed approach is capable of offering a good performance gain over the conventional PPIC scheme and some other well-known multiuser detectors, especially when the system load is heavy.

Optimal joint multiuser detection and decoding for direct-sequence code-division multiple-access (DS-CDMA) systems with forward error correction normally requires prohibitively high computational complexity. A suboptimal solution with low complexity is therefore appealing for use in practical applications. We propose a low-complexity iterative multiuser receiver for turbo-coded DS-CDMA systems. The proposed approach consists of a modified decorrelating decision-feedback detector (MDDFD) and K single-user turbo decoders, where K is the number of users in the DS-CDMA system. The MDDFD is derived on the basis of maximizing a likelihood probability and has a feature that it can use the reliability information from the turbo decoders' output. In addition, the MDDFD can deliver interference-cancelled soft outputs to the turbo decoders where the calculation of transition metrics is modified appropriately. Both performance analysis and computer simulation results have indicated that the reliability information from the turbo decoders' output can enhance the multiuser detection capability of the MDDFD. Computer simulations have also shown that the proposed iterative multiuser receiver outperforms the conventional DDFD-based multiuser receiver in terms of the bit-error probability.

This paper presents a real-valued discrete multicarrier modulation approach that is based on the use of the discrete Hartley transform (DHT) and its inverse (IDHT) to perform the modulation and demodulation operations. Since the DHT and IDHT definitions are identical, we can use the same hardware or program to implement the modulator and demodulator of the proposed multicarrier method. As compared to the complex-valued discrete Fourier transform based multicarrier modulation method, the proposed one achieves the same transmission performance with reduced computational complexity and implementation cost.

We propose a low-complexity iterative multiuser receiver for turbo-coded DS-CDMA systems. The proposed iterative multiuser receiver consists of a modified decorrelating decision-feedback detector (MDDFD) and K single-user turbo decoders, where K is the number of CDMA users. The MDDFD is derived on the basis of maximizing a likelihood probability and has the feature that it uses the reliability information from turbo-decoder output. In addition, the MDDFD delivers interference-cancelled soft-outputs to the turbo decoders where transition metrics calculations are appropriately modified. Both performance analysis and computer simulation results have indicated that the reliability information from turbo-decoder output can enhance the multiuser detection capability of the MDDFD. Computer simulations have shown that the proposed iterative multiuser receiver significantly outperforms the conventional DDFD-based multiuser receiver in terms of bit error probability.

For turbo-coding systems in mobile fading environments, fading amplitudes must be provided to the turbo decoder in order to exhibit the full potential of turbo codes. We investigate the performance of turbo-coding systems with adaptive channel estimation in the Rayleigh flat-fading channels. Two system models are considered for simulations. In the first model, the channel estimation is performed prior to the turbo decoder. In the second model, the decision-directed approach for refined channel estimation is considered where the fading amplitudes are re-estimated with the aid of the hard-decided turbo-decoder outputs. The least mean square (LMS) algorithm and the general optimum block adaptive (GOBA) algorithm are used for the adaptive channel estimators in the two system models. Simulation results have shown that the GOBA channel estimator with the decision-directed approach provides much better estimates of the fading amplitudes, thereby significantly improving the bit error rate (BER) performance of the turbo-coding systems.

Performance of turbo codes in fading channels can be improved when the channel fading amplitudes are available at the turbo decoders, conventionally, channel estimation and turbo-decoding are treated as two independent tasks. In this paper, we propose an iterative structure for fading amplitude estimation where turbo-decoder decisions are directed to an adaptive channel estimator using the general optimum block adaptive (GOBA) algorithm. The performance of a turbo-coding system with the proposed channel estimation structure is also investigated through computer simulations for correlated Rayleigh flat-fading channels. This decision-directed approach for channel re-estimation combined with the excellent tracking capability of the GOBA algorithm significantly improves the turbo-coding system performance. Computer simulation results show that its bit error rate performance is close to that of a system with perfect knowledge of fading amplitudes especially for fast-fading channels.

In this paper, we present a new parallel-in parallel-out systolic array with unidirectional data flow for performing the power-sum operation C+AB/sup 2/ in finite fields GF(2/sup m/). The architecture employs the standard basis representation and can provide the maximum throughput in the sense of producing new results at a rate of one per clock cycle. It is highly regular, modular, and, thus, well-suited to VLSI implementation. As compared to a previous systolic power-sum circuit with bidirectional data flow and the same throughput performance, the proposed one has smaller latency, consumes less chip area, and can more easily incorporate fault-tolerant design. Based on the new power-sum circuit, we also propose a parallel-in parallel-out systolic array with the maximum throughput for computing inverses/divisions in GF(2/sup m/). The proposed systolic divider gains advantages over an existing system with the same throughput performance in terms of chip area, latency, and fault tolerance.

This paper presents a novel VLSI architecture for computing the N-point discrete Fourier transform (DFT) based on a radix-2 fast algorithm, where N is a power of two. The architecture consists of one complex multiplier, two complex adders, and some special memory units. It can compute one transform sample every log/sub 2/N+1 clock cycles in average. For the case of N=512, the chip area required is about 5742/spl times/5222 /spl mu/m/sup 2/ and the throughput is up to 4 M transform samples per second under 0.6 /spl mu/m CMOS technology. Such area-time performance makes the proposed design rather attractive for use in long-length DFT applications, such as ADSL and OFDM systems.

This paper presents two new systolic arrays to realize Euclid's algorithm for computing inverses and divisions in finite fields GF(2/sup m/) with the standard basis representation. One of these two schemes is parallel-in parallel-out, and the other is serial-in serial-out. The former employs O(m/sup 2/) area complexity to provide the maximum throughput in the sense of producing one result every clock cycle, while the latter achieves a throughput of one result per m clock cycles using O(m log,m) area complexity. Both of the proposed architectures are highly regular and, thus, well suited to VLSI implementation. As compared to existing related systolic architectures with the same throughput performance, the proposed parallel-in parallel-out scheme reduces the hardware complexity (and, thus, the area-time product) by a factor of O(m) and the proposed serial-in serial-out scheme by a factor of O(m/log/sub 2/m).

This paper presents a new two-dimensional (2-D) optimum block stochastic gradient (TDOBSG) algorithm for 2-D adaptive finite impulse response (FIR) filtering. The TDOBSG algorithm employs a space-varying convergence factor for all the filter coefficients, where the convergence factor at each block iteration is optimized in a least squares sense that the squared norm of the a posteriori estimation error vector is minimized. It has the same order of computational complexity as another 2-D optimum block adaptive (TDOBA) algorithm. Computer simulations for image restoration show that the TDOBSG algorithm outperforms the TDOBA algorithm and other related algorithms in terms of objective and/or subjective measures.

Reed-Solomon (RS) codes have been widely used in a variety of communication systems to protect digital data against errors occurring in the transmission process. Since the decoding process for RS codes is rather computation-extensive, special-purpose hardware structures are often necessary for it to meet the real-time requirements. In this paper, an area-efficient pipelined very large scale integration (VLSI) architecture is proposed for RS decoding. The architecture is developed based on a time domain algorithm using the remainder decoding concept. A prominent feature of the proposed system is that, for a t-error-correcting RS code with block length n, it involves only 2t consecutive symbols to compute a discrepancy value in the decoding process, instead of n consecutive symbols used in the previous RS decoders based on the same algorithm without using the remainder decoding concept. The proposed RS decoder can process one data block every n clock cycles, i.e., the average decoding rate is one symbol per clock cycle. As compared to a similar pipelined RS decoder with the same decoding rate, it gains significant improvements in hardware complexity and latency.

This paper presents a new pipelined VLSI array for decoding Reed-Solomon (RS) codes. The architecture is designed based on the modified time-domain Berlekamp-Massey algorithm incorporated with the remainder decoding concept. A prominent feature of the proposed system is that, for a t-error-correcting RS code with block length n, it involves only 2t consecutive symbols to compute a discrepancy value in the decoding process, instead of n consecutive symbols used in the previous RS decoders based on the same algorithm without using the remainder decoding concept. The proposed RS decoder reaches an average decoding rate of one data symbol per clock cycle. As compared to a similar pipelined RS decoder with the same decoding rate, it gains significant improvements in hardware complexity and latency.

Recently, Eyuboglu (1988) has shown that adaptive noise-predictive decision-feedback equalization (DFE) can be combined with coded modulation to achieve high-speed data transmission by periodic interleaving. In this paper, we present a new method of adaptive DFE with periodic interleaving for coded modulation systems. The method is an improved version of that proposed by Eyuboglu, where the deinterleaving operation is performed on a vector-by-vector basis, instead of a sample-by-sample basis. Unlike the original system in which the linear equalizer's coefficients can be adjusted only with hard decisions from the threshold detector, the improved structure updates the coefficients of both the linear equalizer and the noise predictor based on soft decisions from the most likely path in the soft decoder. The improved system achieves better error-rate performance than the original with a little increase in hardware complexity. As compared to another improved design reported by Zhou et al. (1990), the new structure also gains advantages in error-rate performance, hardware complexity, and throughput delay.

This paper presents a new systolic architecture that can be used to realize the full-search vector quantization (VQ) encoder for high-speed applications. The architecture possesses the features of regularity and modularity, and is thus very suitable for VLSI implementation. For a codebook of size N and dimension k, the VQ encoder has an area complexity of O(N), a time complexity of O(k), and I/O bandwidth of O(k). It reaches a compromise between the hardware cost and speed performance as compared to existing systolic/regular VQ encoders. At the current state of VLSI technology, the proposed system can easily be realized in a single chip for most practical applications. In addition, it provides flexibility in changing the codebook contents and extending the codebook size, where the latter is achieved simply by cascading some identical basic chips. With 0.8 /spl mu/m CMOS technology to implement the proposed VQ encoder for the case of N=256, K=16, and an input data wordlength of 8 bit, the chip requires a die size of about 5.5/spl times/8.9 mm/sup 2/ and is able for processing 6.25 M data vectors (or 100 M data samples) every second. These features show that the proposed architecture is attractive for use in high-speed image/video applications.

This paper presents a new systolic VLSI architecture to realize the full-search block matching algorithm for motion estimation. The architecture has an efficiency of 100 percent and a throughput of one motion vector per n/sup 2/ cycles, where n/spl times/n is the reference block size. As compared to existing VLSI motion estimators with the same efficiency and throughput, the proposed one not only gains advantages in the flexibility of changing the reference block size and the tracking range, but also employs no additional control circuitry to determine the motion vectors. These features make it useful for a wide range of applications.

In this paper, we present a digit-serial VLSI architecture for realization of an adaptive FIR filter equipped with the delayed least mean square (LMS) algorithm. The architecture is attractive for use in applications where bit-serial arithmetic is too slow and bit-parallel arithmetic requires too much hardware or cannot reach the desired convergence performance.

This paper presents a modified general optimum block adaptive (GOBA) algorithm for block adaptive decision-feedback equalization (DFE) of multipath fading channels. As compared to the sequential fast Kalman algorithm and another previously proposed optimum block adaptive algorithm, the modified GOBA algorithm can achieve better error-rate performance for block adaptive DFE of rapid fading HF radio channels.

A new systolic array without matrix transposition hardware is proposed to compute the two-dimensional discrete cosine transform (2-D DCT) based on the row-column decomposition. This architecture uses N/sup 2/ multipliers to evaluate N/spl times/N-point DCTs at a rate of one complete transform per N clock cycles, where N is even. It possesses the features of regularity and modularity, and is thus well suited to VLSI implementation. As compared to existing pipelined regular architectures for the 2-D DCT, the proposed one has better throughput performance, smaller area-time complexity, and lower communication complexity. The new idea for the 2-D DCT is also extended to derive a similar systolic array for the 2-D inverse discrete cosine transform (IDCT). Simulation results demonstrate that the proposed 2-D DCT and IDCT architectures have good fixed-point error performance for both real image and random data. As a consequence, they are useful for applications where very high throughput rates are required.>

This paper presents a linear systolic array and a 2-D systolic array for computing the 1-D N-point and 2-D N/spl times/N-point discrete cosine transforms (DCT's), respectively. The 1-D DCT array is constructed by using the Chebyshev polynomial to generate the transform kernel values recursively. The 2-D DCT array is based on the row-column decomposition but involves no matrix transposition problems, where the row and column transforms are evaluated similarly to the 1-D DCT. These architectures are highly regular, modular, and thus very suitable for VLSI implementation. Also, each of them has an efficiency of 100% and a throughput rate of one transform per N cycles. As compared to existing related systems, the proposed 1-D DCT array achieves the same time complexity with either much fewer I/O channels or a higher degree of regularity, while the proposed 2-D DCT array possesses better time complexity and regularity with an increase in chip area and I/O channels.>

We present a new 2-D optimum block stochastic gradient (TDOBSG) algorithm for 2-D adaptive finite impulse response (FIR) filtering. Unlike the 2-D optimum block adaptive (TDOBA) algorithm derived from a truncated Taylor's series expansion, which is in fact a suboptimum one, the TDOBSG algorithm exactly minimizes the squared norm of the a posteriori estimation error vector in a given block by optimally choosing the convergence factor of the adaptive filter. The optimum convergence factor can be computed from input signals at the same order of computational complexity as that of the TDOBA algorithm. Computer simulations based on the configuration of adaptive image noise cancellation show that the TDOBSG algorithm has better convergence speed and accuracy than those of the TDOBA algorithm.>

This paper presents a new parallel-in-parallel-out bit-level systolic array with unidirectional data flow for computing exponentiation in GF(2/sup m/). The array is highly regular, modular, and thus well suited to very-large-scale-integration implementation. In addition, it can provide the maximum throughput in the sense of producing new results at a rate of one per clock cycle. As compared with a previously known systolic GF(2/sup m/) exponentiator with the same throughput performance, the proposed system requires much less chip area, has small latency, and is easier to incorporate fault-tolerant design.>

A new serial-in serial-out systolic array is presented for performing the element inversion in GF(2/sup m/) with the standard basis representation. The architecture is highly regular, modular, nearest neighbor connected, and thus well suited to VLSI implementation, It has a latency of 7m-3 clock cycles and a throughput rate of one result per 2m)-1 clock cycles. This speed performance is much better than those of the previous implementations. Without change in hardware design, the proposed inversion array can be directly used for computing the division in GF(2/sup m/).>

Bit-level systolic architectures based on an inner-product computation scheme for finite-impulse response (FIR) and infinite-impulse-response (IIR) digital are presented. The FIR filter structure is optimized in the sense that for a given clock rate, both the utilization efficiency and average throughput are maximized. The IIR filter structure has approximately the same utilization efficiency and throughput rate as previous related techniques for processing a single data stream (channel), but it allows two data streams to be processed concurrently to double the performance. This feature makes the IIR system attractive for use in applications where multiple filtering and particularly bandpass analysis are required.>