In-band full-duplex (IBFD) systems are expected to double the spectral efficiency compared to half-duplex systems, provided that loopback self-interference (SI) can be effectively suppressed. The inherent interference mitigation capabilities of the emerging fluid antenna system (FAS) technology make it a promising candidate for addressing the SI challenge in IBFD systems. This paper thus proposes a FAS-assisted self-interference cancellation (SIC) framework, which leverages a receiver-side FAS to dynamically select an interference-free port. Analytical results include a lower bound and an approximation of the residual SI (RSI) power, both derived for rich-scattering channels by considering the joint spatial correlation amongst the FAS ports. Simulations of RSI power and forward link rates validate the analysis, showing that the SIC performance improves with the number of FAS ports. Additionally, simulations under practical conditions, such as finite-scattering environments and wideband integrated access and backhaul (IAB) channels, reveal that the proposed approach offers superior SIC capability and significant forward rate gains over conventional IBFD SIC schemes.

The fluid antenna (FA)-enabled multiple-input multiple-output (MIMO) system based on index modulation (IM), referred to as FA-IM, significantly enhances spectral efficiency (SE) compared to the conventional FA-assisted MIMO system. To improve the performance in addressing the high spatial correlations between multiple activated ports, this paper proposes an innovative FA grouping-based IM (FAG-IM) system. Specifically, considering the characteristics of the FA two-dimensional (2D) surface structure and the spatially correlated channel model in FA-assisted MIMO systems, a block grouping method is adopted, where adjacent ports are assigned to the same group. Consequently, different groups independently perform port index selection and constellation symbol mapping, with only one port being activated within each group during each transmission interval. Then, a closed-form average bit error probability (ABEP) upper bound is derived for the proposed system. Numerical results show that, compared to state-of-the-art systems, the FAG-IM system consistently achieves substantial performance gains.

The rapid convergence of wireless infrastructure and vertical applications has brought the growing needs for integrated sensing and communications. Due to competing purposes and limited radio resources, an effectively designed integrated sensing and communication (ISAC) system has to precisely adjust its resource allocation to communication and sensing. To maximize the value of service (VoS) for ISAC operation with varying concurrent demands and resource conditions, a successive resource allocation scheme for multi-user ISAC systems is proposed. Specifically, the bandwidth and power allocation are formulated as a mixed integer optimization problem by considering the varying user requirements and resource availability. To solve this problem, a deep-reinforcement learning (DRL) based adaptive resource allocation algorithm is utilized for successive ISAC operational gain maximization. Simulation results demonstrate the adaptiveness and effectiveness of the proposed resource allocation scheme under dynamic scenarios.

Domain generalization aims to reduce the vulnerability of deep neural networks in the out-of-domain distribution scenario. With the recent and increasing data privacy concerns, federated domain generalization, where multiple domains are distributed on different local clients, has become an important research problem and brings new challenges for learning domain-invariant information from separated domains. In this paper, we address the problem of federated domain generalization from the perspective of domain hallucination. We propose a novel federated domain hallucination learning framework, with no additional data exchange between clients other than model weights, based on the idea that a domain hallucination with enlarged prediction uncertainty for the global model is more likely to transform the samples into an unseen domain. These types of desired domain hallucinations are achieved by generating samples that maximize the entropy of the global model and minimize the cross-entropy of the local model, where the latter loss is further introduced to maintain the sample semantics. By training the local models with the learned domain hallucinations, the final model is expected to be more robust to unseen domain shifts. We perform extensive experiments on three object classification benchmarks and one medical image segmentation benchmark. The proposed method outperforms state-of-the-art methods on all the benchmarks, demonstrating its effectiveness.

Wireless backhaul has recently gained a significant amount of interest as a cost-effective solution in comparison with conventional backhaul technologies with dedicated microwave links or fiber optics. Self-interference cancellation (SIC) is an enabling technology that allows wireless backhaul to operate in the more spectrum-efficient in-band full-duplex (IBFD) operation mode instead of the out-of-band mode. Compared to Wi-Fi IBFD transceivers, wireless in-band backhaul systems face some unique challenges, such as significantly higher transmission power and much larger propagation delay spread for the self-interference signal, especially in the low-frequency bands under 1 GHz, which often prevent accurate SIC performance. The SIC is often implemented with an interference-cancelling filter, where the filter weights are essentially the channel estimates of the self-interference signals. In this paper, a frequency-domain Radio Frequency (RF) SIC (RF-SIC) framework with a novel filter weight optimization algorithm is proposed to tackle the challenges of wireless in-band backhaul. The proposed RF-SIC does not require a dedicated training phase which needs to stop the transmission of the backhaul signal. Moreover, it has the capability of tracking the self-interference channel variation since the filter weights are updated in a block-by-block fashion.

Femtocells can be employed as the low-power “green” wireless-access points to extend the macrocell network coverage and enhance the quality-of-service inside homes. In this paper, we focus on the joint subchannel allocation and transmitting-power control for femtocells during the downlink transmissions. Our objective is to minimize the total transmitting power across femtocell access points (FAPs) to facilitate “green” mobile communications. We would like to minimize the following criteria: (1) each user's received signal-to-interference-plus-noise ratio (SINR) per subchannel and (2) the number of subchannels each femtocell user requires to maintain a reliable quality-ofservice (QoS). Meanwhile, the interference of the users in the underlying femtocells to users in other macrocells should also be restricted. Thus, a new pertinent optimization problem is formulated as a mixed integer nonlinear program (MINLP), which is very complicated to solve in practice. In our work, a reformulation-linearization technique (RLT) based on a branchand-bound framework is invoked to simplify the aforementioned MINLP. Finally, simulation results are demonstrated for the effectiveness of our proposed new scheme.

The transmitter identification (Tx-ID) technique has been addressed in the modern ATSC digital television standards. Kasami sequences are adopted as the Tx-ID sequences due to the favorable code capacity. However, the conventional cross-correlation based Tx-ID technique cannot combat the realistic multipath channel impairment. Therefore, in this paper, we propose a new least-square Tx-ID approach, which is demonstrated to be very robust when the multipath channels are encountered. Besides, we also establish the new Hessian analysis to derive the constraint of the injection level. Finally, we devise a fast Tx-ID scheme when the channel length is set to be equal to the Tx-ID sequence length.

Scattering signals on wind turbines may lead to degradation problems on the communication systems provided in the UHF band, such as terrestrial television broadcasting, broadband wireless systems or public safety services. To date, despite the continuous requests from the International Telecommunication Union for studies on this field, no channel model has been developed to characterize signal propagation under these particular conditions. In response to this necessity, this paper presents a complete Tapped Delay Line (TDL) channel model to characterize multipath propagation in presence of a wind farm, including novel scattering modeling and Doppler spectra characterization. As proved later, this channel model, which is based on both theoretical development and empirical data obtained in the surroundings of a real wind farm, is adaptable to the particular features of any case under study: wind turbine dimensions, working frequency, and relative location of the wind farm, transmitter and receivers.

This paper presents a novel multi-layer iterative decoding scheme using deterministic bits to lower the decoding threshold of LDPC codes in wireless multimedia communication systems. These deterministic bits serve as known information in the LDPC decoding process to reduce the redundancy during data transmission. Unlike the existing work, our proposed scheme addresses the controllable deterministic bits, such as MPEG null packets, rather than the widely investigated protocol headers. In particular, our multi-layer scheme integrates deterministic bit identification into LDPC decoding process. This integration is able to make significant performance improvement if adequate deterministic bits are discovered. We find that the length of deterministic bits may vary from time to time, and the exploring of deterministic bits is associated to a series of shortened parity matrices during the decoding iterations. Accordingly, we develop a recursive LDPC shortening algorithm to match the dynamic length and facilitate the iterative identification of deterministic bits. Simulation results show that our proposed scheme can achieve considerable gain in today's most popular broadband wireless access networks such as WiMAX.

Low-density parity-check (LDPC) codes are playing an important role in modern wireless communication systems such as WiMAX due to their Shannon limit approaching error correction performance. To lower the decoding threshold of LDPC codes, this paper develops a novel multi-layer iterative decoding scheme using deterministic bits for multimedia communication systems. These deterministic bits serve as known information in the LDPC decoding process to reduce the redundancy during data transmission. Unlike the existing work, our proposed scheme addresses the controllable deterministic bits, such as MPEG null packets, rather than the widely investigated protocol headers. Simulation results show that our proposed scheme can achieve considerable gain in WiMAX networks.

Among various network topologies, tree-like networks, also known as hierarchical networks are proposed to decrease the overhead of the routing table especially for the situation involving many network nodes. Usually, the routing table size and the routing complexity are the two crucial concerns in designing a large network. Although there have been various algorithms to optimise the routing strategies for the hierarchical networks, hardly exists any work in studying and evaluating the routing table size and the routing complexity rigorously in the statistical sense. In this study, the authors generalise a new mathematical framework by applying the point process in random geometry. The new framework proposed by the authors leads to the explicit statistical measures of the routing table size and the routing complexity, which can be specified as the functions of the hierarchical network parameters including the number of the hierarchical levels and the cluster population for each hierarchical level. After the relationship between the network topology and these two network performance measures (routing complexity and routing table size) is established, a cluster-population optimisation method for hierarchical networks is presented. The simulation results are also provided to demonstrate the advantage of a hierarchical network over the associated conventional network without hierarchy.

The digital imaging technology has grown explosively for multimedia applications in recent years. The need for the copyrighted digitalized media becomes urgent nowadays. An approach for the digital copyright protection is to employ advanced watermarking techniques, where watermarks can reveal the ownership identities. Generally speaking, the watermarks are embedded into image or video signals. In this paper, we will investigate digital watermarking techniques and propose a new optimal watermarking scheme. When multiple embedded watermarks are considered, a new analysis for the signal-to-interference-plus-noise-ratios (SINRs) with respect to the subject signal and the watermark signals is carried out. The objective quality measure for the digital watermarking applications should essentially consist of both signal-to-interference-plus-noise-ratio for the subject signal and similarity coefficients for the watermarks. In order to optimize the aforementioned objective measure, we design a novel efficient scale-factor optimization scheme, which can lead to the maximum overall SINR for both subject signal and watermarks. Simulation results are also demonstrated to illustrate the effectiveness of our proposed method.

ENG is a broadcasting industry acronym which stands for electronic news gathering in digital terrestrial television systems. It usually means that a television crew take an ENG truck on location to do a live report for a newscast. The ENG transmitter identification becomes important in digital video broadcasting nowadays. However, the transmitter identification could be quite difficult in a distributed transmission network. A pseudo-random sequence was proposed to be embedded into the digital television (DTV) signal prior to transmission. Thus, the transmitter identification can be realized by invoking the cross-correlation functions between the received signal and the possible candidates of the pseudo random sequences. Kasami sequences are commonly used as the transmitter ID (Tx-ID) sequences as they provide a large family of nearly-orthogonal codes. In order to investigate the sensitivity of the transmitter identification performance to the arbitrary topologies and the Kasami sequence lengths, we present the new analysis here for Tx-ID over random geometric layouts. In our analysis, the lowest received co-channel signal-to-interference ratio is considered as the crucial factor for the multiple-transmitter identification. Moreover, the transmitter location uncertainties are also considered in this paper. The effect of such uncertainties on the minimum required Kasami sequence lengths is investigated. It turns out to be that the larger the Kasami sequence length, the larger the received signal-to-interference ratio. Our new analysis can be used to determine the required Kasami sequence length for an arbitrary ENG-transmitter topology.

Various terrestrial digital television broadcasting standards have been developed in the last two decades for both fixed residential and mobile receivers. Since personal mobile terminal integrated with multiple functionalities is becoming more popular, it is highly desirable to come up with a universal platform for mobile TV reception which can detect the system parameters of DTV signals automatically and adjust its receiving mechanism correspondingly. In this paper, we propose a progressive automatic method for parameter extraction of OFDM-based mobile broadcasting signals. Classification of ATSC and OFDM based DTV signals can be easily achieved with the unique pilot of ATSC signals. Based on a combination of cyclostationarity test and conventional correlation, the proposed algorithm can estimate system parameters of the received OFDM signal, including the sampling rate, the number of subcarriers and the CP length (CP ratio), without any prior information.

In this paper, we propose a modification to Belief Propagation (BP) decoding algorithm for LDPC codes. The modification is to attenuate the check to bit extrinsic logarithm likelihood ratio by a factor α, when sudden sign change happens. This modification can be applied to both the standard BP algorithm and the joint row and column (JRC) BP algorithm. Simulation results show that the BER and WER performance of both traditional BP and JRC BP algorithms is improved by this method. The expense of the proposed modification is a slight increase in the average number of decoding iterations.

This paper investigates the design of LDPC codes over mobile DTV multipath channels. Most of the existing LDPC codes are optimized for additive white Gaussian noise (AWGN) channel, and not feasible to encounter the long burst error occurring in mobile DTV channel. Accordingly, we study the error propagation statistics of decision feedback equalizer (DFE) and formulate it into a gated noise model. To achieve good error correction in burst error channel, we proposed a class of dual-degree IRA codes to balance the metrics of decoding threshold and robustness. Extensive simulation results are presented in this paper to justify the performance of dual-degree IRA codes over gated noise model.

This paper investigates the use of ATSC M/H digital television (DTV) signal for location finding. In comparison to satellite based location finding system, DTV signals have higher field strength, wider bandwidth, lower frequency band, and DTV transmission towers are pervasively available everywhere. They can be used for indoor and mobile location finding in major cities where satellite based system might not function well. The ATSC receiver can obtain the multiple transmitter impulse responses and signal arrival times using the embedded RF watermark (RFWM) signal, and then derives its geographic coordinates based on the position of ATSC transmitters. As a critical step of this process, the transmitter identification in mobile environment has significant impact on the overall accuracy of location finding. In this paper, we present extensive analytical and simulation results to demonstrate the performance of RFWM technology over mobile channels.

In order to decrease the overhead of the dynamic routing mechanisms in large networks, the hierarchical routing protocols have been proposed in the early 80's. The routing complexity and the routing table size are the two most important functional blocks in a dynamic route guidance system. Although various algorithms exist for finding the best routing policy on a hierarchical network, hardly exists any work in studying and evaluating the aforementioned measures of routing complexity and routing table size for a hierarchical network. In this paper, by applying the random geometry theory, we can generalize the mathematical framework from the previous work which discussed the worst-case deterministic models. Our proposed new framework can carry out the averages of the routing complexity and the routing table size, which can be specified as the functions of the hierarchical network parameters such as the number of the hierarchical levels and the subscriber densities (cluster-population) for each hierarchical level. After establishing the relationship between the structure of a hierarchical network and these two crucial network performance measures (routing complexity and routing table size), we present a novel cluster-population optimization method for hierarchical networks and the associated statistical analysis.

This paper introduces a novel adaptive guard-interval scheme for multiple-input multiple-output (MIMO) orthogonal-frequency-division-multiplexing (OFDM) systems. Conventional OFDM systems set the guard-intervals large enough to combat the inter-symbol interference (ISI). However, such long guard-intervals would often lead to the severe throughput reduction. We design a non-pilot-aided channel-length estimation scheme, which does not require the additional pilot overhead, and propose a new MIMO-OFDM system built on such an adaptive prefix mechanism triggered by the feedback channel length information. Our simulations show that the proposed scheme greatly outperforms the conventional MIMO-OFDM systems.

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.

Channel estimation and equalization techniques are crucial for the ubiquitous wireless communication systems. Conventional receivers for most wireless standards preset the channel length to the maximal expected duration of the channel impulse response for the adopted channel estimation and equalization algorithms. The excessive channel length often significantly increases the implementational complexity of the wireless receivers and leads to the redundant information which would induce the additional estimation errors. Moreover, such a scheme does not allow the dynamic memory allocation for variable channel lengths. This could further increase the power consumption and reduce the battery life of a mobile device. The knowledge of the actual channel length would, in principle, help the system designers decrease the complexity of the channel estimators using maximum likelihood (ML) and minimum-mean-square-error (MMSE) algorithms. In this paper, we address this important channel length estimation problem and propose a novel algorithm to estimate the channel length without the need of pilots or training sequence. In addition, we provide the analysis on the effectiveness of the proposed non-pilot-aided channel length estimator through Monte Carlo simulations.

Recent development in cognitive radio (CR) brings significant technical challenges in the design of robust and flexible transmission technique in hostile communication environment with varying channel condition. An adaptive orthogonal frequency division multiplexing (OFDM) system, with a precoded cyclic prefix (PCP), is proposed in this paper to address these challenges. Besides the basic function as a guard interval for the OFDM systems, the PCP provides an efficient way of sending the transmission system parameters of the cognitive radio simultaneously with the data carrying OFDM signal. These parameters may include the bandwidth, total number of OFDM subcarriers, modulation and coding schemes used. Overall spectrum efficiency can be improved due to the elimination of the preambles and handshaking signaling required when there is any change in the CR transmission parameters. The receiver design particularly a hybrid domain equalizer for the PCP-OFDM system is presented in this paper. Implementation related issues including exploitation of the PCP structure, interference cancellation and complexity reduction are investigated. The performance of the proposed OFDM systems and the channel estimators are analyzed and verified through numerical simulations.

A new multicarrier system, termed multi-symbol encapsulated orthogonal frequency division multiplexing (MSE-OFDM), was proposed earlier, in which one cyclic prefix (CP) is used for multiple OFDM symbols. The motivation of MSE-OFDM is to address the disadvantages of OFDM system, i.e., the sensitivity to carrier frequency offset and high peak to average power ratio at the same time. In this paper, we propose a new time slicing technique by replacing the cyclic prefix with preceded pseudo random sequence for MSE-OFDM system. With the proposed time slicing technique, multiple multimedia data streams with dynamic data rates can be easily multiplexed. In addition, this system overcomes the high sensitivity to frequency offset inherited with OFDMA system and can be used for both uplink and downlink for mobile multimedia communications with variable data rates. The proposed time slicing system also enables the power saving for mobile receivers, through which the batter life can be substantially extended.

Wideband source localization using acoustic sensors has been drawing a lot of research interest recently in wireless communication applications, such as cellular handset localization, global positioning systems (GPS), and land navigation technologies, etc. The maximum-likelihood is the predominant objective which leads to a variety of source localization approaches. However, the appropriate optimization (search) algorithms are still in pursuit by researchers since different aspects about the effectiveness of such algorithms have to be addressed on different circumstances. In this paper, we focus on the two popular source localization methods for wideband acoustic signals, namely the alternating projection (AP) algorithm and the expectation maximization (EM) algorithm. We explore the respective limitations of these two methods and design a new hybrid approach thereupon. Through Monte Carlo simulations, we demonstrate that the trade-off can be achieved between the computational complexity and the localization accuracy using our newly proposed scheme.

It has been widely known that one of the key design parameters in orthogonal frequency division multiplexing (OFDM) systems is the distribution of peak-to-average power ratio (PAPR). Recently some theoretical approaches to determine the PAPR distribution have been proposed based on the assumption that all subcarriers are allocated with equal power. However, this assumption may not be valid due to the following facts. First, in all realistic OFDM systems, usually only a subset: of subcarriers are used to carry information (active subcarriers) and the rest (inactive subcarriers) are set to zero. Second, due to the efficiency concerns transmission power should be allocated to active subcarriers. Third, power allocation may vary depending on different constellations used by different active subcarriers and their signal-to-noise-ratios. In this paper, we propose a general approach to identify PAPR distribution in OFDM systems. Specifically, a more accurate analytical expression of the PAPR distribution is derived with the help of Extreme Value Theory for Chi-squared-2 process in OFDM systems with unequal power distribution strategy. To validate the analytical results, extensive simulations have been conducted, showing a very good match between the identified PAPR distribution and that of real OFDM systems.

The intercarrier interference (ICI) due to the Doppler frequency shift, sampling clock offset, time-varying multipath fading and local oscillator frequency offset becomes the major difficulty for the data transmission via the wireless orthogonal frequency division multiplexing (OFDM) systems. The existing ICI mitigation schemes involve the frequency-domain channel estimation/equalization or the additional coding and therefore require the pilot symbols which reduce the throughput. The frequency-domain channel estimation/equalization relies on the huge matrix inversion with high computational complexity especially for the OFDM technologies possessing many subcarriers such as digital video broadcasting (DVB) systems and wireless metropolitan-area networks (WMAN). In our previous work, we proposed a semi-blind ICI equalization scheme using the joint multiple matrix diagonalization (JMMD) algorithm and empirically showed that the proposed method significantly improved the symbol error rates for QPSK- and 16QAM-OFDM systems. In this paper, we discuss the sufficient condition for the theoretical ICI equalizability and also propose an alternative semi-blind ICI equalization method based on the joint approximate diagonalization of eigen-matrices (JADE) algorithm, which is much more computationally efficient than our previous method.

Kurtosis minimization has been applied for the existing blind equalization schemes but the corresponding optimization procedures are very sensitive to the channel conditions and the initial conditions. In this paper, we introduce a new cognitive receiver front-end, which includes a novel switching blind equalizer and an automatic modulation classifier. We design a switching criterion based on the kurtosis/normalized moment ratio threshold to select the better signal between the raw data and the equalized sequence. Simulations demonstrate that our proposed robust switching blind equalization scheme can significantly outperform the existing blind equalizer and would not degrade the subsequent modulation classification accuracy.

A new cross-layer signaling interface using overlay watermarks for orthogonal frequency division multiplexing (OFDM) system is proposed in this paper. The major advantage of the new proposal is the multiple functionalities the overlay watermark provides, which includes a cross-layer signaling interface, a transceiver identification for position-aware cross-layer design, as well as its basic role as a training sequence for channel estimation. Location information of a mobile can be easily derived for efficient routing when a unique watermark is associated with each individual mobile transceiver. In addition, a new data pipe can be created by modulating the overlay watermarks for the transmission of cross-layer signaling and other interlayer interactive information. We also study the channel estimation and watermark removal techniques at the physical layer for the proposed overlay OFDM. Our channel estimator iteratively estimates the channel impulse response and the combined signal vector from the overlay OFDM signal. Cross-layer design that leads to low power consumption and more efficient routing are investigated.

We propose a new Multi-Symbol Encapsulated Orthogonal Frequency Division Multiplexing (MSE-OFDM) system with reduced implementation complexity in this paper, by replacing the traditional cyclic prefix (CP) with one pseudo random sequence. Although robust performance and high bandwidth efficiency are achieved, the receiver implementation of the previous MSE-OFDM system is substantially more complicated than traditional OFDM. In this paper, we propose a new cyclic prefix for MSE-OFDM using pseudo random sequences. With the new introduced cyclic prefix, inter-symbol interference (ISI) between OFDM symbols within one MSE-OFDM frame can be easily canceled in time domain. An iterative intercarrier interference (ICI) cancellation algorithm is also proposed in this paper. Equalization of the OFDM signal can therefore be achieved on every OFDM symbol basis, based on our new hybrid domain equalizer. It is shown that the implementation complexity of the new MSE- OFDM receiver with the pseudo random sequence cyclic prefix is comparable to the traditional OFDM. The performance of the proposed MSE-OFDM is also analyzed and verified through numerical simulations.

The intercarrier interference (ICI) matrix for the orthogonal frequency division multiplexing systems usually has a fairly large dimension and changes over time for mobile communications. In this paper, we design the modified maximum-length shift-register sequences and propose a new distributive allocation scheme together with a linear interpolation for both pilot-aided and non-pilot-aided ICI vector estimates; this new method can combat the realistic non-circulant ICI matrix problem, where almost all other existing schemes could not perform effectively. Monte Carlo experiments show the significant advantages of our new ICI matrix estimator especially when the signal-to-noise ratio is larger than 15 dB

We propose a new orthogonal frequency division multiplexing (OFDM) system embedded with overlay training watermarks in this paper. The major advantage of the proposed overlay watermark is the elimination of the in-band OFDM pilots while keeping the peak to average power ratio (PAPR) low for the overlay OFDM signal. As a result, the corresponding spectral efficiency and the transmitter amplifier efficiency are both improved over the existing OFDM systems. The adopted Kasami sequence encrypted overlay watermark is known to the receiver and has very minimal impact on the data detection performance once the channel impulse response is estimated. The proposed channel estimation technique is based on an iterative estimation of the channel impulse response, and the combined signal vector from the overlay pilot sequence and the desired OFDM signal. We also investigate the crucial interfering effect of the overlay pilot on the OFDM signal demodulation. The PAPR of the overlay OFDM signal is analyzed and it is shown that the PAPR of our proposed new scheme is less than the OFDM systems using the frequency domain overlay sequences. Moreover, according to our PAPR analysis, a new PAPR reduction technique via the selective watermark insertion is also designed in this paper.

Since the modulation type is unknown at a cognitive receiver front-end, the training sequence or pilot symbols are not available and the robust blind equalization is in demand to combat the fading channel problem and improve the symbol detection performance. Kurtosis minimization has been applied for the existing blind equalization schemes but the corresponding optimization procedures are very sensitive to the channel conditions and the initial conditions. In this paper, we introduce a new cognitive receiver front-end, which includes a novel switching blind equalizer and an automatic modulation classifier. We design a switching criterion based on the kurtosis/normalized moment ratio threshold to select the better signal between the raw data and the equalized sequence. Monte Carlos simulations show that our proposed robust switching blind equalization scheme can significantly outperform the existing blind equalizer and would not degrade the latter modulation classification accuracy.

Performance of a new position location system using the transmitter identification (TxID) RF watermark in the digital TV (DTV) signals is analyzed in this paper. Compared to the Global Positioning System (GPS), DTV signals are received from transmitters at relatively short distances, while the broadcast transmitters operate at levels up to a few megawatts of effective radiated power (ERP), which makes the new position location system very robust even inside buildings. Practical receiver implementation issues including non-ideal correlation function and frequency synchronization are analyzed and discussed. New algorithms of removing the bandlimitation effect and frequency synchronization are proposed. Performances of the proposed techniques are evaluated through analysis and Monte Carlo simulations. Possible ways to improve the accuracy of the new position location system are discussed.

Recently, the growing popularity of low-complexity multi-carrier modulation techniques, such as orthogonal frequency division multiplexing (OFDM), has led researchers to consider equalization of single carrier (SC) transmissions in the frequency domain. However, existing frequency domain equalizers for single carrier modulation rely on the introduction of a cyclic prefix (CP), which are usually not available in the conventional SC based communications standards. In this paper, a frequency domain equalizer (FEQ) without cyclic prefix for single carrier system is proposed. An interference analysis is presented for the block equalization of SC system without CP. The cancellation of the inter-block interference and inter-carrier interference are based on the proposed iterative interference cancellation. The proposed equalizer and the subsequent analysis are also verified through numerical simulations.

The intercarrier interference (ICI) matrix for the orthogonal frequency division multiplexing (OFDM) systems usually has a fairly large dimension and changes over time for mobile communications. Obviously, the traditional least-square solution for the ICI matrix estimation based on the pseudo-inverse operation has its limitation. In addition, the provision of a sufficiently long training sequence to estimate the complete ICI matrix is not feasible, since it will result in severe throughput reduction. In this paper, we design padded maximum-length shift-register sequences (pm-sequences) to serve as the training sequences for the ICI estimation. Such new training sequences will induce the diagonal correlation matrices which can lead to the optimal estimation. We propose a new distributive allocation scheme of short pm-sequences for the ICI estimation with a linear ICI estimate interpolation, which can lead to the multi-ICI-vector estimation to combat the realistic non-circulant ICI matrix problem, where almost all other existing schemes such as the ICI matrix estimation using the Hadamard sequences, the convolutional coder/decoder and the ICI self-cancellation coder/decoder could not perform effectively

This special issue of the proceedings of the IEEE presents a systematical and complete tutorial on digital television (DTV), produced by a team of DTV experts worldwide. This introductory paper puts the current DTV systems into perspective and explains the historical background and different evolution paths that each system took. The main focus is on terrestrial DTV systems, but satellite and cable DTV are also covered,as well as several other emerging services.

The intercarrier interference (ICI) matrix for the orthogonal frequency division multiplexing (OFDM) systems usually involves a fairly large dimension. The traditional least-square solution based on the pseudo-inverse operation therefore has its limitation. In addition, a sufficiently long training sequence to estimate the complete ICI matrix is not feasible since it results in the severe throughput reduction. In this paper, we derive a lower bound for the mean-square estimation error among the least-square ICI matrix estimators using different training sequences and prove that the minimum mean-square error (MMSE) optimality is attained when the training sequences carried by different OFDM blocks are orthogonal to each other, regardless of the sequence length. Then we propose to employ the training sequences based on the padded maximal-length shift-register sequences (m-sequences) so as to achieve a highly efficient and optimal ICI matrix estimator with the minimum mean-square estimation error among all least-square ICI matrix estimators. Besides, our new scheme involves only linear complexity while other existing least-square methods require the complexity proportional to the cube of the ICI matrix size. Both analytical and experimental comparisons between our new scheme using padded m-sequences and the existing method using conventional m-sequences justify the significant advantages of our new ICI matrix estimator.

A new multicarrier system, termed multi-symbol encapsulated orthogonal frequency division multiplexing (MSE-OFDM), was proposed, in which one cyclic prefix (CP) is used for multiple OFDM symbols. The motivations for this new OFDM system are either to reduce the redundancy caused by the CP or to increase the system robustness to frequency offset, depending on the two different proposed implementations for the MSE-OFDM systems. The corresponding frequency offset and channel estimation algorithms are investigated. Possible ways to reduce the complexity of the joint maximum likelihood (ML) estimator, including the approximation of the joint ML estimator and FFT pruning, are discussed. The performance of the proposed estimators is also analyzed and verified through numerical simulations.

A feature-suppressed orthogonal frequency-division multiplexing (OFDM) system and the corresponding channel estimation and intersymbol interference (ISI) mitigation techniques are investigated in this paper. Cyclic prefix (CP) and pilot tones, which are commonly used in civilian OFDM systems for ISI mitigation and channel estimation, create distinctive waveform features that can be easily used for synchronization and channel estimation purposes by intercepting receivers. As a result, CP and pilot tones are eliminated in the proposed feature suppressed OFDM system to reduce the interception probability. Instead, a set of specially designed OFDM symbols, driven by different pseudorandom sequences, are employed as preambles to avoid unique spectral signature. These preambles are inserted into the OFDM data symbol stream periodically and in a round-robin manner. In addition, a random frequency offset is introduced to each preamble to further mask the multicarrier signature. New challenges arising from these feature suppression efforts are studied, including robust channel estimation and demodulation techniques in the presence of frequency offset and severe interference. Based on our interference analysis, an iterative ISI and intercarrier interference (ICI) estimation-cancellation-based technique is proposed for both channel estimation and OFDM data demodulation. Our channel estimator performs joint frequency offset and channel impulse response estimation based on the maximum-likelihood (ML) principle. To reduce its complexity, we employ a number of techniques, which include approximation of the ML metrics, as well as fast Fourier transform pruning. The performances and feasibility of the proposed feature suppressed OFDM system and the channel estimator are analyzed and verified through numerical simulations.

A new multi-symbol encapsulated orthogonal frequency division multiplexing (MSE-OFDM) system is proposed, in which one cyclic prefix (CP) is used for a frame of multiple OFDM symbols. A system level comparison between a conventional OFDM and the proposed MSE-OFDM system is presented in this study. Two different realizations of the MSE-OFDM, i.e., CP-reduced and FFT size-reduced MSE-OFDM systems, are investigated for different system requirement. An analysis on the bandwidth efficiency, impact of synchronization errors on the system performance and peak to average power ratio (PAPR) of these systems is presented. Comparisons are made on two different assumptions, i.e., either keeping the symbol size of the MSE-OFDM (i.e., number of the subcarriers) unchanged to increase the bandwidth efficiency, or keeping the bandwidth efficiency unchanged (ratio between CP and useful data transmission time) for system robustness to synchronization errors and a lower peak-to-average power ratio. In the first case for CP-reduced MSE-OFDM, bandwidth efficiency is improved due to a reduced number of CPs inserted between OFDM symbols. For the latter case of FFT size-reduced MSE-OFDM, robustness to synchronization errors is improved considerably due to the smaller number of subcarriers. The proposed system is of particular interest for fixed wireless systems and digital subscriber loops (DSL). Large frame size can be used in these applications, due to the static nature of the channel conditions. Implementation complexity of the MSE-OFDM system is also discussed.

An encoding technique called multilevel block truncation coding that preserves the spatial details in digital images while achieving a reasonable compression ratio is described. An adaptive quantizer-level allocation scheme which minimizes the maximum quantization error in each block and substantially reduces the computational complexity in the allocation of optimal quantization levels is introduced. A 3.2:1 compression can be achieved by the multilevel block truncation coding itself. The truncated, or requantized, data are further compressed in a second pass using combined predictive coding, entropy coding, and vector quantization. The second pass compression can be lossless or lossy. The total compression ratios are about 4.1:1 for lossless second-pass compression, and 6.2:1 for lossy second-pass compression. The subjective results of the coding algorithm are quite satisfactory, with no perceived visual degradation.>

A color-image data compression technique based on block truncation coding (BTC) is described. BTC is first implemented to encode a weighted trichromatic image. The bit map generated is then used to compress each of the R, G, and B signals separately, removing the intercolor correlations. The weighted trichromatic signal is generated by properly weighting R, G, and B signals so that the reconstructed R, G, and B signals have minimum mean square error (MSE). Another approach using a bit-wise majority rule on the R, G, and B BTC bit maps is also discussed. The algorithm preserves the spatial details in the image content and has low computational complexity. An 8:1 compression can be achieved.>

A hybrid BTC-VQ-DCT (block truncation coding, vector quantization, and discrete cosine transform) image coding algorithm is presented. The algorithm combines the simple computation and edge preservation properties of BTC and the high fidelity and high-compression ratio of adaptive DCT with the high-compression ratio and good subjective performance of VQ, and can be implemented with significantly lower coding delays than either VQ or DCT alone. The bit-map generated by BTC is decomposed into a set of vectors which are vector quantized. Since the space of the BTC bit-map is much smaller than that of the original 8-b image, a lookup-table-based VQ encoder has been designed to 'fast encode' the bit-map. Adaptive DCT coding using residual error feedback is implemented to encode the high-mean and low-mean subimages. The overall computational complexity of BTC-VQ-DCT coding is much less than either DCT and VQ, while the fidelity performance is competitive. The algorithm has strong edge-preserving ability because of the implementation of BTC as a precompress decimation. The total compression ratio is about 10:1.>