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Optimal jamming has important applications in both military and civil communications. There have been a brunch of works investigating the optimal jamming signal design when the signal modes of the opponent are known. In this work, we focus on the less studied hidden mode jamming problem. That is, the jammer has partially recorded the signal modes of the opponent, but there are some hidden modes not revealed to the jammer as of the appearance of these modes. As such, when the hidden modes appear, the jammer has to quickly adapt its jamming strategy to achieve effective jamming. However, it is challenging to do so due to incomplete knowledge of the intrinsic relation between the known and the hidden modes. In this work, a learning-based approach is proposed to attack this problem. Specifically, we custom-devise a jamming network (J-Net) to automatically learn the intrinsic relation among different modes and transfer the jamming strategy from the known modes to the hidden ones. Experimental results demonstrate that the J-Net attains much better jamming effect than pulsed Gaussian jamming and random jamming, and is comparable to the reinforcement learning-based approach, which assumes all the (known and hidden) modes available at the jammer.

Frequency diverse array (FDA) employs an extra frequency increment across array elements, resulting in a range-angle-dependent transmitted beampattern. Due to this superiority against conventional phased array, FDA gains more and more attentions in recent years. To further extend FDA's application, in this study, a symmetrical logarithmic FDA configuration is proposed as transmitter to produce a range-dependent beam. And phased array is adopted as receiver in a bistatic radar system. The overall transmit and receiver array system shows its ability in range-angle target imaging. The influences of both array number and frequency increment are discussed. Simulation experiments validate the effectiveness of the proposed approach.

To alleviate the spectrum congestion crisis, we design a dual-function radar-communication (DFRC) with frequency diverse array multiple-input multiple-output (FDA-MIMO) radar. A set of orthogonal waveforms are used to implement the primary radar operation, and we propose an information embedding scheme for the secondary communication function, which is carried out by embedding the information into the frequency increments of FDA-MIMO radar as part of phase of the transmit steering vector. The communication receiver detects the phase of the received signal and uses it to decode the embedded binary sequence. The probability of error is analyzed in terms of the bit error rate (BER). In addition, the Cramer-Rao bounds (CRBs) for angle and range respectively are derived to examine the effect of information embedding in radar emission on the performance lower bounds of the FDA-MIMO radar. Simulation examples are provided to demonstrate the effectiveness of the proposed information embedding technique.

This paper proposes a general receiver design approach for frequency diverse array (FDA) radar, which has not been investigated in the FDA literatures. The formulated receiver signal model is suitable for any FDA with an arbitrary geometry and arbitrary frequency increments. The designed FDA receiver structure can achieve the optimal estimation and detection based on the maximum likelihood criterion. The effectiveness of the receiver is verified by both theoretical analysis and numerical examples.

Frequency diverse array (FDA) is a kind of radar array who has an additional linear frequency increment across the array elements. Different from the conventional phased array whose steering beam is fixed at a certain angle for all ranges, FDA transmits range-dependent beampattern which contains both the angle and range information, making it resistant to point interference. This paper employs the FDA technique into the stripmap SAR system to implement microwave imaging. Moreover, besides the advantage of FDA, the FDA-SAR system owns a range resolution improvement over the conventional SAR imaging system.

A modified phase gradient autofocus (PGA) method tailored for circular trace scanning synthetic aperture radar (CTSSAR) is provided in this paper to handle the motion compensation problem. In CTSSAR, the circular orbit makes the imaging and the motion compensation hard to perform, and the traditional algorithms cannot accomplish precise imaging. Different from the classical PGA method, the modified PGA algorithm takes the residual high order phase errors into account. The precise phase estimation can be achieved after the residual phase errors are accurately estimated and compensated. Simulation results are presented to demonstrate the validity of the proposed approach.

Different from conventional phased-arrays using a fixed carrier frequency for all the array elements, the frequency diverse array (FDA) using linearly increasing frequency increment yields a ‘S’-shape range-angle beampattern, which provides the potential capability to suppress range-dependent interferences. FDA produces promising range-angle-dependent beampattern, but the beampattern is time-variant which is undesired in target localization and interference suppression. This paper proposes a time-invariant transmit beampattern synthesis via time-dependent weight design for uniform linear array FDA by convex optimization. Compared with existing FDA beampattern synthesis methods, the proposed method provides longer dwell time, better flexibility and more easily to implement. Its effectiveness is verified by simulation results.

Traditional interference suppression approaches will enjoy the additional benefits when angle as well as polarization domain information are involved by polarization sensitive array (PSA). However, the information from range domain and its collaboration with other domains are rarely explored. In this paper, we present the polarization sensitive frequency diverse array (PSFDA) which combines frequency diverse array (FDA) and PSA for robust angle-range-polarization beamforming. To improve the angle-range-polarization resolution, the sparse reconstruction respective of compressive sensing is further applied. Theoretical analysis and simulation results demonstrate that our proposed algorithm can provide the good range-polarization resolution not just the target direction.

This paper proposes a nested frequency diverse array (FDA) design scheme, which jointly utilizes FDA angle-range-dependent beampattern and nested array increased degrees-of-freedom (DOFs). In this case, the commonly used MUSIC algorithm fail to estimate multiple sources because of the source correlation. Furthermore, a compressive sensing-based range and angle estimation algorithm is proposed. While compared with traditional spatial smoothing (SS) based localization method, our proposed method requires less snapshots and better performance.

Different from phased-array providing range-independent beampattern, frequency diverse array (FDA) yields range-dependent transmit beampattern. Since ambiguity function is an effective tool to analyze the time-delay (range) and Doppler resolution performance of various radar systems, this paper derives the FDA radar ambiguity function and optimizes the ambiguity function with simulated annealing algorithm, with an aim to focus the transmit energy to the desired range-angle section and suppress undesired sidelobes. The proposed method is verified by numerical results.

Two-way relaying showed distinct advantages in spectral efficiency for pairs of source nodes to exchange information via a multiple-input multiple-output (MIMO) amplify-and-forward (AF) relay node. This paper studies the relay beamforming problem in the scenario where multiple pairs of users communicate via a MIMO relay node, in order to achieve a beer rate and guarantee the fairness of user's rate. In the relay beamforming design we consider the maximum of minimum information rate among the user pairs as the target and the total relay transmit power as the constrain. The corresponding optimization problem can be built into a difference-of-convex functions (DC) program, and it can be well solved by an effective algorithm. Numerical results show that, the proposed method enjoys the merits of both max-min fairness and sum-rate when compared with existing relay beamforming methods.

This paper compares four elevation multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) antenna arrangements for wide-swath remote sensing. The signal models and range ambiguity function to signal ratio performance are comparatively compared, along with numerical results. It is shown that, when compared with conventional single-antenna SAR and existing multichannel SAR techniques, MIMO SAR indeed provides a potential solution for wide-swath remote sensing.

Although phased-array beamforming has received much attention, it cannot effectively suppress the interferences that have the same direction angle but different ranges of the targets. More seriously, the targets may be submerged in the strong interferences and can not be identified. In this letter, we propose a range-dependent interference suppression via frequency diverse array (FDA) transmit beamforming based on convex optimization algorithm. The FDA uses a small frequency increment based on phased-array to provide a range-dependent beampattern, which thus offers a beamforming-based solution to suppress range-dependent interferences. The interference suppression performance as compared to phased-array is analyzed by examining the output signal-to-interference ratio (SIR) and signal-to-clutter ratio (SCR). Simulation results show that significant SIR and SCR performance improvements have been achieved by employing the proposed method.

Large time-bandwidth product waveform diversity design is a challenging topic in multiple-input multiple-output radar high-resolution imaging because existing methods usually can generate only two large time-bandwidth product waveforms. This paper proposes a new low peak-to-average ratio (PAR) orthogonal frequency division multiplexing chirp waveform diversity design through randomly subchirp modulation. This method can easily yield over two orthogonal large time-bandwidth product waveforms. More waveforms means that more degrees-of-freedom can be obtained for the system. The waveform performance is evaluated by the ambiguity function. It is shown that the designed waveform has the superiorities of a large time-bandwidth product which means high range resolution and low transmit power are allowed for the system, almost constant time-domain and frequency-domain modulus, low PAR and no range-Doppler coupling response in tracking moving targets.

Frequency Diverse Array (FDA) can provide range-angle-dependent beam which is different from the angle-only directional beam of conventional phased-array and bring potential applications. Small frequency offset between adjacent elements is the essential difference compared with conventional phased-array. In this paper, we propose two transmit beampattern synthesis schemes for linear FDA to focus transmit energy in one or multiple desired range-angle spatial areas with applications to locate 2-D targets or suppress interference and clutter. Furthermore, arbitrary shaped beam in a two-dimension section can be attained through our methods. The effectiveness of the proposed schemes are verified by simulation results.

In modern wireless networks, dynamically optimizing the association between base stations (BSs) and users is a promising solution for performance improvement. However, a frequently changing BS-user association introduces heavy burden for network management. In this paper, we seek for balancing the flexibility and stability of the BS-user association in a green downlink MISO network. In addition to minimizing the transmit power and controlling the number of active BSs, we further consider reducing the users' switching frequency among BSs. This problem is a nonlinear mixed-integer program, and challenging to solve. As a compromise, we see for some efficient approximate solution to it by reformulating it as a convex sparse problem. An efficient algorithm is then developed to enhance the sparse solution, based on the iterative reweighted l 1 technique. The effectiveness of the proposed algorithm was validated by numerical simulations.

Consider an uplink SIMO network consisting of multiple base stations (BSs) and multiple users, where each user has an individual transmit power constraint, and the BSs are allowed to cooperate in data receiving. To guarantee fairness among users and avoid heavy burden of backhaul data exchange, we maximize the minimum S-INR based on joint BS selection and beamforming. We formulate this problem from the perspective of sparse beamforming. However, the scaling ambiguity of the receive beamformers will make the sparse constraints trivial. Inspired by the observation that the transmit beamformer is immune to the scaling ambiguity, we apply the duality theorem to the uplink max-min problem under per-user power constraints, and reformulate it as an equivalent downlink problem. An iterative two-stage algorithm is then developed to solve the sparse beamforming problem efficiently. The effectiveness of the proposed algorithm is demonstrated by numerical simulations.

In this paper, we propose a target localization method with frequency diverse array (FDA) multiple-input and multiple-output (MIMO) radar in sparse signal reconstruction perspective. We jointly use sparsity reconstruction method and FDA transmitting array. The essence of the proposed technique is to formulate the problem of angle and range estimation using sparsity enforced reconstruction method with FDA MIMO radar. And one type of sparse reconstruction methods, the convex relaxation method, is considered. By implementing numerical experiments, we demonstrate that our proposed method can fully utilize the range-independent directivity created by FDA transmitting array and also outperform the conventional MUSIC method.

We consider the green communication problem in a downlink cooperative MISO network consisting of multiple base stations (BSs) and multiple users. We employ power efficiency as the performance metric, defined as the ratio of total user rate to total power consumption. The total user rate is related to the number of active users, while the total power consumption includes the transmit power and the device maintenance power, determined by the beamformers and the number of active BSs, respectively. Motivated by this observation, we consider a power efficiency maximization problem by jointly optimizing the active BSs, the admissible users and the cooperative beamform-ers. This problem is challenging due to the fractional objective and the mixed-integer program. To seek for some efficient approximate solution, we first formulate it as a convex sparse problem balancing the transmit power, the number of active BSs and the number of admissible users. A two-stage algorithm is then developed to solve the approximate problem. Simulations demonstrate the effectiveness of the proposed algorithm.

This paper proposes a nested frequency diverse array (FDA) radar by systematically nesting multiple uniform linear FDAs. Using second-order statistics of the received data, it is capable of providing a dramatic increased in degrees-of-freedom (DOFs). The detection performance of the designed nested FDA radar is evaluated by examining the probability of detection. The performance improvements offered by the proposed method, as compared to basic FDA radar, are demonstrated by simulation results.

For frequency diverse array (FDA) pattern synthesis, smaller aperture or fewer elements are expected to obtain the desired beampattern performance. This paper propose a new FDA beampattern synthesis approach by l 1 -norm minimization and convex optimization. Given array aperture, a virtual uniform linear FDA array with much smaller element spacing and corresponding frequency increment is created first; then, the array pattern synthesis (APS) problem is formulated as finding a jointly sparse weight vector, the antenna elements corresponding to nonzero values of the joint sparse weight vector are retained to form the non-uniform FDA. Finally, the weight vector of the non-uniform FDA is optimized via convex programming. Compared with discrete spheroidal sequence (DSS) method, the proposed algorithm can save 7 antenna elements to achieve the desired radiation pattern.

This paper proposes a receiving nested frequency diverse array (FDA) design scheme. The essence of the proposed technique is to construct a new array structure by systematically nesting two or more uniform linear FDA. Using second-order statistics of the received data, it is capable of providing a significant increasing degrees-of-freedom. The frequency increment across the array results in a scan angle that varies with range and provides resistance to range-dependent interference. The improvement offered by the proposed method as compared to traditional FDA are demonstrated by extensive simulation through analyzing the corresponding beam pattern and direction-of-arrival estimation performance.

A direction-of-arrival (DOA) estimator based on sparse recovery, where the dictionary entries are formed by discretizing the angle space and correspondingly sampling the received signal. Furthermore, to reduce hardware realization complexity, we use the level-triggered sampling (LTS) to sample the signal at different sensors, which typically samples below the Nyquist rate for bursty signals and needs only 1 bit to represent each sample. The sampled signal vectors and dictionary are then obtained through interpolations. Simulation results show that the proposed method, when compared with existing compressive sensing-based methods, achieves better estimation performance with less samples.

In this paper, we propose a robust timing and frequency synchronization algorithm for the orthogonal frequency division multiplexing (OFDM) systems. The algorithm we proposed can achieve accurate timing and frequency synchronization in time-domain by using the preamble consisting of only one training symbol based on constant amplitude zero autocorrelation (CAZAC) sequence and a new weighting factor. The timing metric used in the algorithm has a peak only at the correct starting point while almost zeros at other points. So the “platform effect” can be avoided and a high timing precision can be obtained. Meanwhile, the proposed method of integer frequency offset estimation is robust to the multipath and noise interference. Computer simulation results show that our proposed scheme achieves superior performance under the multipath fading channel than existing algorithms in terms of timing and frequency synchronization.

This paper proposes an approach to design orthogonal multiplexing waveform for use of Multiple-input Multiple-output (MIMO) radar. The designed scheme incorporate direct sequence spread spectrum (DSSS) coding techniques on orthogonal frequency division multiplexing (OFDM) chirp signaling. We call it spread spectrum coded OFDM chirp (SSCOC) signaling. The performance of the signals are analyzed with the cross-ambiguity function. In the experiment, the influence of spread spectrum code length and type as well as the bandwidth and duration of OFDM chirp waveforms on cross-ambiguity function (CAF) is discussed. It is verified that the proposed design scheme can ensure these waveforms stay orthogonal on receive and obtain large time-bandwidth product which are beneficial to separate closely spaced targets with ultra-high resolution.

This paper proposes a hybrid phased-array multiple-input multiple-output (MIMO) synthetic aperture radar (SAR)-based ground moving target imaging approach. The proposed ground moving target imaging approach divides the whole array into two subarrays (each subarray coherently transmits a distinct waveform which is orthogonal to the waveforms transmitted by other subarrays) and combines the displaced phase centre antenna (DPCA) and along-track interferometry (ATI) processing techniques. The signal processing, motion parameters estimation and moving targets focusing algorithms are detailed. Both analytical and simulation results validate the effectiveness of the proposed approach.

The algorithm of tracking and localizing a single rapid moving sound target, based on double five-elements-cross arrays, is presented in this paper. The four time-delay-difference values of each array can be estimated by the methods of generalized cross-correlation. And then, the azimuth angle can be calculated with the special structure of the array. The distance between the target and the center of each array can be estimated by the four time-delay-difference values in theory, however, the satisfactory estimating precision of the distance need high estimating accuracy of time delay, and this is very difficult. Therefore, the acceptable position parameter of the target can be gained by the multi- angles of multi-arrays. Double five-elements-cross arrays are placed in one area with 500*500 meters in the simulation, and the estimation error of the azimuth angle is less than 0.4 degree, and the coordinate error is less than 10 meters. The results of the simulation show the algorithm is effective and has high performance.

Phased-multiple-input multiple-output (MIMO) radar enjoys the advantages of MIMO radar in diversity gain without sacrificing the main advantage of phased-array radar in coherent transmit gain. However, a limitation of the phased-MIMO radar is that the beam steering is fixed in an angle for all the ranges. This limits the system performance to mitigate non-desirable range-dependent interferences. To overcome this disadvantage, this paper proposes a flexible phased-MIMO radar with frequency diversity. This approach divides the transmit antenna array into multiple subarrays that are allowed to overlap, each subarray coherently transmits a distinct waveform, which is orthogonal to the waveforms transmitted by other subarrays, at a distinct transmit frequency. Each subarray forms a range-dependent beam and all beams may be steered to different ranges or directions. The subarrays jointly offer flexible operating modes such as MIMO radar, phased-array radar, and phased-MIMO radar.

Signal-to-noise ratio (SNR) is a crucial parameter for adaptive transmission in orthogonal frequency division multiplexing (OFDM) systems. For the OFDM-based multicast/broadcast over single frequency network (MBSFN) system, the downlink transmission channels is quite frequency selective, which is a great challenge for SNR estimation in user terminals with simple implementation. We develop a pilotassisted algorithm operated in transform domain to improve estimation performance. The proposed estimation algorithm is robust to frequency and time selectivity, and is suited to different pilot patterns. Simulations show that the proposed estimator is insensitive to different type of channels, and is superior to conventional methods.

Power control plays a key role in realizing reliable and spectrum-efficient communications in a cognitive radio network. In this paper we study secure power control schemes for cognitive radios via a robust Markov decision process (MDP) approach. We first use the discrete time Markov chain (DTMC) model to characterize the primary user's (PU) activities as well as the dynamics of the fading channel. The resulting power control problem can be optimally solved by a dynamic programming (DP) approach. The presence of malicious users, however, necessitates a cooperative spectrum sensing approach that requires extra signal processing and information exchange efforts to identify false spectrum sensing reports. Such a cooperative approach incurs considerable delay in spectrum sensing that may significantly deteriorate the performance of the DP strategy. Furthermore, the false sensing data generated by malicious users may give rise to erroneous estimation of the transition probabilities. Consequently, the solution obtained based on the estimated transition matrices may exhibit poor performance. To cope with these challenges, we propose a framework of power control schemes based on the robust MDP approach that is capable of achieving reasonably good performance when both spectrum sensing delay and estimation errors are present. The tradeoffs between the robustness, the achievable throughput, and the sensing delay are also discussed. Extensive simulation results are presented to demonstrate the performance of the proposed power control strategies.

In this paper, we study transmission policies for opportunistic spectrum access over multiple Rayleigh fading channels. We formulate the opportunistic spectrum access problem as a joint channel access and power control problem with the objective that maximizes expectation sum of throughput under the constraint of limited battery capacity over finite time slots. In this problem, we consider the transmission power limitation for each channel to guarantee fairness of spectrum access. Furthermore, we propose a discrete-time Markov chain model, which can account for primary users' (PUs) activities and the fading characteristics. Based on this Markov model, we efficiently solve the problem via dynamic programming and propose the optimal transmission policy. Extensive simulations verify the performance of the proposed scheme.

The Direct Sequence Spread Spectral (DSSS) communication system has been widely used in military and civilian fields because of its high processing gain, strong ant-jamming and anti-probed capacity, and low intercepted probability. In this paper, an efficient blind parameter estimating and detecting algorithm is proposed, which takes advantage of the autocorrelation property of pseudo random code. In this algorithm, the input data is first divided into several blocks, and then the correlation between blocks is worked out. By changing the length of the blocks, a series of different correlation values is obtained. The crest value appears at the period of pseudo random code, and it is utilized to determine whether the DSSS signal exists or not and to estimate the signal's parameters in terms of the interval of crest value. The simulation results demonstrate the good performance of the proposed algorithm.

In this paper, a joint frame detection and timing estimation scheme for burst Orthogonal Frequency Division Multiplexing (OFDM) systems is proposed in double selective channels. The proposed scheme based on the training sequence is not sensitive to carrier frequency offset (CFO) and the given threshold for frame detection is robust to different signal-to-noise ratio (SNR). Simulation results demonstrate that the scheme can work well even if SNR is low.

In this paper, a novel rapid varying doubly-selective channel estimator for OFDM systems has been proposed, in which channel is modeled by basis expansion model (BEM). Unlike traditional BEM channel estimation algorithms, in which the comb-pilot is used and the large path delay is not considered, the proposed algorithm uses firstly block-type pilot to estimate the BEM coefficients of fast-varying doubly-selective channel at the pilot OFDM symbols, and then the BEM coefficients at the pilot OFDM symbols can be applied to interpolate for obtaining the BEM coefficients at data OFDM symbols using different interpolation algorithms. With Jake's channel model, the simulation results show that the proposed algorithm is very effective.

In cognitive radio (CR) networks, power control is necessary to not only decrease the interference among the secondary users (SUs), but also avoid negative impact to the primary users (PUs). To meet the communications needs between PUs and SUs in cognitive radios and to ensure that the unimpaired operation of the PUs and SUs' communications be not intermitted, a MC-CDMA cognitive radios system and a hand-off technique were proposed for secondary users. In order to efficiently use the limited cognitive radio resources, a novel power control game algorithm in CR systems was adopted. The novel algorithm can regulate their transmitter powers to meet the different SINR requirements and enhance the total throughput effectively. The computer simulations show that the performance of CR system is thereby improved obviously.

Continuous-Phase Modulation (CPM) signal with bandwidth-efficiency and power-efficiency and constant envelope has been studied and used widely. In this paper, a new non-data aided estimator of the technical parameters of full responsible binary CPM signals, which can be used in non-cooperative communication receivers, is proposed. It consists in estimating the symbol rate and the frequency offset. The frequency offset estimator makes good use of the oversampling information. The simulation results show that the proposed symbol rate estimator is very efficiency and the frequency offset estimator is very good when the frequency offset is big, for example ΔfT=0.3, for full responsible binary CPM signals.

In this paper, a new approach of blind estimation of subcarrier number based on mutiple signal classfication (MUSIC) algorithm is proposed for MB-OFDM ultra-wide band (UWB) communications system. The proposed eigenvalue-construct method only using signal autocorrelation of orthogonal frequency-division multiplexing (OFDM) symbols estimates the number of subcarriers. The computer simulations show that the proposed approach has a good performance whether it is used in AWGN channel or frequency selective fading channel.

In this paper, a carrier recovery algorithm for high-order cross-QAM has been proposed, in which less than twelve symbol points in the constellation have been used. The proposed algorithm can be applied to square QAM signals as well. The simulation results demonstrate that the proposed algorithm can deal with carrier frequency offset up to 600KHz@32QAM or 400KHz@128QAM over AWGN channels when the bit rate is 5Mbit/s. The simulation experiments are also done for 64QAM and 256QAM signals, and results show that the proposed algorithm has good performance over a large acquisition span of frequency.

A timing recovery algorithm has been proposed in this paper. Johnson proposed output power maximizing timing recovery algorithm which was applied to QPSK signal. The novel algorithm can be applied to QAM signal over AWGN and multipath fading channels. It is easily implemented as it requires only one sample per symbol for its operation. The simulation results show that the proposed algorithm needs no training data with fast convergence.