This paper analyzes the performance of a deterministic channel estimation method for wireless systems affected by nonlinearities in the signal chain modelled using expanded memory polynomial (EMP). To solve the performance monotonicity issue, a novel transmission protocol employing random training signals (TSs) and an associated stochastic channel estimation method are then proposed for orthogonal EMP (OEMP)-modelled systems with significantly reduced statistics requirement. Practically measurable modelling errors are defined through alternative mean-squared-error (MSE) analyses, establishing their relationships with EMP and OEMP residual signal powers respectively under reduced nonlinearity orders. The OEMP modelling error is further proved to approach the OEMP residual signal power, ensuring the desired performance monotonicity. Numerical results validate the theoretical findings and highlight the impact of TS design on nonlinear channel estimation in practical applications.

The paper considers monostatic ISAC transceivers relying on in-band full-duplex (IBFD) capability to achieve simultaneous sensing and communication. These systems transmit a waveform for both communication and sensing and receive target echoes and incoming communication signals from other nodes. The major challenge is interference cancellation, suppressing self-interference (SI) from the leaked transmitted signal and the mutual interference (MI) between the echo for sensing and incoming signals for communication. This paper proposes an advanced joint analog and two-stage digital interference cancellation (DIC) structure to address this challenge, enabling simultaneous communication and sensing in IBFD ISAC systems. The analog SI cancellation structure leverages an analog least mean square (ALMS) loop with specific design constraints to preserve the integrity of sensing signals. A track-and-hold mechanism is employed to avoid ALMS weighting coefficient variation caused by the strong reflected sensing signal and uplink communication signal. The novel two-stage DIC first cancels residual SI for sensing and then mitigates echo sensing signals for communication. Doppler effects in the echo signals are compensated during the second stage to ensure effective suppression of sensing signals and accurate retrieval of communication signals. Simulation results validate the proposed approach, showcasing its strong communication and sensing performance and robust interference cancellation capabilities.

In this paper, we introduce a novel two-step framework for joint angle-of-arrival (AoA) and angle-of-departure (AoD) estimation for lens antenna array (LAA)-based multipleinput and multiple-output (MIMO) systems. This method is based on the properties of the sinc function in the array response of LAAs to reduce the dimensionality of the channel matrix collected through each signal snapshot. After completing the estimation of the AoA or AoD in the first step, the remaining angle can be determined in the next step. For example, for each estimated AoA, the corresponding off-grid AoD is found. Consequently, we eliminate the need for a pairing step as seen in other methods, thereby avoiding pairing errors. Furthermore, since the proposed scheme leverages multiple snapshots, the estimation accuracy at each step can be enhanced. Simulation results indicate that the proposed method achieves the highest performance gain among all studied schemes when the number of antennas and snapshots is sufficiently large.

In perceptive mobile networks (PMNs), using 5G New Radio (NR) signals for direct sensing poses a significant challenge to practical implementation due to the high computational complexity involved in estimating sensing parameters. In this paper, an efficient sensing method is proposed to incorporate both downlink active sensing and passive sensing to estimate multiple sensing parameters, including delays, angle of arrival (AoA), angle of departure (AoD) and Doppler. In particular, it exploits the synchronization signal blocks (SSBs) to facilitate sensing with multiple remote radio units (RRUs). To reduce the computational complexity of direct sensing, a sparse model is developed to decouple multiple sensing parameter estimation, enabling efficient sensing method design. Then, leveraging unitary approximate message passing (UAMP) and sparse Bayesian learning (SBL), we propose an efficient method to achieve parameter estimation and association with corresponding RRUs. This method is further extended to general scenarios involving multiple path components with the same delay. Extensive simulations demonstrate the effectiveness of the proposed method, showing that it outperforms existing ones in terms of sensing accuracy and complexity.

This paper explores two novel compressed sensing (CS) strategies for estimating the directions of incoming signals in a coherent environment using a lens antenna array (LAA). Compared to the subspace-based algorithm family, CS techniques, such as the conventional orthogonal matching pursuit (OMP), can effectively address the direction-of-arrival (DoA) estimation without prior knowledge about the number of signals at low complexity. However, they are sensitive to noise and can be adversely affected by multipath distortion. To overcome these limitations, we leverage the energy-concentrating property of an LAA and introduce the signal covariance matrix-based OMP (SCM-OMP) method. This method enhances the accuracy of angular estimation, even in regions with low signal-to-noise ratio (SNR). Furthermore, by analyzing the definition of mutual coherence (MC), we demonstrate that the SCM-OMP scheme achieves improved performance with a large number of antennas. We then propose the multiple sub-covariance matrices-based OMP (MSCM-OMP) to reduce computational complexity. We also analyze the exact recovery conditions of the studied OMP algorithms and utilize the noise reduction property to show that our proposed SCM-OMP and MSCM-OMP algorithms have better successful recovery probabilities than the OMP scheme. Moreover, we combine the Rife method with two proposed CS-based algorithms to overcome the off-grid effect. Simulation results confirm that the SCM- and MSCM-OMP schemes outperform other high-resolution DoA estimation methods in both on-grid and off-grid scenarios. Furthermore, the MSCM-OMP method can achieve a detection accuracy of higher than 60%, even in a low-SNR regime, i.e.,$\rm {SNR}=-10$dB.

The research of faster-than-Nyquist (FTN) signaling has reached a state of maturity for considering practical multipath fading channels, rather than idealized additive white Gaussian noise channels only. To overcome fast-fading multipath propagations, conventional FTN systems tend to rely on channel coding techniques for cleaning up the residual errors, rather than harnessing Doppler effect mitigation. To circumvent this limitation, we propose an adaptive transmit precoding (ATPC) method associated with FTN signaling for applications in fast-fading multipath channels. Upon leveraging real-time channel state information fed back by the receiver, ATPC updates the modulation matrix to improve resilience against Doppler frequency shifts. To mitigate the inter-block interference and multipath effect, a cyclic prefix is inserted at the beginning of each transmission frame. In addition, we employ decision-directed successive interference cancellation for alleviating the inter-symbol interference stemming from FTN signaling and multipath effects. We also analyze the theoretical bit error rate (BER) performance and a pair of closed-form BER expressions are derived for extreme channel conditions, i.e., sufficiently large number of paths and sufficiently large Doppler frequency shift. Simulation results verify the effectiveness of the proposed ATPC method and demonstrate our performance improvements over conventional schemes.

Current research on faster-than-Nyquist (FTN) systems mainly focuses on baseband digital signal processing without considering the impact of I/Q imbalance (IQI) caused by hardware impairments in the signal chain. To address this problem, this paper considers frequency-dependent IQI and applies the frame-based decision-directed successive interference cancellation (DDSIC) algorithm after minimum mean square error (MMSE) equalization to jointly mitigate inter-symbol interference (ISI) and IQI. We introduce extended-dimension signal models, which use both original and image signals to describe the impact of IQI. Based on the models, a two-stage iterative DDSIC algorithm is then proposed, achieving effective interference cancellation. Furthermore, the theoretical bit error rate (BER) for each iteration of DDSIC and the BER lower bound of the proposed system are derived. Simulation results demonstrate the superiority of DDSIC over some existing algorithms under both additive white Gaussian noise (AWGN) and multipath fading channels. These results also validate the derived theoretical BER expressions and the robustness of our scheme under various ISI and IQI scenarios, respectively.

This paper introduces a novel method for radio frequency (RF) self-interference (SI) cancellation in in-band full-duplex (IBFD) communication systems using a generalized analog least mean square (GALMS) loop. Conventional research in this area has predominantly focused on employing the tapped delay line (DL) structure to process the RF transmitted signal. The proposed GALMS loop utilizes a filter bank applied on the baseband transmitted signal to avoid the limitation of the conventional tapped DL adaptive filters, which require tapped spacing to satisfy the Nyquist principle. We utilize frequency domain representation and steady-state analysis to derive the modeling error and residual SI power of the proposed structure. Notably, the GALMS loop incorporating an allpass filter bank can achieve the same level of SI cancellation as the conventional DL structure with a significantly reduced number of taps. Simulations are conducted to validate the efficiency of the proposed GALMS loop and prove the theoretical findings.

This paper delves into a novel compressed sensing (CS) strategy for estimating the directions of incoming signals in a coherent environment using a lens antenna array (LAA). In comparison to the well-known subspace-based algorithm family, CS techniques, such as the conventional orthogonal matching pursuit (COMP), can effectively address the direction-of-arrival (DoA) estimation problem requiring prior knowledge about the number of signals and offer lower complexity. However, they are susceptible to noise and can be adversely affected by multipath distortion. Leveraging the energy-concentrating property of an LAA, we first introduce the signal covariance matrix-based OMP (SCM-OMP) method that enhances the angular estimation performance, even in low-SNR regions. Subsequently, we propose the multiple sub-covariance matrices-based OMP (MSCM-OMP) to achieve a reduction in computational complexity. Simulation results demonstrate that the MSCM-OMP scheme also outper-forms other high-resolution DoA estimation methods.

Segment Anything Model (SAM) is an innovative image segmentation model by Meta AI. It has demonstrated generalization capabilities across a diverse range of image datasets with zero shot. The objective of this study is to advance SAM applications in building detection for high resolution optical satellite imagery. The automated mask produced by SAM for RGB 3 channels of satellite imagery is initially introduced as an additional channel. Subsequently, the DeeplabV3+ deep learning model with Dilated ResNet C42 backbone is employed to train the combination of these four channels along with the ground truth of building masks for effective building detection. The SpaceNet dataset serves as the foundational training dataset, while a new dataset specific to Southeast Asia is incorporated for fine-tuning the model. Results demonstrate the model's notable success in building detection across various satellite images.

Joint communications and sensing (JCAS) have the potential to improve the overall energy, cost and frequency efficiency of Internet-of-Things (IoT) systems. As a first effort, we propose to optimize the MIMO-OFDM data symbols carried by sub-carriers for better time-and spatial-domain signal orthogonality. This can reduce inter-target and inter-antenna interference, enabling high-quality sensing. We establish an optimization problem that modifies data symbols on sub-carriers to enhance the above-mentioned signal orthogonality. We also develop an efficient algorithm to solve the problem based on the majorization-minimization framework. Moreover, we discover unique signal structures and features from the newly modeled problem, which substantially reduce the complexity of majorizing the objective function. We also develop new projectors to enforce the feasibility of the obtained solution. Simulations show that to achieve the same sensing performance, the optimized waveform can reduce the signal-to-noise ratio (SNR) requirement by 3~4.5 dB compared with the original waveform, while the SNR loss for the uncoded bit error rate is only 1~1.5 dB.

For wideband transceivers operating at millimeter wave and terahertz frequencies, the implementation of conventional digital predistortion for nonlinearity mitigation faces significant challenges due to the limited availability and/or complexity of high-speed digital signal processing. In this paper, a simple received signal model is proposed for wideband system with nonlinearity and other practical impairments, such as transmitter (Tx) and receiver (Rx) I/Q imbalances (IQIs), carrier frequency offset (CFO), and phase noise, to enable low-complexity impairment mitigation. An expanded memory polynomial (EMP) model is firstly proposed to capture Tx IQI and the nonlinearity over the entire transceiver chain. Exploiting the CFO and a novel transmission protocol, a blind Rx IQI estimation is also proposed. The noise enhancement after Rx IQI and CFO compensation is then evaluated as a noise factor related to the mean-square-error of the Rx IQI estimation. As a result, the received signal of the wideband system is finally modelled as an EMP plus additive noises followed by a band-limited noisy receiver filter. Simulation results using a millimeter wave system with 2.5 GHz bandwidth and 73.5 GHz carrier frequency are presented to verify the accuracy of the EMP modelling and validate the theoretical analyses.

Wideband millimeter wave and terahertz systems face severe nonlinearity and other practical impairments such as transmitter and receiver in-phase/quadrature imbalances (IQIs), carrier frequency offset, and phase noise. Based on a simplified yet effective received signal model including an expanded memory polynomial (EMP) and a noisy receiver filter, this paper proposes a low-complexity digital post-cancellation (DPC) framework for transmitter IQI and overall system nonlinearity mitigation. The nonlinearity parameters with reduced nonlinearity order are firstly estimated with low-complexity using a novel transmission protocol incorporating both frame rotation and preamble power scaling. Through widely linear system equalization and interference cancellation, the signal distortion caused by frequency-dependent IQI and nonlinearity is then mitigated with significant performance improvement. The mean-squared-error measurement of the EMP-modelled signals also provides a practical means for the nonlinear system identification and characterization. Both simulation and experiment results obtained from a millimeter wave system with 2.125 GHz bandwidth and 73.5 GHz carrier frequency are presented to verify the theoretical analyses and demonstrate the effectiveness of the DPC technology.

Integrating sensing into wifi platforms, referred to as wifi sensing, provides an efficient and device-free means for indoor monitoring/localization with low cost. Clock asynchrony is one of the most challenging issues in wifi sensing. A mainstream solution to date employs cross-antenna processing to suppress the clock offsets that are common to all antennas. Such methods, however, may suffer from issues such as mirrored targets and noise enhancement etc. This paper develops a novel wifi sensing scheme. It embodies accurate and low-complexity methods for estimating the timing and frequency offsets as well as the angle-of-arrival (AoA), all from the LoS path. It also involves a coherent Doppler processing method which effectively suppresses static paths and accurately estimates the Doppler by enjoying the coherent processing gain. Corroborated by experimental results using open Widar2.0 data, the proposed design is able to precisely recover the velocity traces in various indoor scenarios.

Effective wireless communications are increasingly important in maintaining the successful closed-loop operation of mission-critical Industrial Internet of Things (IIoT) applications. To meet the ever-increasing demands on better wireless communications for IIoT, we propose an orthogonal time-frequency space (OTFS) waveform-based joint communication and radio sensing (JCAS) scheme—an energy-efficient solution for not only reliable communications but also high-accuracy sensing. OTFS has been demonstrated to have higher reliability and energy efficiency than the currently popular IIoT communication waveforms. JCAS has also been highly recommended for IIoT, since it saves cost, power, and spectrum compared to having two separate radio frequency systems. Performing JCAS based on OTFS, however, can be hindered by a lack of effective OTFS sensing. This article is dedicated to filling this technology gap. We first design a series of echo preprocessing methods that successfully remove the impact of communication data symbols in the time-frequency domain, where major challenges, such as intercarrier and intersymbol interference and noise amplification, are addressed. Then, we provide a comprehensive analysis of the signal-to-interference-plus-noise ratio (SINR) for sensing and optimize a key parameter of the proposed method to maximize the SINR. The extensive simulations show that the proposed sensing method approaches the maximum-likelihood estimator with respect to the estimation accuracy of target parameters and manifests applicability to wide ranges of key system parameters. Notably, the complexity of the proposed method is only dominated by a 2-D Fourier transform.

In this letter, we investigate a novel optimization approach to direction-of-arrival (DoA) estimation for a lens antenna array. Inspired by a property of the sinc function and${\ell _{2}}$-norm optimization, we develop the gradient descent-based spatial spectrum reconstruction (GD-SSR) to estimate the DoAs based on the sum signal covariance vector (SSCV). Our proposed algorithm does not require a priori knowledge of signal number and has a lower complexity compared with existing techniques while achieving a better estimation performance, even in a low-SNR regime. In addition, the proposed model does not require any pretraining process as prior learning-based methods. The simulation results show that our scheme not only outperforms other techniques but also resolves the angular ambiguity problem.

Faster-than-Nyquist (FTN) signaling can improve spectral efficiency and enable high-speed transmission for next-generation communication systems. One of the most significant challenges in FTN transmission is how to remove the inter-symbol interference (ISI). In this paper, we propose a novel decision-directed successive interference cancellation (DDSIC) based on frequency-domain minimum-mean-square-error (MMSE) equalization for practical FTN systems. To reduce the computational complexity, the detection process is performed frame-by-frame in the frequency domain. In addition, we derive the theoretical bit error rate (BER) expression for each iteration in DDSIC as well as the BER lower bound for$M$-ary quadrature amplitude modulated FTN systems. The simulation results verify the theoretical analyses and demonstrate that our proposed method enables lower complexity and better performance compared with state-of-the-art methods.

Beamspace millimeter-wave (mmWave) and terahertz (THz) massive MIMO constitute attractive schemes for next-generation communications, given their abundant bandwidth and high throughput. However, their user and beam selection problem has not been efficiently addressed yet. Inspired by this challenge, we develop low-complexity solutions explicitly. In contrast to the zero forcing in the prior art, we introduce the dirty paper coding (DPC) into the joint user and beam selection problem. We unveil the compelling properties of the DPC sum rate in beamspace massive MIMO, showing its monotonic evolution against the number of users and beams selected. We then exploit its beneficial properties for substantially simplifying the joint user and beam selection problem. Furthermore, we develop a set of algorithms striking unique trade-offs for solving the simplified problem, facilitating simultaneous user and beam selection based on partial beamspace channels for the first time. Additionally, we derive the sum rate bound of the algorithms and analyze their complexity. Our simulation results validate the effectiveness of the proposed design and analysis, confirming their superiority over prior solutions.

An effective and practical joint analog and digital self-interference cancellation (SIC) scheme without additional signalling overhead for an I/Q imbalanced full duplex transceiver is proposed in this paper. This scheme combines an I/Q imbalanced analog least mean square (ALMS) loop at the transceiver radio frequency frontend and a two-stage digital signal processing (DSP) at the digital baseband to achieve excellent SIC performance with low complexity. The steady state weighting coefficients of the I/Q imbalanced ALMS loop with periodical transmitted signal and the loop’s convergence behaviour are firstly analysed. The residual SI is then modelled as the output of a time-varying widely linear system. With a track/hold control mechanism applied to the ALMS loop, the system model for digital SIC is further presented, followed by the DSP algorithms suitable for real-time implementation. The noise enhancement in each stage digital cancellation is also analysed and formulated. Finally, simulation results are provided to verify the theoretical analyses and demonstrate the overall SIC performance.

Employing cyclic prefixed OFDM (CP-OFDM) communication waveform for sensing has attracted extensive attention in vehicular integrated sensing and communications (ISAC). A unified sensing framework is developed recently, greatly extending the ranging capability of CP-OFDM sensing. However, a false target issue still remains unsolved. In this paper, we investigate and solve this issue. Specifically, we unveil that false targets are caused by periodic cyclic prefixes (CPs) in CP-OFDM waveform. We also derive the relation between the locations of false and true targets, and other features, e.g., strength, of false targets. Moreover, we develop an effective solution to removing false targets. Simulations are provided to confirm the validity of our analysis and the effectiveness of the proposed solution.

Abstract Due to difficulties in manufacturing, data conversion devices with extremely high sampling rate are becoming the bottleneck in realising high‐speed communication systems with a large bandwidth. Dual pulse shaping (DPS) transmission allows half‐symbol‐rate conversion devices to be used for two parallel data streams to achieve full‐rate transmission, and is proved to be an effective solution. Here, two sets of ideal sinc‐function based complementary Nyquist pulses for DPS transmission are proposed. Theoretically, it is shown that the proposed pulses satisfy the inter‐symbol and cross‐symbol interference‐free conditions, and can achieve full‐Nyquist‐rate transmission with half of the sampling rate. With reference to commercially available D/As, two sets of practical dual spectral shaping pulses are further proposed, and the close relationship between the ideal and practical pulses are disclosed. Performance analysis for linear equalisation is provided in the presence of both timing offset between dual shaping pulses and carrier‐frequency offset. Two approaches are then proposed to improve the system robustness by adjusting the clock phase of the D/As and A/Ds. Simulation results are presented to provide a comparison between the proposed DPS transmission schemes and the state of the art, in terms of the performance metrics of peak‐to‐average power ratio and bit error rate.

Integrating sensing into standardized communication systems can potentially benefit many consumer applications that require both radio frequency functions. However, without an effective sensing method, such integration may not achieve the expected gains of cost and energy efficiency. Existing sensing methods, which use communication payload signals, either have limited sensing performance or suffer from high complexity. In this paper, we develop a novel and flexible sensing framework which has a complexity only dominated by a Fourier transform and also provides the flexibility in adapting to different sensing needs. We propose to segment a whole block of echo signal evenly into sub-blocks; adjacent ones are allowed to overlap. We design a virtual cyclic prefix (VCP) for each sub-block that allows us to employ two common ways of removing communication data symbols and generate two types of range-Doppler maps (RDMs) for sensing. We perform a comprehensive analysis of the signal components in the RDMs, proving that their interference-plus-noise (IN) terms are approximately Gaussian distributed. The statistical properties of the distributions are derived, which leads to the analytical comparisons between the two RDMs as well as between the prior and our sensing methods. Moreover, the impact of the lengths of sub-block, VCP and overlapping signal on sensing performance is analyzed. Criteria for designing these lengths for better sensing performance are also provided. Extensive simulations validate the superiority of the proposed sensing framework over prior methods in terms of signal-to-IN ratios in RDMs, detecting performance and flexibility.

Joint communication and radar sensing (JCAS) integrates the two functions into one system, sharing one transmitted signal. In this paper, we investigate JCAS waveform optimization in communication-centric systems, where a base station (BS) detects radar targets and communicates with mobile users simultaneously. Different from existing works, we study multi-metric optimizations for a practical low-cost system and establish their connections. To relax the requirement of full-duplex technology, we add a single receive antenna for sensing at the BS, which is synchronized with and spatially separated from the JCAS transmit array. We first optimize precoders for communications and radar, individually. Then, we formulate a JCAS waveform optimization problem that constrains either mutual information (MI) or Cramér-Rao bound (CRB) of radar and maximizes the relaxed signal-to-interference-plus-noise rate (SINR) of communications. Exploiting the geometric characteristic of the relaxed SINR, we provide a closed-form solution under certain conditions and propose a numerical iteration algorithm that works in all situations. We also disclose the connections between optimizations with constraining MI and CRB, using numerical results. Finally, simulation results are provided and validate the proposed optimization solutions.

The integration of terrestrial and satellite communications (Satcom) is advocated for satisfying the challenging requirements of seamless, high-performance services. However, both the bandwidth and the power available are limited over satellite channels. In this paper, we propose index modulation (IM) and code-aided Satcom by conveying information by a pair of distinguishable constellation modes and their permutations. In order to combat both the linear and nonlinear distortion imposed by satellite channels, we conceive a factor graph (FG)-based iterative detection algorithm for Satcom relying on dual-mode (DM) IM (Sat-DMIM). The correlation amongst Sat-DMIM symbols imposed by both the channel-induced dispersion and the mode-selection mapping is explicitly represented by the FG constructed. Then the amalgamated belief propagation (BP) and mean field (MF) message passing algorithm is derived over this FG for detecting both the IM bits and the classic constellation mapping bits, while eliminating both the linear and nonlinear distortions. The complexity of the iterative detection algorithm is reduced by linearizing some high-order terms appearing in nonlinear distortion components using thea posterioriestimates of the Sat-DMIM symbols obtained from the previous iteration. Our simulation results demonstrate the power of the proposed amalgamated BP-MF-based and partial linearization approximation-based iterative detection algorithms.

A novel noncoherent microwave imaging principle with periodical or random radio frequency (RF) illumination is proposed in this article. Implemented with circular array synthetic aperture radar (SAR) frontend and low-complexity signal processing algorithms, the imaging device, called RF camera, achieves some desired properties similar to an optical camera, such as the capability to operate with multiple uncoordinated illuminators. Different from conventional multistatic imaging, the RF camera does not require any knowledge about an illuminator’s location or signal waveform. A static illumination sensor (IS) can be used to provide a reference signal for image reconstruction. With periodical illumination, the RF camera can even operate without IS, but the imaging performance can be improved with IS. With random illumination, the IS is necessary for the RF camera operation, and the imaging distortion can be described by a point blur function. Theoretical analyses on the imaging signal-to-noise ratios are performed under different RF camera operation modes. Simulation and experimental tests are conducted using 77-GHz millimeter wave frequency to verify the noncoherent imaging principle and its performance.

This article presents an universal circular synthetic aperture radar (SAR) (UCSAR) by which the targets to be observed at any radial distance can be imaged, thus making SAR imaging possible in a more general scenario with a circular movement of the radar platform. The UCSAR point spread function (PSF) is firstly analyzed based on the time-domain correlation imaging approach, and thus a three-dimension (3-D) spatial variant PSF of the target can be formulated. The closed-form PSF expressions with single-frequency and frequency-modulated continuous wave (FMCW) transmitted signals are derived respectively to quantify the imaging resolutions, showing that the PSF is a product of a sinc function and a zeroth-order Bessel function when using a wideband FMCW signal. Secondly, a fast UCSAR imaging algorithm and its further simplified version are proposed to reduce the computational cost significantly based on the piecewise constant Doppler (PCD) principle. To quantify the imaging performance, we derive an error function of the slant range approximation for the proposed algorithm, serving as a practical guideline for the UCSAR parameter selection. Finally, the simulation and experimental results are provided to validate the PSF analysis, the fast imaging algorithm, and the implementation of the proposed UCSAR.

This paper proposes a new synthetic aperture radar (SAR), named as panoramic SAR, based on a combination of linear and rotational SARs, by which a large 360-degree panoramic view of the observed scene can be reconstructed. Firstly, the system geometry and its imaging process based on the back-projection algorithm (BPA) are presented. The combined movement constitutes a two-dimensional synthetic aperture and thus higher imaging resolutions can be obtained. The corresponding resolution analysis and the sampling criteria are discussed accordingly. Then, a novel dynamic piecewise compensation (DPC) algorithm, a recursive imaging process, is proposed to reduce the processing complexity significantly. The imaging implementation and the complexity are also studied respectively. Finally, a prototype of panoramic SAR is built based on an frequency modulated continuous wave (FMCW) radar and a moving platform, and the simulation and experimental results are provided to validate the proposed panoramic SAR principle and the DPC algorithm.

Dual-function radar-communication (DFRC) based on frequency hopping (FH) MIMO radar (FH-MIMO DFRC) achieves symbol rate much higher than radar pulse repetition frequency. Such DFRC, however, is prone to eavesdropping due to the spatially uniform illumination of an FH-MIMO radar. In this paper, we reveal the potential of using permutations of hopping frequencies to achieve secure and high-speed FH-MIMO DFRC. Specifically, we identify the angle-dependent issue in detecting permutations and develop an element-wise phase compensation (EPC) to solve the issue for a legitimate user (Bob). EPC makes the demodulation at an eavesdropper (Eve) conditioned on knowing the angle-of-departure (AoD) of Bob. We also propose the random sign reversal (RSR) technique which randomly selects several antennas over hops and reverses their signs. Owing to EPC, there is a sign rule available for Bob. We employ the rule and develop a low-complexity algorithm for Bob to remove RSR. We further prove that, given the same signal-to-noise ratio, RSR plus EPC make the demodulation performance of Eve inferior to that of Bob in most angular regions. Confirmed by simulation, our design achieves substantially high physical layer security for FH-MIMO DFRC, improves demodulation performance compared with existing designs, and reduces mutual interference among radar targets.

Achieving better performance in high mobility scenarios has become an emerging topic for next generation wireless communications. Compared with traditional modulation techniques, the recently proposed orthogonal time frequency space (OTFS) shows outstanding performance over fast fading channels. In this paper, the OTFS system is first represented in the form of precoded orthogonal frequency division multiplexing (OFDM), enabling traditional estimation and equalization techniques to work under fast fading channels. Then, a novel frequency-domain pilot-aided channel estimation scheme is proposed to obtain the channel state information at the receiver. Simulation results show that the new channel estimation scheme works efficiently in different channel scenarios. Meanwhile, the overhead of the proposed scheme is also lower than those of the current popular schemes.

Frequency-hopping (FH) MIMO radar-based dual-function radar communication (FH-MIMO DFRC) enables communication symbol rate to exceed radar pulse repetition frequency, which requires accurate estimations of timing offset and channel parameters. The estimations, however, are challenging due to unknown, fast-changing hopping frequencies and the multiplicative coupling between timing offset and channel parameters. In this article, we develop accurate methods for a single-antenna communication receiver to estimate timing offset and channel for FH-MIMO DFRC. First, we design a novel FH-MIMO radar waveform, which enables a communication receiver to estimate the hopping frequency sequence (HFS) used by radar, instead of acquiring it from radar. Importantly, the novel waveform incurs no degradation to radar ranging performance. Then, via capturing distinct HFS features, we develop two estimators for timing offset and derive mean squared error lower bound of each estimator. Using the bounds, we design an HFS that renders both estimators applicable. Furthermore, we develop an accurate channel estimation method, reusing the single hop for timing offset estimation. Validated by simulations, the accurate channel estimates attained by the proposed methods enable the communication performance of DFRC to approach that achieved based on perfect timing and ideal knowledge of channel.

Frequency-hopping (FH) MIMO radar is recently introduced as an underlying system for realizing dual-function radar-communication (DFRC), increasing communication symbol rates to multiples of the radar pulse repetition frequency. As a newly conceived DFRC system, many realistic issues, such as channel estimation and synchronization, are not effectively solved yet. In this paper, we develop a multi-antenna receiver-based downlink communication scheme for the FH-MIMO DFRC, addressing the above issues in multi-path channels. By exploring the unique FH-MIMO radar waveform, we suppress both inter-antenna and inter-hop interference, and introduce minimal constraints on the radar waveform to facilitate DFRC. We then develop accurate estimation methods for timing offset and channel parameters. These methods are further employed to design reliable demodulation methods. We also derive performance bounds for the proposed estimation methods and embedded communications. Simulation results validate the efficacy of our receiving scheme, showing that the performance of estimators and data communications approaches analytical bounds.

A novel 3-D time-domain terahertz (THz) imaging system based on piecewise constant Doppler (PCD) algorithm and step-frequency continuous-wave (SFCW) signaling is proposed in this article. First, the SFCW THz imaging system configuration and the Gaussian beam propagation model are introduced. Then, the conventional time-domain correlation imaging algorithm is reviewed, and the closed-form expression of its point spread function (PSF) is derived to quantify the range and lateral resolutions. To reduce the computational complexity, a 2-D recursive imaging process based on the plane approximation of the range surface is proposed, by which the original PCD algorithm is extended for 3-D imaging with 2-D aperture synthesis. The 3-D PCD imaging principle, implementation, and complexity analysis are discussed afterward. Finally, simulation and experimental results are provided to validate the theoretical analysis of the 3-D time-domain THz imaging and demonstrate the high quality of the proposed imaging algorithm at a low computational cost.

The performance of transmit beamforming for both optimized precoding and self-interference cancellation (SIC) in full duplex multiple input multiple output (MIMO) transceivers is analysed in this paper. With sub-space dimension larger than that of the null-space of the self-interference channels, the precoding error is reduced but the interference suppression ratio (ISR) is degraded, resulting in a trade-off between multibeam communication and MIMO SIC. An analytical approach for the ISR evaluation is proposed assuming known eigenvalue distribution of the self-interference channels, and a closed-form ISR expression is derived after applying a uniform distribution approximation. The ISR and precoding error trade-off curves are also formulated. Joint SIC by transmit beamforming and beam-based analog adaptive filters over both propagation and analog domains is proposed to achieve better SIC performance and enable more flexible receive antenna selection. Simulation results verify the theoretical analyses.

Joint analog and digital self-interference cancellation (SIC) is essential for enabling in-band full duplex (IBFD) communications. Analog least mean square (ALMS) loop is a promising low-complexity high-performance analog SIC technique with multi-tap adaptive filtering capability, but its properties on the tap coefficient variation have not been fully understood. In this paper, analysis based on higher-order statistics of the transmitted signal is performed to solve the problem of evaluating the variance of the ALMS loop’s weighting coefficient error, which reveals two additional types of irreducible residual self-interference (SI) produced by an ALMS loop if it runs freely. The residual SI channel impulse response in digital baseband is also analysed and its unique properties are investigated. By introducing a simple track and hold control to the ALMS loop’s tap coefficients, a joint analog and digital SIC scheme is proposed to stop the tap coefficient variation and achieve very low residual SI close to the IBFD receiver’s noise floor. In a coordinated application scenario, the noise figure of the digital SIC algorithm is proved to be only 1.76 dB at most. Simulation results are provided to verify the theoretical analyses.

In this paper, the emerging orthogonal time frequency space (OTFS) modulation is firstly restructured as a precoded orthogonal frequency division multiplexing (OFDM) system, so that the well-established frequency-domain approach can be applied to perform signal in fast fading channels. Then a frequency-domain minimum mean squared error (MMSE) equalizer for OTFS is introduced and its performance is analyzed based on the eigenvalue decomposition of the channel matrix. Inspired by the frequency-domain precoding structure, an adaptive transmission scheme with frequency-domain precoding matrix composed of the eigenvectors of the channel matrix is proposed to improve the system performance under MMSE equalization, and its optimized performance is derived with simple expression. Finally, considering two extreme channel conditions, the lower and upper bounds for the diversity performance of the adaptive transmission scheme are derived. Simulation results show that the proposed adaptive transmission achieves significantly better performance for short signal frames and can work well with imperfect channel state information (CSI). The derived performance bounds can serve as benchmarks for OTFS and other precoded OFDM systems.

This paper proposes a low-complexity joint phase noise (PHN) estimation and decoding algorithm for orthogonal frequency division multiplexing relying on index modulation (OFDM-IM) systems. A factor graph (FG) is constructed based on the truncated discrete cosine transform (DCT) expansion model for the variation of PHN. In order to explicitly take into account the structured and sparse a priori information of the frequency-domain symbols provided by the soft-in soft-out (SISO) decoder, the generalized approximate message passing (GAMP) algorithm is employed. Furthermore, to solve the unknown and nonlinear transform matrix problem introduced by the PHN, the mean-field (MF) method is invoked at the observation nodes on the FG. Monte Carlo simulations show the superiority of the proposed algorithm over the existing variational inference (VI) and extended Kalman filter (EKF) methods in terms of their bit error rate (BER) performance and complexity. In addition, we demonstrate that the OFDM-IM scheme outperforms its conventional OFDM counterpart in the presence of PHN.

The sixth generation (6G) mobile systems will enable high mobility applications in both space and ground based networks. In this paper, we investigate low-complexity equalization and adaptive transmission schemes to combat fast fading channels due to high mobility. We first derive signal and channel models in fast fading channels, which allow low complexity minimum mean square error (MMSE) equalization. We then analyze the output signal-to-noise ratio (SNR) using eigenvalue decomposition for a generalized modulation representation. Assuming the channel state information (CSI) is known at the transmitter, we propose an adaptive transmission technique which utilizes the CSI to precode data symbols in order to improve the output SNR at the receiver. Simulation results show that the adaptive transmission scheme effectively improves the MMSE equalization performance in non-line-of-sight channels especially when the transmission signal frame is short.

Radio sensing can be integrated with communication in what the authors call future perceptive mobile networks. Due to the complicated signal structure, it is challenging to estimate sensing parameters such as delay, angle of arrival, and Doppler when joint communication and radar/radio sensing is applied in perceptive mobile networks. Radio sensing with signals compatible with a fifth‐generation (5G) new radio standard using one‐dimension (1D) to 3D compressive sensing (CS) techniques under 5G channel conditions is studied. In the case of 1D–3D CS techniques, they formulate the parameter estimation as a sparse signal recovery problem. These algorithms demonstrate respective advantages, but also show shortcomings in dealing with clustered channels. To effectively exploit the cluster structure in multipath channels, they also propose a 2D cluster Kronecker CS algorithm for significantly improved sensing parameter estimation via introducing a prior probability distribution. Simulation results are provided and they focus the respective advantages and disadvantages of these techniques that validate the effectiveness of the proposed algorithms.

A novel generalized continuous-wave synthetic aperture radar (GCW-SAR) based on deramp-on-receive operating in millimeter-wave frequency is proposed in this article. With deramp-on-receive, the receiver sampling rate is drastically reduced, and the downsampled 1-D raw data can be obtained from the received beat signal. Further adopting piecewise constant Doppler (PCD) imaging in the digital domain, a GCW-SAR image can be easily reconstructed by using the existing frequency-modulated continuous-wave (FMCW) radar system. The effects of deramp-on-receive in PCD imaging are analyzed accordingly. The short wavelength of the millimeter-wave carrier used in the proposed GCW-SAR enables high azimuth resolution as well as a short synthetic aperture, which, in turn, significantly reduces the imaging computational complexity. Simulation and experimental results confirm the advantages of the proposed GCW-SAR.

Self-interference (SI) cancellation for full-duplex (FD) multiple input multiple output (MIMO) systems is challenging due to both hardware and signal processing complexity. In this paper, a beam-based adaptive filter structure with analog least mean square (ALMS) loops is proposed to significantly reduce the complexity of SI cancellation for FD MIMO systems. With this structure, the number of adaptive filters required for SI cancellation scales linearly with the number of transmit beams rather than quadratically with the number of antennas. Furthermore, to avoid additional transmit chains used to up-convert the beam signals to generate reference signals for the ALMS loops, a novel method is proposed to select the optimized reference signals from all transmitted signals. In addition, our stationary analysis shows that the proposed structure for FD MIMO systems outperforms the ALMS loop employed for an FD single input single output system. Simulations are conducted to confirm the theoretical analyses.

Angle-of-arrival (AoA) estimation is a challenging problem for analog antenna arrays. Typical schemes use time-consuming beam scanning, and the resolution is limited to the scanning beam width. In this paper, we propose a virtual-subarray based AoA (ViSA) estimation scheme, which divides an analog array into two virtual subarrays and exploits phase difference between one pair of measurements for AoA estimation. The basic ViSA algorithm can obtain a direct AoA estimate from every two temporal measurements. We propose different subarray constructions which can lead to different accuracy of estimation. We provide closed-form expressions for the statistics of the estimation error. Based on the basic ViSA estimator, we develop two methods to combine multiple pairs of measurements, when they are obtained via sequential and multi-resolution scanning, respectively. Near-optimal estimators are derived for both methods, employing the maximum likelihood principle. Novel techniques are also proposed to address the typical phase ambiguity problem due to the periodic phase function. Simulation results demonstrate that the proposed scheme significantly outperforms existing ones.

The sparse code multiple access (SCMA) is a promising candidate for bandwidth-efficient next generation wireless communications, since it can support more users than the number of resource elements. On the same note, faster-than-Nyquist (FTN) signaling can also be used to improve the spectral efficiency. Hence in this paper, we consider a combined uplink FTN-SCMA system in which the data symbols corresponding to a user are further packed using FTN signaling. As a result, a higher spectral efficiency is achieved at the cost of introducing intentional inter-symbol interference (ISI). To perform joint channel estimation and detection, we design a low complexity iterative receiver based on the factor graph framework. In addition, to reduce the signaling overhead and transmission latency of our SCMA system, we intrinsically amalgamate it with grant-free scheme. Consequently, the active and inactive users should be distinguished. To address this problem, we extend the aforementioned receiver and develop a new algorithm for jointly estimating the channel state information, detecting the user activity and for performs data detection. In order to further reduce the complexity, an energy minimization based approximation is employed for restricting the user state to Gaussian. Finally, a hybrid message passing algorithm is conceived. Our Simulation results show that the FTN-SCMA system relying on the proposed receiver design has a higher throughput than conventional SCMA scheme at a negligible performance loss.

Multibeam technology has recently been proposed for joint communication and radio sensing (JCAS) in millimeter wave systems using analog antenna arrays. Generation of the multibeam satisfying both communication and sensing requirements is yet to be developed. In this paper, we develop closed-form solutions for optimizing the coefficient that combines communication and sensing subbeams to generate a multibeam. Our solutions maximize the received signal power for communication, in the cases (1) without constraint on sensing beamforming (BF) waveform, (2) with minimum BF gain constraints on discrete sensing directions, and (3) with a minimum total power constraint on a range of sensing directions. Simulation results are provided and validate the effectiveness of the proposed solutions.

We propose a novel joint quantization scheme for hybrid antenna array systems using the two-phase-shifter (2-PS) structure, where two phase shifters are combined to represent one beamforming weight. Conventional quantization using a single phase shifter for each beamforming weight cannot represent the magnitude. We propose a new codebook design that combines the two codebooks of the two phase shifters in the recently proposed 2-PS structure. We also study the scaling problem of the beamforming vector and propose a low-complexity searching algorithm for finding a near-optimal scalar based on element-wise quantization. The mean squared quantization error and signal-to-noise ratio (SNR) degradation are derived analytically. Simulation results validate the accuracy of the analytical results and the effectiveness of the proposed quantization methods.

© 2019 IEEE A millimeter wave system with commercially available and affordable data conversion devices is presented in this paper for achieving high-speed and low-cost wireless communications. By adopting the proposed dual pulse shaping (DPS) transmission scheme, the system can achieve full Nyquist rate transmission with only half of the sampling rate required by conventional Nyquist pulse shaping. Structures of the DPS transmitter and receiver are described and effective symbol rate equalization techniques suitable for DPS transmission are presented. Simulation results with two sets of practical dual spectral shaping pulses are also provided to compare system performance with the conventional Nyquist pulse shaping system.

The concept of complementary Nyquist pulse is introduced in this paper. Making use of a half rate Nyquist pulse and its complementary one, a dual pulse shaping transmission scheme is proposed, which achieves full Nyquist rate transmission with only a half of the sampling rate required by conventional Nyquist pulse shaping. This is essential for realizing high-speed digital communication systems with available and affordable data conversion devices. The condition for cross-symbol interference free transmission with the proposed dual pulse shaping is proved in theory, and two classes of ideal complementary Nyquist pulses are formulated assuming raised-cosine pulse shaping. Simulation results are also presented to demonstrate the improved spectral efficiency with dual pulse shaping and compare other system performance against conventional Nyquist pulse shaping.

With balanced system performance, implementation complexity and hardware cost, hybrid antenna array is regarded as an enabling technology for massive multiple-input and multiple-output communication systems in millimeter wave (mmWave) frequencies. Angle-of-arrival (AoA) estimation using a localized hybrid array faces the challenges of the phase ambiguity problem due to its localized nature of array structure and susceptibility to noises. This paper discusses AoA estimation in an mmWave system employing dual-polarized antennas. We propose an enhanced AoA estimation algorithm using a localized hybrid dual-polarized array for a polarized mmWave signal. First, the use of dual-polarized arrays effectively strengthens the calibration of differential signals and resulting signal-to-noise ratio with coherent polarization combining, leading to an enhanced estimate of the phase offset between adjacent subarrays. Second, given the phase offset, an initial AoA estimate can be obtained, which is used to update the phase offset. By employing the updated one, the AoA is re- estimated with improved accuracy. The closed-form mean square error (MSE) lower bounds of AoA estimation are derived and compared with simulated MSEs. The simulation results show that the proposed algorithm in combination with hybrid dual- polarized arrays significantly improves the estimation accuracy compared with the state of the art.

Angle-of-arrival (AoA) estimation is a challenging problem for analog antenna arrays. Typical algorithms use beam scanning and sweeping, which can be time-consuming, and the resolution is limited to the scanning step. In this paper, we propose a virtual-subarray based AoA estimation scheme, which divides an analog array into two virtual subarrays and can obtain a direct AoA estimate from every two temporal measurements. We propose different subarray constructions which lead to different range and accuracy of estimation. We provide detailed beamforming vector designs for these constructions and provide a performance lower bound for the estimator. We also present how to apply the estimator to AoA acquisition and tracking. Simulation results demonstrate that the proposed scheme significantly outperforms existing ones when the signal-to-noise ratio is not very low.

Analog least mean square (ALMS) loop is a promising method to cancel self-interference (SI) in in-band full-duplex (IBFD) systems. In this paper, the steady state analyses of the residual SI powers in both analog and digital domains are firstly derived. The eigenvalue decomposition is then utilized to investigate the frequency domain characteristics of the ALMS loop. Our frequency domain analyses prove that the ALMS loop has an effect of amplifying the frequency components of the residual SI at the edges of the signal spectrum in the analog domain. However, the matched filter in the receiver chain will reduce this effect, resulting in a significant improvement of the interference suppression ratio (ISR). It means that the SI will be significantly suppressed in the digital domain before information data detection. This paper also derives the lower bounds of ISRs given by the ALMS loop in both analog and digital domains. These lower bounds are joint effects of the loop gain, tap delay, number of taps, and transmitted signal properties. The discovered relationship among these parameters allows the flexibility in choosing appropriate parameters when designing the IBFD systems under given constraints.

In this paper, we study the low complexity reception of multiuser signals in uplink millimeter wave (mmWave) communications using a partially connected hybrid antenna array. Exploiting the mmWave channel property, we propose a low-complexity user-directed multiuser receiver with three novel schemes for allocating subarrays to users. This receiver only requires the knowledge of angles-of-arrival (AoAs) for dominating paths and a small amount of equivalent channel information instead of perfect channel state information. For comparison, we also derive a successive interference cancellation-based solution as a performance benchmark. We design two types of reference signals with the channel estimation method to enable efficient and simple estimation for AoA and equivalent baseband channel. Also, we provide analytical results for the performance of the AoA estimation, using the lower bounds of mean square errors in line-of-sight dominated mmWave channels. The simulation results validate that the proposed channel estimation method is effective when employed in combination with a zero-forcing equalizer.

Joint communication and radio sensing (JCAS) in millimeter-wave (mmWave) systems requires the use of a steerable beam. For analog antenna arrays, a single beam is typically used, which limits the sensing area within the direction of the communication. Multibeam technology can overcome this limitation by separately generating package-level direction-varying sensing subbeams and fixed communication subbeams and then combine them coherently. In this paper, we investigate the optimal combination of the two subbeams and the quantization of the beamforming (BF) vector that generates the combined beam. When either the full channel matrix or only the angle of departure (AoD) of the dominating line-of-sight (LOS) path is known at the transmitter, we derive the closed-form expressions for the optimal combining coefficients that maximize the received communication signal power. For the quantization of the BF vector, we focus on the two-phase-shifter array where two phase shifters are used to represent each BF weight. We propose novel joint quantization methods by combining the codebooks of the two phase shifters. The mean squared quantization error is derived for various quantization methods. Extensive simulation results validate the accuracy of the analytical results and the effectiveness of the proposed multibeam optimization and joint quantization methods.

Due to the limited dynamic range of the off-the-shelf electrical and optical components, deliberate digital clipping (DDC) is widely applied to optical orthogonal frequency division multiplexing (OFDM) based visible light communication systems. In this paper, we present a theoretical characterization of the layered asymmetrically clipped optical OFDM (ACO-OFDM) signals subject to peak clipping. We decouple a clipped L -layer ACO-OFDM symbol to L single-layer ACO-OFDM symbols, each corresponding to a layer, and show that these symbols are subject to symmetrical peak clippings at random levels. Using Bussgang's theorem, the resulting attenuation factors and variances of the additive noise associated with each layer are derived. It is shown that the clipping noise caused by the DDC mainly falls onto the first layer, and its impact is gradually reduced in the subsequent layers. In order to combat the clipping noise, a novel receiver based on decision aided reconstruction is proposed. Simulation results show that the proposed receiver can effectively mitigate the clipping noise, leading to significant improvement of bit error rates over the conventional receiver.

Passive localization based on time of arrival (TOA) measurements is investigated, where the transmitted signal is reflected by a passive target and then received at several distributed receivers. After collecting all measurements at receivers, we can determine the target location. The aim of this paper is to provide a unified factor graph-based framework for passive localization in wireless sensor networks based on TOA measurements. Relying on the linearization of range measurements, we construct a Forney-style factor graph model and conceive the corresponding Gaussian message passing algorithm to obtain the target location. It is shown that the factor graph can be readily modified for handling challenging scenarios such as uncertain receiver positions and link failures. Moreover, a distributed localization method based on consensus-aided operation is proposed for a large-scale resource constrained network operating without a fusion center. Furthermore, we derive the Cramér-Rao bound (CRB) to evaluate the performance of the proposed algorithm. Our simulation results verify the efficiency of the proposed unified approach and of its distributed implementation.

Automated individual tree crown detection and delineation (ITCD) is essential for forest mapping, sustainable urban planning and 3D city model. In this paper, ITCD using high-resolution optical Worldview-2 satellite imagery over Singapore is presented. The object-based multiresolution approach for tree mapping including tree positions, crown sizes and canopy gaps is described. Accuracy assessment is performed with ground truth data.

The superiority of exploring millimeter wave (mmWave) frequencies for future wireless communication systems has pushed forward the development of large-scale antenna arrays for achieving sufficient array gain and high spectral efficiency. In this paper, we study the matrix normalization (MN) based zero-forcing (ZF) hybrid precoding in multi-user multi-input-multi-output (MU-MIMO) mmWave systems. We derive the upper bounds of the achievable rate for two representative hybrid array structures, i.e., fully-connected structure and partially-connected structure. Analytical and simulation results validate the tightness of the proposed performance upper bounds for both hybrid structures using massive array, and provide a comparison of the achievable rate using MN and vector normalization (VN).

Generalized continuous wave synthetic aperture radar (GCW-SAR) is a promising new imaging radar system since it applies the full-duplex (FD) transmission technique to achieve continuous signaling in order to overcome several fundamental limitations of the conventional pulsed SARs. As in any FD wireless communication system, self-interference (SI) is also a key problem which can impact on the GCW-SAR system. In this paper, the analog least mean square (ALMS) loop in the radio frequency domain is adopted to cancel the SI for a GCW-SAR system with periodic chirp signaling. The average residual SI power after the ALMS loop is analyzed theoretically by a stationary analysis. It is found that the ALMS loop not only works with random signals in general FD communication systems, but also works well with the periodic signal in GCW-SAR systems. Simulation results show that over 45 dB SI cancellation can be achieved by the ALMS loop which ensures the proper operation of the GCW-SAR system.

This paper considers the issue of passive localization based on time of arrival (TOA) measurement in the presence of receiver detection failures. In passive localization, the signal sent from the transmitter is reflected or relayed by "passive" target and then received at several distributed receivers. The target's position can be determined by collecting range mea- surements from all receivers. With a linearized model for range measurements, we build a factor graph model and implement Gaussian message passing algorithm to obtain target location and detect link failures. The Cramer-rao bound (CRB) is also derived to evaluate the performance of proposed algorithm. Simulation results verify the effectiveness of proposed factor graph approach.

In this paper, fractional reverse polarity optical orthogonal frequency division multiplexing (FRPO-OFDM) is studied to enable dimming compatible visible light communications. The scheme combines a layered asymmetrically clipped optical OFDM (ACO-OFDM) sequence with an information-carrying brightness control sequence (BCS) in the form of M-ary pulse position modulation. We derive the expressions of the FRPO-OFDM signal and its achievable brightness level, and develop an effective detector which can recover information from both sequences based on maximum likelihood detection. We show that when the detector is to be implemented, the use of multi-layer ACO-OFDM imposes strong periodicity on the BCS, which leads to a trade-off between spectral efficiency and brightness resolution for dimming control. It is shown that high spectral efficiency can be achieved with practical dimming requirements. Simulation results show that the extra information carried by the BCS can be decoded with extremely low bit error rate and thus has negligible impacts on the demodulation of the ACO-OFDM signal, when the system nonlinearity is not dominating.

A generalized continuous wave synthetic aperture radar (GCW-SAR) concept is proposed in this paper. By using full-duplex radio frontend and continuous wave signaling, the GCW-SAR system can overcome a number of limitations inherent within the existing SAR systems and achieve high-resolution and wide-swath remote sensing with low-power signal transmission. Unlike the conventional pulsed SAR and the frequency-modulated continuous-wave SAR, the GCW-SAR reconstructs a radar image by directly correlating the received 1-D raw data after self-interference cancellation with predetermined location-dependent reference signals. A fast imaging algorithm, called the piecewise constant Doppler (PCD) algorithm, is also proposed, which produces the radar image recursively in the azimuth direction without any intermediate step, such as range compression and migration compensation, as required by conventional algorithms. By removing the stop-and-go assumption or slow-time sampling in azimuth, the PCD algorithm not only achieves better imaging quality but also allows for more flexible waveform and system designs. Analyses and simulations show that the GCW-SAR tolerates significant self-interference and works well with a large selection of various system parameters. The work presented in this paper establishes a solid theoretical foundation for next-generation imaging radars.

This paper evaluates the performance of an analog least mean square (ALMS) loop employed to cancel self-interference in in-band full-duplex (IBFD) orthogonal frequency division multiplexing (OFDM) systems. Cyclostationary analysis is applied to investigate the behavior of the ALMS filter. It is revealed that the performance of the ALMS filter for OFDM systems primarily depends on windowing function rather than pulse shaping as in single carrier systems. It is also noticed that the ALMS loop in OFDM systems provides a much higher level of sel-interference (SI) suppression because OFDM signals lead to reduced the error of the interference channel modelling with the adaptive filter. Simulations are then conducted to verify the theoretical findings.

Due to the enormous needs for signal processing and hardware constraints, the full digital implementation for a large antenna array at mmWave frequencies becomes intractable. Hence, receiver design for MIMO system with massive hybrid array is very demanding, particularly for subarray structure. In this paper, we propose two low- complexity uplink multiuser receiver design schemes (single-beam and multi-beam) under the circumstances of only users' angles of arrival (AOAs) available at base station, which greatly simplify the analog beamforming structure and reduce the complexity of channel estimation especially when the number of antenna elements is considerably large. In the single-beam scheme, subarrays are mapped to different users one by one such that each subarray serves a specific user. In the multibeam scheme, all subarrays use the same analog beamforming and any subarray's beamforming signal potentially points at all users. Digital beamforming is then employed to combine all subarray signals followed by equalization. Simulations are performed to compare the proposed schemes with other schemes that need channel information available at the subarray output. Since only AOAs are required for analog and digital beamformings, the proposed schemes are more suitable for mmWave MIMO system with massive hybrid array in spite of slight sum-rate loss.

Attention has been devoted to Synthetic Aperture Radar (SAR) for half a century. Though it is a well-proven remote sensing technique, conventional pulsed SAR has several inherent limitations. In this paper, we present a new SAR concept, called Generalized Continuous Wave SAR (GCW-SAR). By using continuous wave signaling, the GCW-SAR system achieves better performance and overcomes the limitations such as the minimum antenna area in conventional SAR. Unlike the frequency modulated continuous wave SAR (FMCW-SAR) system, the GCW-SAR image is reconstructed by correlation between the sampled raw data and the location dependent reference signals. A fast image reconstruction algorithm is also presented in the paper. The principle of GCW-SAR and the effectiveness of the proposed algorithm are validated by numerical simulation results.

In this paper, we study a novel optical orthogonal frequency division multiplexing (OFDM) scheme, fractional reversed polarity optical OFDM (FRPO- OFDM), which enables dimmable visible light communications. The scheme combines an asymmetrically clipped optical OFDM (ACO-OFDM) sequence with an information-carrying brightness control sequence (BCS). We show that the new scheme can create a wide range of brightness levels whilst transmitting extra information using the BCS to enhance the spectral efficiency. The detector which can recover information from both sequences is derived based on maximum likelihood (ML) detection and estimation. It is shown that the information carried by the BCS using variable on-off keying (VOOK) can be detected with extremely low bit error rate (BER) and that the resulting overall BER of FRPO-OFDM is constant over a wide dimming range.

The logically-centralized controllers have largely operated as the coordination points in software-defined networking(SDN), through which applications submit network operations to manage the global network resource. Therefore, the validity of these network operations from SDN applications are critical for the security of SDN. In this paper, we analyze the mechanism that generates network operations in SDN, and present a fine-grained access control model, called Access Control Protector(AC-PROT),that employs an attribute-based signature scheme for network applications. The simulation result demonstrates that AC-PROT can efficiently identify and reject unauthorized network operations generated by applications.

In this paper, we develop a framework for an innovative perceptive mobile (i.e. cellular) network that integrates sensing with communication, and supports new applications widely in transportation, surveillance and environmental sensing. Three types of sensing methods implemented in the base-stations are proposed, using either uplink or downlink multiuser communication signals. The required changes to system hardware and major technical challenges are briefly discussed. We also demonstrate the feasibility of estimating sensing parameters via developing a compressive sensing based scheme and providing simulation results to validate its effectiveness.

Beam-steering has great potentials for joint communications and sensing, which is becoming a demanding feature on many emerging platforms such as unmanned aerial vehicles and smart cars. Although beam-steering has been extensively studied for communications and radar sensing respectively, its application in the joint system is not straightforward due to different beamforming requirements by communications and sensing. In this paper, we propose a low-cost system framework which allows seamless operation of communications and sensing, using two small- size steerable analog antenna arrays. We provide system architecture, high-level protocols, detailed signal model, novel beamforming design and advanced 1D compressive sensing algorithms for joint communications and sensing. We also provide preliminary simulation results which validate the effectiveness of the proposed technique in resolving closely located objects.

The rapid growth of mobile broadband wireless services in recent years demands high speed data transmission for both access and backhaul networks. With the increase of data rate for 5G access to tens of Gigabits per second (Gbps), higher speed transmission for backhaul network is necessary. Current wireless backhaul systems have been able to achieve the data rate of multiple Gbps, but the ability to deal with significant practical impairments such as large carrier frequency offset and IQ mismatch is still a technical challenge. In this paper, a 20 Gbps digital modem for wireless backhaul applications is proposed. Simulation and field programmable gate array implementation show that the the proposed design and signal processing algorithms meet the targeted system performance.

Beamforming design for millimeter-Wave hybrid array with the subarray structure is very challenging. There is neither known optimal solution that maximizes the sum rate capacity nor near-optimal solution. This paper proposes some low-complexity user-directed analog radio- frequency (RF) beamforming design schemes. The basic idea is to iteratively allocate different subarrays to different users such that users' channel correlation can be efficiently reduced via RF beamforming. Several new but less efficient schemes are also presented to shed light on RF beamforming design, and to serve as comparisons for the user-directed schemes. Simulation results are provided for these proposed schemes, existing ones in the literature and an upper-bound for hybird array with a fully-connected structure. The user-directed schemes demonstrate significantly better sum-rate and BER performance over other schemes, although the gap to the upperbound is still large.

In Multi-User Multiple Input Multiple Output (MU-MIMO) Wireless Local Area Networks (WLANs), the optimal-solution such as Dirty Paper Coding (DPC) or the sub-optimal solution Zeroforcing Beamforming (ZFB) with perfect Channel State Information (CSI), is practically limited due to the complexity and the non-availability of perfect CSI at the Access Points (APs)/transmitters. In such a context, ZFB based on channel quantization available at the APs (ZFQ) is the obvious choice for the Multi-User transmission strategy. However, since the quantized CSI is used instead of the perfect CSI at the APs, the quantization error and its impact on the average rate for ZFQ have to be quantified in MU-MIMO WLAN settings. In this paper, we derive a closed-form expression for the upper bound of the channel quantization error and the average rate reduction due to the quantization error with respect to the perfect CSI at the APs. In MU-MIMO WLAN settings, our analytical and numerical studies show that, with an increasing number of antennas at the clients, both the quantization error bound and the average rate reduction increase for ZFQ, in comparison to the ZFB with the perfect CSI.

Compressed sensing based noncoherent UWB systems have been proved to be feasible with a sub-Nyquist sampling rate. As a kind of noncoherent UWB systems, code-shifted differential chaos shift keying (CS- DCSK) UWB system has drawn much attention recently. However, its receiver cannot directly be combined with compressed sensing to reduce the sampling rate. With this motivation, in this paper, we redesign the receiver of the CS-DCSK UWB system and further design two compressed sensing based receivers where the measurement matrix is redesigned. Bit error rate (BER) expression is derived over UWB channel. It is shown that the simulation results are in good agreement with the theoretical ones.

A rotation parameter extraction method based on temporal differencing and image edge detection from range-Doppler images is presented in this letter. The proposed method first detects the motion trail of the moving pixels caused by the rotating parts in temporal differential range-Doppler images using image edge detection. A Doppler-slow-time image is then generated from the edge pixels on the motion trail. Finally, the rotation parameters are extracted from the Doppler-slow-time image. The proposed method is simple, rapid, and practical. Computer simulations and experimental results demonstrate its effectiveness in terms of computation time compared with existing methods.

Frequency-dependent I/Q imbalance estimation and compensation are of significant practical importance to low-cost wideband systems with an I/Q modulation architecture. To enable multichannel transmission without inter-channel interference, transmitter I/Q imbalance must be pre-compensated to meet stringent transmit mask requirement. In this paper, a simple frequency domain joint transmitter and receiver I/Q imbalance estimation method is proposed for self-calibration of such wideband multichannel transceivers. Using two frequency domain training signals and a phase shifter inserted in the transceiver local loopback channel, the transmitter and receiver I/Q imbalances can be estimated separately. The estimation errors are also analyzed and the mean square error lower bounds are derived. Simulation results are in good agreement with analytical ones. Compared with existing methods, the proposed technique demonstrates better image rejection performance and quicker adaptation to parameter changes, making it more applicable to many wireless systems, especially the multichannel microwave backhaul, for achieving high data rates with high-order modulation and wide transmission bandwidth.

Energy efficiency is one of the most critical parameters in ultra-wideband (UWB) based wireless body area networks (WBANs). In this paper, the energy efficiency optimization problem is investigated for cooperative transmission with a single relay in UWB based WBANs. Two practical onbody transmission scenarios are taken into account, namely, along-torso scenario and around-torso scenario. With a proposed single-relay WBAN model, a joint optimal scheme for the energy efficiency optimization is developed, which not only derives the optimal power allocation but also seeks the corresponding optimal relay location for each scenario. Simulation results show that the utilization of a relay node is necessary for the energy efficient transmission in particular for the around-torso scenario and the relay location is an important parameter. With the joint optimal relay location and power allocation, the proposed scheme is able to achieve up to 30 times improvement compared to direct transmission in terms of the energy efficiency when the battery of the sensor node is very limited, which indicates that it is an effective way to prolong the network lifetime in WBANs.

In this paper, we investigate a distributed beamforming problem to optimize energy efficiency (EE) in ultra-wideband (UWB) based implant body area networks (IBANs). To evaluate the impact of relay location on the EE, a relay location based cooperative network model is proposed, where multiple on-body relays are employed to assist an implant node to communicate with a BAN coordinator. With the proposed model, the EE optimization problem is mathematically formulated as a non-convex optimization problem. Sequential quadratic programming (SQP) combined with scatter search are applied to find the corresponding optimal solution. Simulation results illustrate that the proposed beamforming scheme outperforms other transmission schemes. A remarkable improvement can be achieved not only in EE but also in spectral efficiency (SE) compared to direct transmission. Moreover, numerical examples show that the relay location has a significant impact on the EE performance.

In this paper we address the problem of rate scheduling in the Impulse Radio (IR) ultra-wideband (UWB) wireless body area networks (WBANs) and the minimum energy required to stabilize the queuing system. Targeting low complexity WBAN applications, we assume noncoherent receivers based on energy detection and autocorrelation for all nodes. The coordinating node can minimize the average energy consumption of the system and achieve the queue backlog stability of the sensor nodes by controlling the number of pulses per symbol. We first illustrate the necessary and sufficient conditions of network stability for a multi-mode UWB system and then propose a feasible rate scheduling algorithm based on the Lyapunov optimization theory. The scheduling algorithm uses the instantaneous channel state information and the length of the local queue of all sensor nodes and can approach the optimal energy-delay tradeoff of the network. We apply our theoretical framework to the IR-UWB physical layer of the IEEE 802.15.6 standard and extract the optimal physical layer modes that can achieve the desired energy-delay tradeoff.

This paper proposes a comprehensive solution to reduce peak-to-average power ratio (PAPR), cancel out-of-band emission (OOBE), and alleviate the impact of phase noise for precoded orthogonal frequency-division multiplexing (OFDM) systems. Making use of the cancellation and pilot symbols and subcarriers in both data and frequency domains, this solution integrates a number of novel schemes to overcome OFDM's inherent drawbacks and mitigate practical impairments for high speed wireless communications. These schemes include a layered precoding structure, a low complexity OOBE cancellation using both data domain cancellation symbols and frequency domain cancellation subcarriers, and an effective phase noise compensation using data domain pilot symbols. The improved overall system performance of the proposed solution is verified by simulation results.

This paper investigates discrete Fourier Transform (DFT)-precoded OFDM systems (DFT-OFDM) for intensity modulated direct-detection optical communications. Such scheme can be used to support both single and multiple user communications. Two DFT-OFDM systems using real modulation and DC-biasing are proposed. Performance analysis based on signal-to-interference-and-noise ratio (SINR) is provided. Insights are provided for designing choices between different modulations, and between using DC-biasing and asymmetrical clipping approaches. Simulation results show that the proposed schemes largely outperform systems using asymmetrical clipping, particularly in the case of using higher order modulations.

In this paper, spectral efficiency (SE) is investigated for cooperative ultra-wideband (UWB) based on-body area networks (OBANs). To optimize SE for single-relay cooperation, an equivalent generic cooperative model in UWB based OBANs is established first. With the proposed model, joint optimal relay location and power allocation for cooperation is then derived to solve the SE maximization problem. Simulation results show that direct transmission is preferable for UWB based OBANs when the transmitter and receiver are located on the same side of the human body. However, the joint optimal cooperative transmission scheme can achieve a significant improvement on SE compared with direct transmission when the transmitter and receiver are located on the different sides of the human body, which indicates that cooperation is more feasible to be applied in this case due to its robustness to the significant path loss.

Denoising recovery algorithms are very important for the development of compressed sensing (CS) theory and its applications. Considering the noise present in both the original sparse signal x and the compressive measurements y, we propose a novel denoising recovery algorithm, named Regularized Subspace Pursuit (RSP). Firstly, by introducing a data pre-processing operation, the proposed algorithm alleviates the noise-folding effect caused by the noise added to x. Then, the indices of the nonzero elements in x are identified by regularizing the chosen columns of the measurement matrix. Afterwards, the chosen indices are updated by retaining only the largest entries in the Minimum Mean Square Error (MMSE) estimated signal. Simulation results show that, compared with the traditional orthogonal matching pursuit (OMP) algorithm, the proposed RSP algorithm increases the successful recovery rate (and reduces the reconstruction error) by up to 50% and 86% (35% and 65%) in high noise level scenarios and inadequate measurements scenarios, respectively.

For non-contiguous (NC) OFDM based cognitive radio (CR) systems, schemes have been developed in literature to acquire spectrum synchronization information (SSI) with perfect carrier frequency offset (CFO) synchronization. However, OFDM is extremely sensitive to the CFO in practice, which leads to inter-carrier interference (ICI), hence degrading the spectrum synchronization performance for existing schemes. An accurate CFO estimation is therefore required before setting up the SSI. In this paper, we present a novel scheme based on the maximum likelihood (ML) algorithm to estimate the CFO for the NC-OFDM receiver when the SSI is unknown. A corresponding Cramér-Rao lower bound (CRB) with the ideal SSI is derived to demonstrate the efficiency of the proposed scheme. Simulation results show that the proposed scheme is robust against interference and achieves a satisfactory accuracy of estimation, which is close to the relevant CRB.

Recently, the recovery performance of analog Compressed Sensing (CS) has been significantly improved by representing multiband signals with the modulated and merged Slepian basis (MM-Slepian dictionary), which avoids the frequency leakage effect of the Discrete Fourier Transform (DFT) basis. However, the MM-Slepian dictionary has a very large scale and corresponds to a large-scale measurement matrix, which leads to high recovery computational complexity. This paper resolves the above problem by modulating and band-limiting the multiband signal rather than modulating the Slepian basis. Specifically, instead of using the MM-Slepian dictionary to represent the whole multiband signal, we propose to use the non-modulated Slepian basis to represent the modulated and band-limited version of the multiband signal based on the recently proposed Modulated Wideband Converter (MWC). Furthermore, based on the analytical derivation with the non-modulated Slepian basis, we propose an Interpolation Recovery (IR) algorithm to take full advantage of the Slepian basis, whereas the Direct Recovery (DR) algorithm using the Moore-Penrose pseudo-inverse cannot achieve this. Simulation results verify that, with low recovery computational load, the non-modulated Slepian basis combined with the IR algorithm improves the recovery SNR by up to 35 dB compared with the DFT basis in noise-free environment.

Based on the sequential sample rate conversion (SRC) structure using B-spline interpolation for orthogonal frequency division multiplexing (OFDM) based software defined radios, a parallel processing SRC structure is proposed in this paper to achieve high speed data transmission for multiband OFDM systems. By deriving an impulse response matrix from the sequential SRC structure, the state vectors of the SRC structure can be calculated from a block of input samples with less complexity than conventional Farrow structure. Real-time SRC implementation combined with local feedback and stuffing is also presented. Performance in terms of state buffer pointer offset caused by clock variation and finite precision in digital hardware is analyzed to provide guidance for practical system design such as determining clock stability and word-length requirements.

This letter extends our previous work on layered inverse Fast Fourier Transform (IFFT) structure to a multistage layered IFFT structure where data symbols can input at different stages of the IFFT. We first show that part of the IFFT in the transmitter of an OFDM system can be shifted to the receiver, while a conventional one-tap frequency-domain equalizer is still applicable. We then propose two IFFT split schemes based on decimation-in-time and decimation-in-frequency IFFT algorithms to enable interference-free symbol recovery with simple linear equalizers. Applications of the proposed schemes in multiple access communications are investigated. Simulation results demonstrate the effectiveness of the proposed schemes in improving bit-error-rate performance.

An optimal detection method along with two reduced-complexity methods, modified energy detection (MED) and equal gain detection (EGD), under low signal-to-noise ratio (SNR) condition are proposed in this paper for detection of temporally correlated signals over multipath fading channels. By incorporating resolvable multipaths and multiple antennas into system model, these detection methods are derived based on maximum log-likelihood ratio (LLR) test principal and using the same low SNR LLR approximation. Analytical performance expressions for MED and EGD are also given. Simulation results show that, when signal exhibits temporal correlation, the proposed optimal detection and EGD achieve better performance than conventional generalized likelihood ratio test through utilizing multipath propagation. Further, the proposed MED is superior to conventional energy detection if it a priori signal temporal correlation information is exploited. It is also revealed that multipath tap correlation can have either constructive or destructive effect to spectrum sensing. The proposed EGD is proven to be a practical technique for reliable spectrum sensing over multipath fading channels as it approaches optimal performance with low complexity.

Recently, distributed data storage (DDS) for Wireless Sensor Networks (WSNs) has attracted great attention, especially in catastrophic scenarios. Since power consumption is one of the most critical factors that affect the lifetime of WSNs, the energy efficiency of DDS in WSNs is investigated in this paper. Based on Compressed Sensing (CS) and network coding theories, we propose a Compressed Network Coding based Distributed data Storage (CNCDS) scheme by exploiting the correlation of sensor readings. The CNCDS scheme achieves high energy efficiency by reducing the total number of transmissions Nttot and receptions Nrtot during the data dissemination process. Theoretical analysis proves that the CNCDS scheme guarantees good CS recovery performance. In order to theoretically verify the efficiency of the CNCDS scheme, the expressions for Nttotand Nrtotare derived based on random geometric graphs (RGG) theory. Furthermore, based on the derived expressions, an adaptive CNCDS scheme is proposed to further reduce Nttot and Nrtot. Simulation results validate that, compared with the conventional ICStorage scheme, the proposed CNCDS scheme reduces Nttot, Nrtot, and the CS recovery mean squared error (MSE) by up to 55%, 74%, and 76% respectively. In addition, compared with the CNCDS scheme, the adaptive CNCDS scheme further reduces Nttotand Nrtotby up to 63% and 32% respectively.

This paper presents a novel downlink resource allocation scheme for OFDMA-based next generation wireless networks subject to inter-cell interference (ICI). The scheme consists of radio resource and power allocations, which are implemented separately. Low-complexity heuristic algorithms are first proposed to achieve the radio resource allocation, where graph-based framework and fine physical resource block (PRB) assignment are performed to mitigate major ICI and hence improve the network performance. Given the solution of radio resource allocation, a novel distributed power allocation is then performed to optimize the performance of cell-edge users under the condition that desirable performance for cell-center users must be maintained. The power optimization is formulated as an iterative barrier-constrained water-filling problem and solved by using the Lagrange method. Simulation results indicate that our proposed scheme can achieve significantly balanced performance improvement between cell-edge and cell-center users in multi-cell networks compared with other schemes, and therefore realize the goal of future wireless networks in terms of providing high performance to anyone from anywhere.

Channel matrix inversion, which requires significant hardware resource and computational power, is a very challenging problem in MIMO-OFDM systems. Casting the frequency-domain channel matrix into a polynomial matrix, interpolation-based matrix inversion provides a promising solution to this problem. In this paper, we propose novel algorithms for interpolation based matrix inversion, which require little prior information of the channel matrix and enable the use of simple low-complexity interpolators such as spline and low pass filter interpolators. By invoking the central limit theorem, we show that a Gaussian approximation function well characterizes the power of the polynomial coefficients. Some low-complexity and efficient schemes are then proposed to estimate the parameters of the Gaussian function. With these estimated parameters, we introduce phase shifted interpolation and propose two algorithms which can achieve good interpolation accuracy using general low-complexity interpolators. Simulation results show that up to 85% complexity saving can be achieved with small performance degradation.

Analog Compressed Sensing (CS) has attracted considerable research interest in sampling area. One of the promising analog CS technique is the recently proposed Modulated Wideband Converter (MWC). However, MWC has a very high hardware complexity due to its parallel structure. To reduce the hardware complexity of MWC, this paper proposes a novel Random Circulant Orthogonal Matrix based Analog Compressed Sensing (RCOM-ACS) scheme. By circularly shifting the periodic mixing function, the RCOM-ACS scheme reduces the number of physical parallel channels from m to 1 at the cost of longer processing time, where m is in the order of several dozen to several hundred in MWC. It is proved that the m×M measurement matrix of RCOM-ACS scheme satisfies the Restricted Isometry Property (RIP) condition with probability 1-M-O(1)when m = O(rlog2Mlog3r), where M is the length of the periodic mixing function, r denotes the sparsity of the input signal. Furthermore, to make a good tradeoff between processing time and hardware complexity, a short processing time RCOM-ACS scheme is proposed in this paper. Simulation results show that, the proposed schemes outperform MWC in terms of recovery performance.

Compressed sensing (CS) has recently emerged as a powerful signal acquisition paradigm. CS enables the recovery of high-dimensional sparse signals from much fewer samples than usually required. Further, quite a few recent channel measurement experiments show that many wireless channels also tend to exhibit sparsity. In this case, CS theory can be applicable to sparse channel estimation and its effectiveness has been validated in point-to-point (P2P) communication. In this work, we study sparse channel estimation for two-way relay networks (TWRN). Unlike P2P systems, applying CS theory to sparse channel estimation in TWRN is much more challenging. One issue is that the equivalent channels (terminal-relay-terminal) may be no longer sparse due to the linear convolutional operation. On this basis, novel schemes are proposed to solve this problem and effectively improve the accuracy of TWRN channel estimation when using CS theory. Extensive numerical results are provided to corroborate the proposed studies.

Wireless propagation phenomena including multipath pose significant challenges to reliable spectrum sensing which is a fundamental requirement for dynamic spectrum access and system coexistence. In this paper, an optimal detection technique along with two reduced-complexity alternatives, modified energy detection (MED) and equal gain detection (EGD), are proposed to improve the detection probability for spectrum sensing over severe multipath channels. By incorporating the resolvable multipaths and multiple receiving antennas into the system model and assuming the availability of a priori temporal correlation about the source signal, these detection methods are derived based on maximum log-likelihood ratio test under low signal-to-noise ratio condition. Simulation results show that the proposed optimal detection outperforms the conventional generalized likelihood ratio test in a multipath environment either with or without a priori information. The proposed MED significantly improves the performance of conventional energy detection after a priori information is exploited. Finally, the proposed EGD performs better than MED and approaches the optimal detection as the number of multipaths increases.

A low-complexity and efficient sidelobe suppression with orthogonal projection (SSOP) scheme is proposed in [1] for OFDM systems. This paper provides comprehensive performance analysis for the zero-forcing receiver for the SSOP scheme. Via rigorous proof, we show the independence of the orthogonal projection matrix on the ordering of the suppression distances, and the monotonicity of the SNR with the suppression distance and the number of reserved subcarriers. We also characterized the SNR degradation of the single-side and double-side suppression schemes analytically. These analytical results match with the numerical results well.

Channel matrix inversion, which requires significant hardware resource and computational power, is a very challenging problem in MIMO-OFDM systems. Casting the frequency-domain channel matrix into a polynomial matrix, interpolation-based matrix inversion provides a promising solution to this problem. In this paper, by showing that the polynomial coefficients can be well approximated by a Gaussian function, we propose an efficient algorithm, which relaxes the requirement for knowing the maximum multipath delay spread and enables the use of simple low-complexity interpolators by introducing a phase shift term to the signal to be interpolated. Simulation results show that significant complexity saving can be achieved with little equalization performance degradation.

Reliable spectrum sensing should be able to operate under realistic wireless environments such as multipath and fading. Based on the optimal spectrum sensing with multiple receiver antennas over multipath channels, this paper presents further studies into two more practical detection methods, the modified energy detection (MED) and the equal gain detection (EGD), over frequency-selective fading channels, with focus on the impact of multipath tap correlation on the sensing performance. Both simulation and analytical results are provided. It is verified that utilizing multipath propagation enhances the detection probability of the EGD, which approaches that of the optimal detection. The EGD also demonstrates better performance than the MED and the conventional generalized likelihood ratio test. The tap correlation can have either constructive or destructive effect to the spectrum sensing system depending on how well the tap correlation matches the source signal's temporal correlation, whereas the spatial correlation always degrades the detection performance.

In this paper we propose a novel resource allocation scheme to achieve a balanced performance improvement for all users in a LTE network subject to inter-cell interference. In the proposed scheme the resource allocation process is implemented in two steps. In the first step interference coordination and scheduling are first conducted in a global manner to prevent cell-edge users from mutual interference. In the second step, optimal power allocation is conducted to maximize performance of cell-edge users while maintaining high performance of cell-center users. The optimal power allocation problem is solved using the Lagrange decomposition method. Simulation results show that our proposed scheme can significantly improve performance for all users in a multi-cell network and achieve a better performance balance between cell-edge and cell-center users.

This paper proposes arbitrary ratio sample rate conversion (SRC) architectures and a simpler B-spline interpolation algorithm for orthogonal frequency division multiplexing (OFDM) based software defined radios (SDRs) with multiband and multi-channel capabilities. Different from conventional standalone digital front-end designs for SDRs, the proposed SRC architectures combine the B-spline interpolation with OFDM modulation and equalization for OFDM transmitter and receiver respectively. With this combined design, the passband droop introduced by the B-spline interpolation can be more efficiently compensated using frequency-domain pre-distortion, instead of conventional time-domain pre-filtering, and hence an overall system complexity reduction is achieved. A novel multi-period B-spline interpolation and re-sampling structure is then constructed, and an interpolation algorithm with lower implementation complexity than that of the conventional Farrow structure is further developed. The SRC performance is also analysed by deriving the signal-to-peak distortion ratio formulas which can be used as design tools for determining the required orders of B-splines in the OFDM transmitter and receiver respectively. Finally, SRC examples used in a high-speed multiband multi-channel microwave backhaul system are given and compared with conventional polyphase filterbank interpolation to demonstrate the practicality and performance of the proposed SRC architectures and interpolation algorithm.

Sidelobe suppression, or out-of-band emission reduction, in multicarrier systems is conventionally achieved via time-domain windowing which is spectrum inefficient. Although some sidelobe cancellation and signal predistortion techniques have been proposed for spectrum shaping, they are generally not well balanced between complexity and suppression performance. In this paper, an efficient and low-complexity sidelobe suppression with orthogonal projection (SSOP) scheme is proposed. The SSOP scheme uses an orthogonal projection matrix for sidelobe suppression, and adopts as few as one reserved subcarrier for recovering the distorted signal in the receiver. Unlike most known approaches, the SSOP scheme requires multiplications as few as the number of subcarriers in the band, and enables straightforward selection of parameters. Analytical and simulation results show that more than 50dB sidelobe suppression can be readily achieved with only a slight degradation in receiver performance.

Two novel differential normalization factors, depending on the severity of carrier frequency offset, are proposed for autocorrelation based coarse timing scheme. Compared with the conventional normalization factor based on signal energy, they improve the robustness of the timing metric to signal-to-noise ratio (SNR), improve the mainlobe sharpness of the timing metric and reduce both missed detection and false alarm probabilities.

High speed long range millimetre-wave (mm-wave) links can be achieved by using wideband hybrid antenna arrays of sub-arrays. However, conventional wideband angle-of-arrival (AoA) estimation and beamforming algorithms are not applicable to the wideband hybrid arrays due to the array architecture difference. In this paper, an adaptive frequency-domain AoA estimation and beamforming algorithm suitable for practical wideband hybrid array of side-by-side sub-arrays is proposed. Mean square error bounds under simplified array configuration and extreme array imperfection condition are also given. Simulation results show that the proposed algorithm is robust with low complexity and fast convergence.

The decode-and-forward relay technique has been introduced in next generation wireless networks (such as LTE) to extend coverage and improve performance, although it may generate additional inter-cell interference. Soft frequency reuse (SFR) has been proposed as the most promising frequency planning strategy to mitigate inter-cell interference in LTE systems. In this paper we propose an effective combination of relay networks and SFR, with a dedicated relay topology and the SFR-based resource allocation scheme. In the proposed relay network, each relay station (RS) can jointly serve cell-edge users from adjacent cells to increase efficiency. The proposed resource allocation scheme, on the other hand, is able to achieve throughput improvement for both cell-edge users and cell-center users by minimizing the interference impact in the system. The benefit of relay networks with SFR-based resource allocation in terms of 30% overall performance improvement over conventional non-relay networks can be realized as demonstrated by the simulation results.

This paper proposes a novel load distribution aware soft frequency reuse (LDA-SFR) scheme for inter-cell interference mitigation and performance optimization in next generation wireless networks. Our proposed scheme aims to provide a solution to effectively achieve inter-cell interference mitigation while maintaining high spectrum efficiency to all users in the cell. The proposed scheme consists of two novel algorithms: edge bandwidth reuse and centre bandwidth compensation. Using the edge bandwidth reuse algorithm, cell-edge users can take advantage of uneven traffic load and user distributions within each cell to expand their resource allocations. The center bandwidth compensation algorithm, on the other hand, provides a protection mechanism for cell-center users to avoid exhaustive edge bandwidth extension. Applying LDA-SFR to an LTE network and comparing its performance against that of existing soft frequency reuse (SFR) and adaptive soft frequency reuse (ASFR) schemes indicates that LDA-SFR is superior as it achieves fairness between cell-edge users and cell-center users in terms of average throughput improvement.

An efficient hardware-optimized Physical Random Access Channel (PRACH) baseband signal generation algorithm and its ASIC implementation in the LTE user equipment (UE) transmitter are presented in this paper. A simplified DFT of the Zadoff-Chu (ZC) sequence as well as a phase computation are applied to the prime size DFT of the PRACH preamble and the large size IDFT is accomplished by groups of smaller size IFFTs. The optimized algorithm achieves significantly lower computational complexity compared with the original algorithm in the LTE specification and better performance compared to another publication. The ASIC architecture is also designed to reduce the memory size and logic complexity, which achieves a low hardware cost in terms of the cell area. The proposed design was implemented in 65nm CMOS and it was demonstrated that this design can satisfy the timing requirements of the LTE specification.

Coexistence of multiple wireless body area networks (WBAN) is a very challenging problem because piconets move frequently and each piconet can have hundreds of sensors. The IEEE 802.15.6 task group is developing a standard based on superframe-level frequency-hopping scheme, which is a good solution to the piconet coexistence problem without requiring coordination between piconets. However, its spectrum efficiency is very low when only a single piconet is operating. In this paper we propose a superframe-level time-hopping scheme with variable contention access period. Compared to the frequency-hopping scheme, the proposed scheme has similar interference mitigation capability, but can achieve significant improvement in energy consumption, latency and spectrum efficiency.

A solution to the power leakage minimization problem in discrete Fourier transform (DFT) based communication systems is presented. In a conventional DFT based system, modulated subcarriers exhibit high sidelobe levels, which leads to significant out-of-band power leakage. Existing techniques found in the literature either do not achieve sufficient sidelobe suppression or suffer from significant spectral efficiency loss. Precoding can be seen as a general linear processing method for power leakage reduction, however, how to design the optimal linear precoder is still an open problem. In this paper, the power leakage suppression is first treated as a matrix Frobenius norm minimization problem, and then the optimal orthogonal precoding matrix design for the power leakage suppression is proposed based on singular value decomposition (SVD). By further exploiting the extra degrees of freedom in the precoding matrix, two kinds of optimized precoding matrices, one with multi-carrier property and the other with single-carrier property, are developed to take the advantages of orthogonal frequency division multiplexing (OFDM) and single carrier frequency division multiple access (SC-FDMA), respectively. Simulation results show that both the multi-carrier and the single-carrier precoding schemes achieve significant power leakage suppression, and have similar peak-to-average power ratio (PAPR) and bit-error-rate (BER) to those of OFDM and SC-FDMA systems, respectively.

High speed long range millimetre-wave (mm-wave) links can be achieved by using wideband hybrid antenna arrays of sub-arrays. Due to the array architecture difference, conventional wideband angle-of-arrival (AoA) estimation and beamforming techniques are not applicable to such wideband hybrid arrays. Targeted at point-to-point line-of-sight wireless transmission in the 70/80 GHz E bands, a unified frequency-domain AoA estimation and beamforming algorithm suitable for large scale wideband hybrid arrays of both interleaved and side-by-side sub-arrays is proposed in this paper. The AoA estimation performance is analyzed by deriving a recursive modified Cramér-Rao bound (MCRB). The effect of mutual coupling among antenna elements on the estimation performance is also considered for the hybrid array of side-by-side sub-arrays. The analytical results can be used to determine system parameters according to required system specifications. Simulation results show that the proposed AoA estimation algorithm is robust against practical impairments, and the frequency dependency of the array pattern is significantly reduced after digital beamforming. Simulated mean square errors of AoA estimation are also compared with the analytical bounds, showing that the derived recursive MCRB provides a meaningful indication to the AoA estimation performance.

This paper presents a joint channel and mutual coupling estimation technique for wideband antenna array to achieve high speed wireless communications in the millimetre-wave frequency bands. The estimated channel frequency responses and mutual coupling matrix can be used to digitally calibrate a wideband antenna array in the frequency-domain, followed by digital beamforming. Experiments are carried out using a four-element receive array prototype in the E-band (71-76 GHz) to demonstrate the frequency-domain digital calibration and beamforming performance. The results show that both the mutual coupling and wideband effects are effectively mitigated by the proposed technique and a 11.5 dBi array gain is achieved which is very close to that of an ideal four-element antenna array.

In this paper, a novel call admission control (CAC) scheme for multicast and unicast integrated services is proposed, which optimizes service provision capacity for both services. A resource sharing model is presented in which multiple classes services are dynamically admitted into the system. Several basic CAC rules for the above resource model are proposed first and improved mechanisms are investigated to further increase system performance. Subsequently, the call level QoS and system performance of the resulting CAC scheme are evaluated. Numeric results show that the proposed scheme can achieve optimal multiclass service performance while satisfying QoS constraints.

A novel combination of block spread orthogonal frequency division multiple access (BS-OFDMA) with space-time coded multiple input multiple output (STC MIMO) scheme is proposed for broadband wireless access uplink transmission. Using complex exponential spreading sequences, the block spreading technique can efficiently generate precoded OFDMA signal to exploit frequency diversity. An Alamouti STC MIMO encoding technique is incorporated with the block spreading to achieve further spatial diversity. The performance of the proposed STC-BS-OFDMA system using minimum mean squared error equalization is analyzed, and a closed-form asymptotical bit error rate expression is derived. Simulation results are also given to demonstrate the improved diversity performance as compared with other OFDMA schemes. The proposed techniques are well suited for future broadband wireless access systems such as 3G LTE and 4G.

We consider the robust linear precoding (LP) and Tomlinson-Harashima precoding (THP) schemes for multiuser MIMO-OFDM downlink channels with limited feedback. Benefiting from the correlation of spatial channels, the mobile terminal compresses and feeds back the time-domain channel vectors instead of the corresponding frequency-domain vectors to substantially reduce the feedback signalling overhead. A compression and restoration method and a codebook design for channel state information at the transmitter (CSIT) feedback are proposed in the time domain. By treating the partial CSIT as a random quantity, we develop the robust precoders to combat the truncation and quantization errors introduced in the feedback procedure. In comparison with the non-robust designs, both the robust LP and THP have better bit-error rate performance especially in high signal-to-noise ratio region.

The power allocation problem is addressed for time division duplex (TDD) LTE-A uplink systems in this paper. Due to the IDFT de-spreading in LTE-A uplink, the channel frequency responses in an IDFT de-spreading block will be tangled together. After analyzing the equivalent signal to interference plus noise ratio (SINR) in the time domain, a Truncated Squared norm of channel equalization Coefficients based Power Allocation (TSCPA) method is proposed to improve the final SINR performance after the IDFT de-spreading block. The proposed TSC-PA algorithm is verified for the clustered DFT-s-OFDM system in eigen-model block diagonalization multi-user MIMO uplink environment by simulations. The results demonstrate that the proposed TSC-PA algorithm can further improve the system block error rate (BLER) performance by selecting a proper truncation threshold.

Owing to the excessive demand on signal processing and space constraint, a full digital implementation of a large adaptive antenna array at millimeter wave frequencies is very challenging. Targeted at long range high data rate point-to-point link in the 70/80 GHz bands, a novel hybrid adaptive antenna array which consists of analogue subarrays followed by a digital beamformer is presented in this paper to overcome the digital implementation difficulty. Two subarray configurations, the interleaved subarray and the side-by-side subarray, are proposed, and two Doppler resilient adaptive angle-of-arrival estimation and beamforming algorithms, the differential beam tracking (DBT) and the differential beam search (DBS), are developed. Simulation results on the DBT and DBS performance are provided using a 64 element hybrid planar array of four 4 by 4 element subarrays with the two subarray configurations, respectively. Recursive mean square error (MSE) bounds of the developed algorithms are also analyzed and compared with simulated MSEs.

The mean squared error (MSE) is commonly used to measure and compare the performance of various phase estimation techniques in communications and signal processing systems. When the received signal contains recursive nuisance parameters, the MSE is extremely difficult to obtain and even the conventional modified Cramer-Rao bound (MCRB) can not be readily applied. In this paper, a recursive MSE bound and its simplified calculation method are proposed to solve the problem. As an application example, an adaptive hybrid antenna array and its associated angle-of-arrival (AoA) estimation technique are presented. The MSE of the AoA estimation is simulated and compared with the recursive MSE bound and MCRB. The results show that the proposed recursive MSE bound provides a tighter lower MSE bound than the recursive MCRB.

A new type of hybrid antenna array consisting of analogue subarrays followed by a digital beamformer is proposed for practical implementation of long range high data rate millimetre wave communications systems. An adaptive algorithm, referred to as the differential beam search (DBS), is proposed for the angle of arrival (AoA) estimation to control the phase shifters in the analogue subarrays and to perform digital beamforming. This algorithm does not need the knowledge of a reference signal and effectively solves the phase ambiguity problem in AoA estimation inherent to the practical subarray configuration. The performance of the proposed DBS algorithms is demonstrated by simulations.

This paper proposes a parallel packet transmission (PPT) scheme based on orthogonal frequency division multiplexing (OFDM). The principle of the PPT scheme is to divide a packet into a number of smaller parallel packets, and transmit each smaller packet over an individual subcarrier of the OFDM symbols instead of spreading the data bits in a packet across a number of different subcarriers. It is proved theoretically that the proposed PPT scheme has higher average throughput than the conventional serial packet transmission without preceding. Furthermore, simulation results show that the OFDM system with PPT outperforms the preceded OFDM system with minimum mean squared error equalization in both uncoded and coded cases in terms of average throughput. The PPT scheme provides an alternative and simpler means to combat frequency-selective fading.

A new frequency and space preceding scheme for multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems is presented. For frequency preceding, the data symbols to be transmitted are divided into multiple substreams, and a predefined unitary matrix is applied to each substream to obtain different linear combinations of data symbols in the substream to gain frequency diversity. For space preceding, different preceding matrices selected from a predefined orthogonal matrix are used to allocate each frequency precoded data symbol to all transmit antennas to gain spatial diversity. The number of substreams and the corresponding data symbol mapping scheme are also adaptively determined at the receiver under varying received signal strength and MIMO channel conditions, and are made available to the transmitter through a low-rate feedback channel. Simulation results show that the proposed MIMO OFDM system with adaptive substream selection can effectively exploit both frequency and spatial diversity, and deliver the maximum system throughput.

This paper settles a controversy over the multipath diversity performance of the precoded orthogonal frequency division multiplexing system with the linear equalization. Through the asymptotical analysis of the bit error rates with extreme system parameters, a comprehensive understanding of the linear equalization's behavior in the frequency-selective multipath fading channels is gained. Compared with the optimum maximum-likelihood detection, the diversity performance of the linear equalization can be well described by an asymptotical signal-to-noise ratio (SNR) degradation, which reveals that the linear equalization can achieve the maximum multipath diversity within an operational SNR range but will lose diversity advantage as SNR increases.

Cooperative Multi-In Multi-Out (MIMO) schemes can reduce both transmission energy and latency in distributed wireless sensor networks (WSNs). When circuit energy is considered in such networks, the total energy consumed as the number of cooperating nodes increases becomes of particular interest. In addition, most of the previous works focused only on Space-Time-Block-Code (STBC) schemes and ignore other MIMO schemes. In this paper we present a comparison study of three cooperative MIMO schemes: Beamforming (BF), STBC and Spatial Multiplexing (SM) where both the transmission and circuit energies are considered. We consider a wireless sensor network operating in quasi-static Rayleigh fading channels with M cooperating transmit nodes and N cooperating receive nodes. We show that the Single-In-Single-Out (SISO) scheme is more energy-efficient and has lower packet latency at higher regions of transmission power while the three cooperative MIMO schemes are more energy-efficient and outperform the SISO scheme at the lower regions. From our analysis, we can conclude that, Beamforming outperforms both the SM and STBC schemes in term of energy-efficiency and lower packet latency. Also we suggest that the Beamforming scheme utilising two transmit nodes results in an efficient cooperative system.

This paper presents a semi-automated method for 3D building reconstruction and height measurement from a single very high resolution satellite image by using the building top, building base and/or building shadow information. An interactive software system, complete with editing and visualization features has been implemented.

This paper presents an overview of the design of the system for interactive 3-D visualization of the city model. It uses high resolution images of IKONOS satellite and corresponding camera model of Rational Polynomial Coefficients (RPC) for building texture mapping and orthorectified images for ground texture mapping. The level of detail for both terrain and texture is applied, and 2D virtual memory management system is implemented for efficient visualization.

In this paper, we expand the idea of spreading the transmitted symbols in OFDM systems by unitary spreading matrices based on the rotated Hadamard or rotated Discrete Fourier Transform (DFT) matrices proposed in the literature to apply to Space-Time Coded Multiple-Input Multiple- Output OFDM (STC-MIMO-OFDM) systems. We refer the resulting systems to as STC-MIMO Block Spread OFDM (STC-MIMO-BOFDM) systems. In the proposed systems, a multi-dimensional diversity, including time, frequency, space and modulation diversities, can be used, resulting in better bit error performance in frequency selective Rayleigh fading channels compared to the conventional OFDM systems with or without STCs. Simulations carried out with the Alamouti code confirm the advantage of the proposed STC-MIMO-BOFDM systems.

The performance of impulse-train-modulated ultra-wideband (UWB) systems for the ideal additive white Gaussian noise channel is analyzed in this letter. The derived formulae are also used to optimize the modulation parameter of a Gaussian monocycle UWB impulse radio

Based on a switched linear modulation model recently developed for continuous-phase modulated (CPM) signal representation and approximation, and incorporated with new phase state symbol definitions, three simple CPM receivers are proposed in this letter. Their performance simulation results and complexity comparison are given using a quaternary 2RC (raised cosine frequency pulse) CPM scheme.

The optimal linear modulation approximation of any M-ary continuous-phase modulated (CPM) signal under the minimum mean-square error (MMSE) criterion is presented in this paper. With the introduction of the MMSE signal component, an M-ary CPM signal is exactly represented as the superposition of a finite number of MMSE incremental pulses, resulting in the novel switched linear modulation CPM signal models. Then, the MMSE incremental pulse is further decomposed into a finite number of MMSE pulse-amplitude modulated (PAM) pulses, so that an M-ary CPM signal is alternatively expressed as the superposition of a finite number of MMSE PAM components, similar to the Laurent representation. Advantageously, these MMSE PAM components are mutually independent for any modulation index. The optimal CPM signal approximation using lower order MMSE incremental pulses, or alternatively, using a small number of MMSE PAM pulses, is also made possible, since the approximation error is minimized in the MMSE sense. Finally, examples of the MMSE-optimal CPM signal approximation and its comparison with the Laurent approximation approach are given using raised-cosine frequency-pulse CPM schemes.

An automatic process for registering the panchromatic and multispectral SPOT5 imagery is presented. The registration process make used of edges and corner information to select informative image patches in the PAN image. A hierarchical local matching method is then used to find the best matched image patches in the XS image. The coordinates of the matched image patches are fitted to an affine transformation model. The merged high resolution color imagery is obtained by multiplying each spectral bands with a sharpening factor computed from the intensity values of the panchromatic image and the corresponding pixel values of the multispectral images.

Conventional differential detection and energy detection offer poor performances for demodulating continuous phase modulated (CPM) signal because of inherent inter-symbol interference (ISI). Based on the pulse amplitude modulation (PAM) decomposition of CPM signal, the binary CPM with any non-integer modulation index can be interpreted as a linear modulation with differentially encoded pseudo-symbols or equivalently as a modulation scheme with two overlapped waveforms to carry information bits. By combining the equalization of ISI with the design of the receiver filters under the minimum mean square error (MMSE) criterion, the equalized differential detection and equalized energy detection for binary CPM signal demonstrate significant performance improvements while maintaining the same simple receiver structures as the conventional ones. Through theoretical analysis, a closed-form formula is derived to efficiently evaluate the bit error probabilities of the proposed noncoherent receivers. Simulation results using minimum shift keying (MSK) and Gaussian frequency shift keying (GFSK) with BT = 0.5, h = 0.34 are also provided to conform with the performance improvements.

A novel arbitrary conversion ratio sample rate conversion (SRC) structure for software defined radio (SDR) is proposed in this paper. Simplified implementation is also presented, which uses only one multiplication per sample for the trapezoidal interpolation. The passband droop of the trapezoidal interpolation is compensated by the reconstruction filter, which is designed using frequency sampling method. A root raised cosine filter design example is given to show that both anti-imaging and anti-aliasing requirements for SRC can be satisfied by proper selection of design parameters.

This article presents the solution for decomposing continuous-phase modulated (CPM) signals with integer modulation index into pulse-amplitude modulated components. The notion of main complex pulse is also introduced. A simplified demodulator for CPM signals with integer modulation index is proposed as an application example and simulation results using a quaternary 2 raised cosine (RC) scheme are given.

A family of complete complementary sets of sequences with closed-form expression is presented in this paper. Firstly, by introducing the notion of Golay (1961)-paired matrix and providing its synthesis algorithms, an orthogonal Golay-paired matrix called Golay-paired Hadamard matrix is derived. Then, general procedures for constructing mutually orthogonal Golay-paired matrices are proposed. Finally, the complete complementary sets of sequences represented by Golay-paired Hadamard matrices are generated and their scalability is illustrated. The unique properties of this new family of scalable complete complementary sets of sequences make it an ideal candidate for applications in future advanced signal processing and communications systems.

This paper analyzes the performances of three impulse train modulated ultra-wideband (UWB) communications systems in an additive white Gaussian noise (AWGN) channel. First, the mathematical models for describing biphase, pulse position and hybrid modulated ultra-wideband signals are developed and the decision rules for detecting them with only AWGN interference are proposed. Then, the exact formulae of the bit error probabilities of these UWB systems and their closed-form approximations are derived. Finally, the derived formulae are applied to optimize the modulation parameter of a Gaussian monocycle UWB impulse radio.

Multiple independent Rayleigh fading waveforms are often required for the simulation of wireless communications channels. Jakes (1974) Rayleigh fading model and its derivatives based on the sum-of-sinusoids provide simple simulators, but they have major shortcomings in their simulated correlation functions. A novel sum-of-sinusoids fading model is proposed and verified, which generates Rayleigh fading processes satisfying the theoretical independence requirements and providing desired power spectral densities with ideal second-order moment. The effects of replacing sinusoids in the proposed model by their approximate waveforms are also analyzed and tested. Performance evaluation and comparison are provided, using the quality measures of the mean-square-error of autocorrelation function and the second-order moment of the power spectral density.

An intersymbol interference (ISI) free spread spectrum system, named multicode interleaved direct sequence spread spectrum (MCI-DSSS) system, is proposed in this paper. By combining the multicode direct sequence spreading and block interleaving together, this system is able to provide high-speed data transmission over severe multipath frequency-selective fading channel While the ISI is resolved by the orthogonality of the code set used in the multicode spreading, high degree path diversity is exploited to overcome the significant dispersion of the channel which may have a delay spread much longer than one bit duration, Another advantage of this MCI-DSSS system over conventional multicode and multicarrier systems is its higher power efficiency as constant envelope modulations can be applied to the binary MCI-DSSS baseband signal. The principle of the multicode interleaved direct sequence spreading and the MCI-DSSS system models are described. The selection of practical code sets in relation to the system structures is summarized and numerical results are given.

The simulation of wireless communication channels often requires the generation of multiple complex waveforms satisfying the following conditions. (1) The real and imaginary parts are independent zero-mean random Gaussian processes with identical auto-correlation functions. (2) The complex waveforms are independent so that the cross-correlation function between any two waveforms is zero. We first analyze previously proposed methods based on Jakes fading model to demonstrate that the above two conditions have not been satisfied. We then propose a novel method for the generation of multiple Rayleigh faders, which uses improved arrival angle patterns and incident wave phases. The auto-correlation and cross-correlation functions are derived to prove theoretically that the above two conditions are satisfied. Finally the statistical properties are verified by numerical results.