Integrated sensing, communications, and computation (ISCC) is becoming increasingly critical, particularly for enabling advanced intelligent applications. This paper proposes an ISCC framework for edge-intelligent networks, where edge intelligent devices (EIDs) cooperatively sense multiple mobile targets and simultaneously offload radar sensing data to a base station (BS) equipped with an edge server for processing. To address the time-varying nature of the network, we develop an online resource management strategy that maximizes the long-term average weighted sum rate (AWSR), subject to queue stability, average power constraints, and quality-of-service (QoS) requirements. Using the Lyapunov drift-plus-penalty framework, the original stochastic optimization problem is decomposed into a sequence of deterministic subproblems across time slots. At each time slot, sensing scheduling, transmit beamforming for both sensing and communications, receive beamforming for radar echoes, and computing resource allocation at the BS are jointly optimized through an efficient alternating optimization algorithm based on the current system state. Simulation results validate the effectiveness of the proposed online strategy, showing superior performance over baseline methods and revealing the influence of key parameters. In particular, a trade-off is observed between the AWSR and queue backlogs, which can be flexibly tuned via control parameters.

This paper investigates a full-space covert communication (CC) scheme aided by a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS), which can resist the position randomness of the eavesdropper (PRE). In contrast to prevailing STAR-RIS assisted CC schemes assuming an eavesdropper with fixed position, the proposed CC scheme considers an eavesdropper which randomly locate at both sides of the STAR-RIS, leading to 360° eavesdropping risks. To restrict the eavesdropper’s ability to detect the CCs, the covert user is designed with two antennas working in full-duplex mode. One of the antennas is employed to receive the desired covert messages, while the other produces jamming signals at various power levels to impede the eavesdropper’s detection. Except the covert user, the base station (BS) also needs to serve a public user, which has certain quality of service (QoS) requirement. In order to construct a robust covert constraint, we analyze and derive a closed-form formula for the eavesdropper’s minimum detection error probability (DEP) in the worst-case situation. Subsequently, an optimization problem is established to maximize the covert rate of the system, through joint optimizing the bandwidth allocation, the active beamforming of the BS, and the passive beamforming of STAR-RIS, while adhering to the covert constraint and QoS requirement for the public user. An iterative algorithm is provided to tackle this non-convex optimization problem, utilizing the semi-definite relaxation (SDR) method and the augmented Lagrange technique. The simulation results demonstrate that the proposed STAR-RIS assisted CC scheme exhibits superior performance in resisting the full-space eavesdropping compared to other benchmark schemes, thereby validating the efficacy of the proposed scheme.

In response to the “security blind zone” challenges faced by traditional reconfigurable intelligent surface (RIS)-aided covert communication (CC) systems, the joint distance-angle beamforming capability of frequency diverse RIS (FD-RIS) shows significant potential for addressing these limitations. Therefore, this paper initially incorporates the FD-RIS into the CC systems and proposes the corresponding CC transmission scheme. Specifically, we first develop the signal processing model of the FD-RIS, which considers effective control of harmonic signals by leveraging the time-delay techniques. The joint distance-angle beamforming capability is then validated through its normalized beampattern. Based on this model, we then construct an FD-RIS-assisted CC system under a multi-warden scenario and derive an approximate closed-form expression for the covert constraints by considering the worst-case eavesdropping conditions and utilizing the logarithmic moment-generating function. An optimization problem is formulated which aims at maximizing the covert user’s achievable rate under covert constrains by jointly designing the time delays and modulation frequencies. To tackle this non-convex problem, an iterative algorithm with assured convergence is proposed to effectively solve the time-delay and modulation frequency variables. To evaluate the performance of the proposed scheme, we consider three communication scenarios with varying spatial correlations between the covert user and wardens. Simulation results demonstrate that FD-RIS can significantly improve covert performance, particularly in angular-overlap scenarios where traditional RIS experiences severe degradation. These findings further highlight the effectiveness of FD-RIS in enhancing CC robustness under challenging spatial environments.

Multi-beam low earth orbit (LEO) satellite communications, as an essential component for 6G systems, may encounter challenges from severe Doppler shifts and co-channel interference. This paper addresses a realistic problem in 6G-LEO systems, that is, how to meet the high-reliability demands of massive high-mobility terminals. We propose an integrated framework to exploit the synergy of non-orthogonal multiple access (NOMA) and orthogonal time frequency space (OTFS). OTFS modulation is employed to achieve full time-frequency diversity to combat Doppler shifts, while NOMA is used to accommodate more access requests. Specifically, within each beam, power domain superposition is applied to the delay-Doppler domain, enabling multiple terminals to share delay-Doppler grid resources. We analyze the performance of reliability, outage probability and ergodic capacity. Notably, we derive a novel closed-form expression to characterize the distribution of multi-beam interference with varying beam gains. Theoretical analysis and simulation results confirm that the proposed framework achieves a substantially lower outage probability compared to conventional OFDM schemes, with a system capacity improvement exceeding 11.9%.

Multi-source direction of arrival (DOA) estimation based on mobile platforms draws much attention for its extensive practical applications, among which that unmanned aerial vehicle (UAV) platform is particularly valuable. To ensure the precision and spatial resolution, multi-source DOA estimation always relies on large-scaled antenna arrays. With the rapid development of UAV and its coordinate technology, high-accuracy multi-source DOA estimation based on UAV coordinate system becomes possible. However, due to all kinds of external disturbances, multi-source DOA estimation for the UAV coordinate system suffers the random UAV unit positions and pointing directions, and there is always unknown phase error between adjacent units. To handle these problems, a Fourth-order Cumulant (FoC) based DOA Matrix algorithm is proposed. A DOA Matrix is constructed by FoCs using the received signals, and its eigenvectors are used to acquire the manifold of the entire array, which can be used to solve the implied DOAs. The simulation results verify the availability of the proposed algorithm in the UAV coordinate system, while the traditional DOA estimation methods are disabled. Meanwhile, it gets at least the similar estimation performance as the traditional methods in their own ideal conditions.

This paper explores a simultaneous tasks offloading and communications (STOC) scheme in mobile edge computing (MEC) networks, supported by the combination of simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) and the unmanned aerial vehicle (UAV). Different from the traditional MEC schemes, the proposed scheme concurrently considers the computation and communication capabilities of the MEC networks, which is actually more practical in reality. Specifically, an optimization problem is devised to maximize the weighted sum of the minimum computed task data and communication data, while ensuring the quality of service (QoS) constraints for STOC through joint design of time scheduling, resource allocation, active and passive beamforming, alongside with the UAV trajectory planning. This non-convex problem with strong couplings among variables is challenging to solve directly. Then, a novel alternating optimization method is proposed, leveraging the successive convex approximation (SCA) and semi-definite relaxation (SDR) techniques. We provide sufficient numerical results to validate the effectiveness of the proposed STOC scheme, which demonstrate that the proposed scheme supported by STAR-RIS and UAV outperforms five benchmark schemes in terms of performance gain. It is important to note that the proposed scheme offers a feasible and realistic way for the implementations of STOC in practical MEC networks.

A robust full-space physical layer security (PLS) transmission scheme is proposed in this paper considering the full-space wiretapping challenge of wireless networks supported by simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS). Different from the existing schemes, the proposed PLS scheme takes account of the uncertainty on the eavesdropper’s position within the 360◦ service area offered by the STAR-RIS. Specifically, the large system analytical method is utilized to derive the asymptotic expression of the average security rate achieved by the security user, considering that the base station (BS) only has the statistical information of the eavesdropper’s channel state information (CSI) and the uncertainty of its location. To evaluate the effectiveness of the proposed PLS scheme, we first formulate an optimization problem aimed at maximizing the weighted sum rate of the security user and the public user. This optimization is conducted under the power allocation constraint, and some practical limitations for STAR-RIS implementation, through jointly designing the active and passive beamforming variables. A novel iterative algorithm based on the minimum mean-square error (MMSE) and cross-entropy optimization (CEO) methods is proposed to effectively address the established non-convex optimization problem with discrete variables. Simulation results indicate that the proposed robust PLS scheme can effectively mitigate the information leakage across the entire coverage area of the STAR-RIS-assisted system, leading to superior performance gain when compared to benchmark schemes encompassing traditional RIS-aided scheme.

This paper introduces a novel multi-user mobile edge computing (MEC) scheme facilitated by a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) and a unmanned aerial vehicle (UAV). Unlike existing MEC approaches, the proposed scheme enables bi-directional offloading, allowing users to concurrently offload tasks to the MEC servers located at ground base station (BS) and UAV with the support of the STAR-RIS. To evaluate the effectiveness of the proposed MEC scheme, we first formulate an optimization problem aiming at maximizing the energy efficiency of the system while ensuring the quality of service (QoS) constraints by jointly optimizing the resource allocation, user scheduling, passive beamforming of the STAR-RIS, and the UAV trajectory. A block coordinate descent (BCD) iterative algorithm designed with the Dinkelbach’s algorithm and the successive convex approximation (SCA) technique is proposed to effectively handle the formulated non-convex optimization problem characterized by significant coupling among variables. Simulation results indicate that the proposed STAR-RIS enhanced UAV-enabled MEC scheme possesses significant advantages in enhancing the system energy efficiency over other baseline schemes including the conventional RIS-aided scheme.

This article investigates the covert performance of the finite block length device-to-device (D2D) transmission between the multiantenna transceivers assisted by a decode-and-forward (DF) relay node, where the adversary in covert communication, the warden, also employs a multiantenna maximum likelihood detector which observes the covert signals from the source and the relay for joint detection. The relay periodically transmits reference signals to improve the throughput rate over the fading channels while the source and destination estimate the channel coefficients for beamforming. The nonideal beamforming performance with limited reference signals is analyzed, the covert performances measured by the expected relative entropies of the warden’s joint detection are derived, and the optimal power allocation strategy to achieve the highest covert performance under the required throughput rate and outage probabilities is formulated in this article. The theoretical analysis and the numerical results illustrate that the communication side will achieve higher covertness if the relay and the source adopt uncorrelated codes, and the increase in the warden’s antenna number would rapidly improve its detection performance. The numerical results also depict that enhancing the source-to-relay covert transmission brings more improvements for the covertness than the relay-to-destination link, showing the asymmetry between the different links of the DF-relay-assisted covert communication.

Multi-sources Direction of Arrival (DOA) estimation based on Unmanned Aerial Vehicle (UAV) draws much attention for its flexibility and practicability. Meanwhile, the UAV collaborative technology can be used to guarantee the spatial Degree of Freedom (DOF), but it is always puzzled by the imprecise array structure and the strict demand of Radio Frequency (RF) chains calibration. The random amplitude and phase differences among the units deeply disturb the DOA estimation. To handle this random problem, a unique UAV network is designed, and a fourth-order cumulant-based multi-sources DOA estimation algorithm is proposed in this letter. The network consists of one main unit with two antennas and several assistant units with one antenna, the main unit provides the effective amplitude and phase information and the assistant units are used to ensure the spatial DOF. Therefore, both the array structure information and RF chain calibration of assistant units are not needed. The simulation results verify that the proposed algorithm is effective for multi-sources DOA estimation even with random amplitude and phase differences among the units.

Covert wireless communication intends to prevent hostile surveillance but is threatened by the powerful multi-antenna detection technique. In this paper, we investigate finite blocklength covert communication assisted by a multi-antenna relay station and a multi-antenna destination to fight against hostile detection from a warden also equipped with multiple antennas and interference from an uninformed jammer. In order to achieve optimal covert communication performance, we formulate the optimization problems in the single-user and the frequency division multiple access (FDMA) multi-user scenarios separately. In the single-user scenario, we design a cooperative beamforming strategy for the relay and the destination to maximize their received signal-to-interference-plus-noise (SINR). Then in the multi-user scenario, we utilize the above beamforming strategy and propose a majorization-minimization-based relay’s power allocation algorithm to maximize the total covert throughput rate. The numerical results are provided to depict the effectiveness of the proposed scheme, and we address how the jamming power and the numbers of antennas affect covert communication based on these numerical results and theoretical analysis.

This paper investigates the utilization of simultaneously transmitting and reflecting RIS (STAR-RIS) in supporting joint physical layer security (PLS) and covert communications (CCs) in a multi-antenna millimeter wave (mmWave) system, where the base station (BS) communicates with both covert and security users while defeating eavesdropping by wardens with the help of a STAR-RIS. Specifically, analytical derivations are performed to obtain the closed-form expression of warden’s minimum detection error probability (DEP). Furthermore, the asymptotic result of the minimum DEP and the lower bound of the secure rates are derived, considering the practical assumption that BS only knows the statistical channel state information (CSI) between STAR-RIS and the wardens. Subsequently, an optimization problem is formulated with the aim of maximizing the average sum of the covert rate and the minimum secure rate while ensuring the covert requirement and quality of service (QoS) for legal users by jointly optimizing the active and passive beamformers. Due to the strong coupling among variables, an iterative algorithm based on the alternating strategy and the semi-definite relaxation (SDR) method is proposed to solve the non-convex optimization problem. Simulation results indicate that the performance of the proposed STAR-RIS-assisted scheme greatly surpasses that of the conventional RIS scheme, which validates the superiority of STAR-RIS in simultaneously implementing PLS and CCs.

This paper investigates the multi-antenna covert communications assisted by a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS). In particular, to shelter the existence of covert communications between a multi-antenna transmitter and a single-antenna receiver from a warden, a friendly full-duplex receiver with two antennas is leveraged to make contributions where one antenna is responsible for receiving the transmitted signals and the other one transmits the jamming signals with a varying power to confuse the warden. Considering the worst case, the closed-form expression of the minimum detection error probability (DEP) at the warden is derived and utilized in a covert constraint to guarantee the system performance. Then, we formulate an optimization problem maximizing the covert rate of the system under the covertness constraint and quality of service (QoS) constraint with communication outage analysis. To jointly design the active and passive beamforming of the transmitter and STAR-RIS, an iterative algorithm based on semi-definite relaxation (SDR) method and Dinkelbach’s algorithm is proposed to effectively solve the non-convex optimization problem. Simulation results show that the proposed STAR-RIS-assisted scheme highly outperforms the case with conventional RIS, which validates the effectiveness of the proposed algorithm as well as the superiority of STAR-RIS in guaranteeing the covertness of wireless communications.

This paper investigates the multi-antenna covert communications assisted by a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS). In particular, to shelter the existence of communications between transmitter and receiver from a warden, a friendly full-duplex receiver with two antennas is leveraged to make contributions to confuse the warden. Considering the worst case, the closed-form expression of the minimum detection error probability (DEP) at the warden is derived and utilized as a covert constraint. Then, we formulate an optimization problem maximizing the covert rate of the system under the covertness constraint and quality of service (QoS) constraint with communication outage analysis. To jointly design the active and passive beamforming of the transmitter and STAR- RIS, an iterative algorithm based on globally convergent version of method of moving asymptotes (GCMMA) is proposed to effectively solve the non-convex optimization problem. Simu-lation results show that the proposed STAR-RIS-assisted scheme highly outperforms the case with conventional RIS.

This paper presents a low-complexity lossy compression scheme for Gaussian vectors, using sparse regression codes (SRC) and a novel decimated approximate message passing (AMP) encoder. The sparse regression codebook is characterized by a design matrix and each codeword is a linear combination of selected columns of the matrix. In order to enable the convergence of AMP for lossy compression, we incorporate the concept of decimation into the AMP algorithm for the first time. Further, we show that the power allocation technique is beneficial for improving the rate-distortion performance. The computational complexity of the proposed encoding is O(log n) per source sample for a length-n source vector, using a sub-Fourier design matrix. Moreover, the proposed AMP encoder inherently supports successively refinable compression. Simulation results show that the proposed decimated AMP encoder significantly outperforms the existing successive-approximation encoding [1] and approaches the rate-distortion limit in low-rate regime.

In this paper, we address finite block-length covert wireless communication against an adversary that not only detects the signals but also localizes the source. Because of the probability of failed localization, the adversary’s detection strategy differs greatly from the former works. In the free space propagation model, we discuss the surveillance strategy of an adversary equipped with a uniform linear antenna array and the legitimate users’ resources optimization scheme for achieving covert communication. The theoretical analysis and the numerical results illustrate the properties of the adversary’s surveillance and the achievable covert communication performance, showing that the randomness in the source’s transmission time may also improve the covertness.

This paper investigates the utilization of simultaneously transmitting and reflecting RIS (STAR-RIS) in supporting joint physical layer security (PLS) and covert communications (CCs) in a multi-antenna millimeter-wave (mmWave) system. Specifically, analytical derivations are performed to obtain the closed-form expression of the warden’s minimum detection error probability (DEP) considering the practical assumption. Subsequently, an optimization problem is formulated with the aim of maximizing the average sum of the covert rate and the secure rate while ensuring the covert requirement and quality of service (QoS) for legal users by jointly optimizing the active and passive beamformers. Due to the strong coupling among variables, an iterative algorithm based on the alternating strategy and the semi-definite relaxation (SDR) method is proposed to solve the non-convex optimization problem. Simulation results indicate the superiority of STAR-RIS in simultaneously implementing PLS and CCs.

In this paper, we study a concatenate coding scheme based on sparse regression code (SPARC) and tree code for unsourced random access in massive multiple-input and multiple-output systems. Our focus is concentrated on efficient decoding for the inner SPARC with practical concerns. A two-stage method is proposed to achieve near-optimal performance while maintaining low computational complexity. Specifically, a one-step thresholding-based algorithm is first used for reducing large dimensions of the SPARC decoding, after which a relaxed maximum-likelihood estimator is employed for refinement. Adequate simulation results are provided to validate the near-optimal performance and the low computational complexity. Besides, for covariance-based sparse recovery method, theoretical analyses are given to characterize the upper bound of the number of active users supported when convex relaxation is considered, and the probability of successful dimension reduction by the one-step thresholding-based algorithm.

In this paper, we study a concatenate coding scheme based on sparse regression code (SPARC) and tree code for unsourced random access in massive multiple-input and multiple-output systems. Our focus is concentrated on efficient decoding for the inner SPARC with practical concerns. A two-stage method is proposed to achieve near-optimal performance while maintaining low computational complexity [1]. Specifically, a one-step thresholding-based algorithm is first used for reducing large dimensions of the SPARC decoding, after which a relaxed maximum-likelihood estimator is employed for refinement. Adequate simulation results are provided to validate the near-optimal performance and the low computational complexity. Besides, for covariance-based sparse recovery method, theoretical analyses are given to characterize the upper bound of the number of active users supported when convex relaxation is considered, and the probability of successful dimension reduction by the one-step thresholding-based algorithm.

This paper considers a concatenated coding scheme of sparse regression codes (SPARC) and tree code for asynchronous uplink unsourced random access. The encoding of SPARC is limited in a single sub-carrier to counter the unknown delay due to asynchronization. A slotted structure, where both channel uses and potential users are divided into slots, is added to reduce the overall computational complexity and improve its reliability when the length of the coherence block is limited. An efficient two-stage decoder is applied for further computational complexity reduction at the cost of slightly higher per-user probability of error. Asymptotic and numerical results are provided to demonstrate the effectiveness of the proposed scheme.

In this paper, we define the metric "detectable area" to measure the covertness of covert communication in a practical way. Detectable area is the area where interceptor can achieve acceptance probability of detection with desired probability of false alarm. By computing the detectable areas of single and multi-antenna interceptors in line-of-sight (LOS) channel scenario, we find that single jammer may do more harm than good on covert communication when interceptor is equipped with multi-antenna detector. This impact should be considered while designing covert communication system in the presence of jammer.

Sparse linear array has been widely used for its good performance of large aperture and low cost. But this kind of array often suffers from its high level side lobes and grating lobes. This paper presents a two-dimension particle swarm optimization (2-D PSO) algorithm for the design of non-uniform sparse linear array to reduce the effect of harmful lobes. Both the positions and beam directions of array elements are considered as the two optimization variates of the proposed algorithm. The patterns and output SINRs are compared between 2-D PSO sparse array and pre-existing array, the simulation results show that 2-D PSO algorithm is more efficient for sparse array optimization. The robustness of the proposed 2-D sparse array is also verified in this paper.

In 5G and beyond, the adequate interaction between densely deployed Internet-of-Things (IoT) devices and cellular users will generate a massive cyber-physical information stream in a real-time manner. How to capture insights underneath these data in a smart city context is gaining great attention nowadays. In this article, we introduce a highly function-differentiated metropolitan scenario, which is covered by multiple unmanned aerial vehicles (UAVs) serving as cache-enabled edge computing nodes. With the help of wireless backhaul technology, coverage capability of UAV can be dynamically configured through smart 3-D placement, where trajectories of two types of UAVs are optimized. A social augmented reality (AR)-based use case is proposed and discussed in the proposed scenario, from which we derive the fundamental mechanisms and strategies to maintain a green and sustainable edge/fog computing framework. We sequentially establish two nonconvex programming problems and optimize delay and energy performance during AR data acquisition and AR content downloading, respectively. Two convex approximation skills are applied to transform the original problems into tractable form. The experimental results show that our proposed edge computing framework can help provide energy-efficient AR service to cellular users, catering to pretty tight delay constraints.

In order to achieve more dramatic spatial multiplexing gains, both industry and academia have pushed towards the massive Multi-User Multi-Input and Multi-Output (MU-MIMO) systems. However, traditional linear precoding techniques do not scale up well with the number of antennas, i.e., they either have high implementation difficulties (zero-forcing) or sacrifice wireless capacity as a price (conjugate or codebook-based precoding). In this paper, we present a novel precoding scheme, BeamRaster, which is a fast and high efficient scheme for massive MU-MIMO system. Inspired from the codebook-based precoding, BeamRaster pre-computes a set of angle-domain beam filters that divide the channel into directional subspaces. Unlike previous work, BeamRaster carefully manages the cross-interference using (1) a grating table to track the correlation among beams in real-time, (2) an interference-aware user-beam selection, and (3) a pre-distortion method to cancel the residual interference because of side-lobes. We implement and evaluate the BeamRaster using FPGA and software defined radio platform. On one hand, BeamRaster is easy to implement in hardware, i.e., it can realize the precoding for a 64-antenna MU-MIMO system in real time with a single Altera Stratix V FPGA. On the other hand, both the experiments with medium-scale antennas and simulations with large-scale antennas show that BeamRaster can achieve high capacity gain.

In this paper, we propose a new blind frequency synchronization scheme for an OFDM system with I/Q imbalance. A blind estimation of joint CFO and I/Q imbalance parameters is first developed by exploiting the multi-antenna redundancy at the receiver. The estimation computational complexity is reduced by expressing the cost function as a superposition of very few harmonically related cosine waves. The compensation for CFO and I/Q imbalance can be further carried out, which would result in an equivalent received signal model without CFO and I/Q imbalance distortion. Then the conventional channel estimation and data detection can be performed. The Cramer-Rao bound (CRB) of the CFO estimation is derived. We also provide numerical simulations to demonstrate the superiority of the proposed method over the existing competitors.

In this paper, we investigate secure communications uplink transmissions, where there are a base station (BS) with M receive antennas, K mobile users each with a single antenna, and an eavesdropper with N receive antennas. The closed-form expressions of the achievable ergodic secrecy sum rates (ESSRs) for a random k users selection scheme in the high and low signal-to-noise ratio regimes are presented. It is shown that the scaling behavior of ESSR with respect to the number served users k can be quite different under different system configurations, determined by the numbers of the BS antennas and that of the eavesdropper antennas. In order to achieve multiuser gain, two low-complexity user selection schemes are proposed under different assumptions on the eavesdropper's channel state information. The closed-form expressions of the achievable ESSRs and the multiuser secrecy gains of the two schemes are also presented in both low and high SNR regimes. observe that, as k increases, the multiuser secrecy gain increases, while the ESSR may decrease. Therefore, when N much larger than M, serving one user with the strongest channel (Time Division Multiple Address-like) is a favorable secrecy scheme, where the ESSR scales with √2 log K.

A generalized Chinese remainder theorem (CRT) for multiple integers from residue sets has been studied recently, where the correspondence between the remainders and the integers in each residue set modulo several moduli is not known. A robust CRT has also been proposed lately to robustly reconstruct a single integer from its erroneous remainders. In this paper, we consider the reconstruction problem of two integers from their residue sets, where the remainders not only are out of order but also may have errors. We prove that two integers can be robustly reconstructed if their remainder errors are less than M/8, where M is the greatest common divisor of all the moduli. We also propose an efficient reconstruction algorithm. Finally, we present some simulations to verify the efficiency of the proposed algorithm. This paper is motivated from and has applications in the determination of multiple frequencies from multiple undersampled waveforms.

In this paper, we investigate the secrecy performance of matched-filter (MF) and zero-forcing (ZF) precoding in a multiuser massive multiple-input multiple-output (MIMO) system with a multi-antenna passive eavesdropper. For the two precoding schemes, we find that the equivalent wiretap channels are similar and thus the eavesdropper achieves the approximate same sum-rate. Closed-form expressions of ergodic secrecy sum-rate (ESSR) are derived for the both schemes in the low and high signal-to-noise ratio (SNR) regimes. We show that a positive ESSR of MF scheme may be not achieved when the BS simultaneously serves more than two users with high transmit power, while the ESSR of ZF scheme always grows with the number of the served users. On the contrast, MF scheme is better than ZF scheme in the low SNR regime. Simulation results corroborate the analytic results.

This work considers the physical-layer security of a wiretap channel, where a transmitter communicates with a receiver using the precoding-aided spatial modulation (PSM) in the presence of an unauthorized passive eavesdropper. We first analyze the security capability of the PSM and show that the PSM has the property of low-probability-of-interception (LPI). Based on the observations, we then design a secret PSM (SPSM), which represents a generalization of the PSM. We derive the upperbounds for the bit error rate (BER) of both the desired receiver and the eavesdropper when assuming communications over Rayleigh fading channels. Both the numerical results evaluated from the BER upper-bounds and the simulation results are provided to demonstrate the secrecy performance of the SPSM. Our studies show that the SPSM can significantly enhance the security of the PSM, in addition to inheriting all its merits.

With the proliferation of smart wireless devices in our homes, the cross-technology interference increasingly becomes an important issue. This paper presents a novel smart relay system, called SpaceHub, which leverages an multi-antenna relay node to mitigate cross-technology interference for all communicating devices which may only have single antenna. In SpaceHub, the relay node overhears wireless communications in the air, separates the collided signals, and forwards the separated (cleaned) signals to their intended receivers without a prior knowledge of the wireless signal structures. The core component of SpaceHub is a blind signal separator that constructs spatial filters using the angle-of-arrival information of collided signals. We have implemented SpaceHub on a software radio platform and our evaluation shows SpaceHub signal separator can suppress the interference up to 23dB, and is robust against the power or relative locations of interfering signals.

In this letter we determine the largest dynamic range within which any two nonnegative integers can be uniquely determined from their residues modulo a set of moduli. We also propose an efficient determination algorithm that extends a recent known result.

In this paper, we consider the problem of secure communications for a four-node system consisting of one source, one destination, one eavesdropper, and one helper. We investigate the question of which role should the helper act to improve the secrecy, to jam, or to relay. Two transmission schemes are investigated: (1) direct transmission scheme (DTS) with jamming and (2) relay transmission scheme (RTS). We consider both the path-loss and fading-in channel models and define a notion of distance normalized signal-to-noise-ratio (DN-SNR) to account for propagation. The ergodic secrecy rate (ESR) is adopted as the performance metric and semi-closed-form expressions of ESR for the two schemes are derived. Additionally, optimal power allocations in both low and high DN-SNR regimes are characterized analytically. We give the performance comparison of the two schemes from the perspective of energy efficiency in the low DN-SNR regime, and characterize the secrecy degree of freedom in the high DN-SNR regime. In the high DN-SNR regime, DTS provides higher secrecy rate compared with RTS, while in the low DN-SNR regime, RTS outperforms DTS. Furthermore, we show that eavesdropper's position impacts greatly on security.

Distance estimation using multifrequency phases measurement is a common practice in many areas of engineering. This method brings in the issue of phase ambiguity. Some Chinese remainder theorem (CRT) based phase unwrapping algorithms have been suggested to solve the problem, however, these algorithms either have high complexity or lack precision. In this paper, we propose an efficient algorithm to reconstruct the unknown distance from the contaminated wrapped phases. The proposed method can be separated into two stages. The first stage is to obtain the optimal estimate of the common remainder which is significant to the estimation. In the second stage, the indefinite distance is estimated by using the extended CRT. Simulations test the validity of the proposed algorithm.

This paper investigates the secret key generation from multiple cooperative sources. We assume that the public communication between the legitimate users has unlimited capacity. In this case, the secret key rate is the upper bound of a practical system with limited public communication. The random signals from the multiple helpers can help to create correlated Gaussian sources for the legitimate users to generate secret key, and only local channel state information (CSI) is needed by the helpers to cooperate with others. The power allocation between the helpers is studied with a total transmit power constraint, which results in a non-convex optimization problem. A high efficiency sub-optimal solution is proposed. And even when the legitimate users have no idea about the eavesdropper, the scheme still can help the system to achieve fairly good performance.

In this paper, we propose a new blind carrier frequency offset (CFO) estimation method for orthogonal frequency division multiplexing (OFDM) with multi-antenna receiver. The proposed method is one-shot and works with only a single OFDM block, which differs from the existing works for multi-antenna receiver. We show that, the proposed method not only supports fully loaded transmission, but also outperforms the existing maximum likelihood estimator for multi-antenna receiver. The numeral results are provided to corroborate the proposed studies.

In this poster, we present a novel spectrum monitor, named AirEye, that monitors a wide spectrum band using only a narrowband radio. Unlike previous work, AirEye blindly extracts cyclic features from received waveform and performs classification without any prior knowledge on the transmitted signals. Although AirEye uses only a narrowband radio, it can still identify any signal that is wider than the radio bandwidth. Finally, AirEye exploits the signal sparsity in both radio and cyclic frequency dimensions to significantly speedup the feature extraction.

In this paper, we address the problem of distributed angle estimation in wireless sensor localization system. Given that the practical limitations on size and cost, i.e., anchor node cannot equip a complicated antenna or antenna array, we devise an alternative measure based on a fixed-spacing two-antenna equipment. Through the multiple frequencies tuning, a virtual non-uniform linear array, called multiple frequencies synthetic array (MFSA), can be rebuilt independently at each sensor node. We first provide in theory the angle unambiguity conditions for such virtual array and then propose two different algorithms to achieve the distributed angle of departure (AOD) estimation. The first algorithm is based on the spectral searching technique, which is an improved version of the conventional rank reduction estimator (RARE) and has the same performance but less computational complexity. To further alleviate the computational burden at sensor node end, we convert the above angle estimation into a congruence problem and provide another closed-form solution based on Chinese remainder theorem (CRT). We also derive the Cramer-Rao bound for the MFSA and demonstrate theoretically that the latter algorithm from the perspective of cumulative circular distance is suboptimal when compared with the former one. Numerical examples are provided to show the validity of the proposed algorithms and the corresponding conclusions.

In this paper linear precoders for non-cooperative transmitters and iterative multiuser detectors (MUD) for the receiver are jointly designed to achieve the individual quality-of-service (QoS). An evolutional analysis framework is first developed for predicting and tracking the performance evolution for each user along iterations. This semi-analytical tool then leads to a joint QoS and quality-of-convergence (QoC) constrained precoder design problem formulation that is complicated and non-convex. Due to the competitive nature of a multiaccess system, a game-theoretic reformulation is adopted to reveal the underlying partial convexity structure of the problem, which further facilitates the development of an efficient iterative solver for the problem. Extensive simulation results are given to support the mathematical development of the problem.

Cooperative beamforming and jamming are two efficient schemes to improve the physical-layer security of a wireless transmission in the presence of a passive eavesdropper. However, in most works they are discussed separately. In this paper, we propose a joint cooperative beamforming and jamming scheme to enhance the security of a cooperative relay network, where some intermediate nodes adopt distributed beamforming while the others jam the eavesdropper, simultaneously. Subjected to the more practical individual power constraint of each node, we propose a null-space beamforming based secrecy strategy. The beamformer design can be optimized by a bisection method and second-order convex cone programming (SOCP). Simulations show the joint scheme greatly improves the security.

In this paper, we propose a novel angle of departure (AOD) aided sensor localization algorithm. Through the multiple frequency tuning technique at a fixed-spaced two-antenna anchor node, a non-uniform linear array can be rebuilt at each ground sensor node. We convert the angle estimation into a real number reconstruction by Chinese remainder theorem (CRT) and then provide a new algorithm to solve the congruence problem. Compared with the conventional spectral searching algorithms, the proposed one is computationally efficient and also performs much better than other CRT reconstruction algorithms. The validity and the advantages of the proposed algorithm is proved by numerical simulations.

In this paper, we consider a random wireless sensor network where the sensor nodes are distributed randomly and form clusters to cooperatively transmit data packets using cooperative multi-input-multi-output (CMIMO) technique. We focus on analyzing the overall system performance in terms of packet error rate (PER). And then propose a new node sleep strategy to minimize the overall energy consumption. We take the random distribution of sensor nodes into consideration and get a closed form of overall PER expression that simplifies the overall energy consumption optimization. We analyze the tradeoff between the overall energy consumption and sensor nodes sleep rate. The simulation results corroborate our analysis and show that the proposed sensor node sleep strategy has significant energy saving compared with other transmission schemes.

A distributed localization method has been proposed recently based on a novel concept of angle of departure (AOD) to estimate the angle information and achieve localization. Based on the AOD estimation, we introduce a synthetic uniform circular array (SUCA) synthesized by a rotary antenna to get the distributed localization of the sensors in multi-path environments. The rotated operation of antenna can create the SUCA with a larger aperture to deal with AOD of multi-path components (MPCs) and relaxes the condition that array aperture should be greater than the number of MPCs. This method only relies on radio transceivers without requiring extra measuring equipments, and the sensor nodes conduct localization in a completely distributed manner instead of centralized processing.

This letter investigates a novel two-stage cooperative scheme to secure the communication system with one source, one destination and multiple helpers. Herein, the source mixes the confidential messages with the interferences transmitted by the helpers and destination. Since the helpers and destination serve to suppress interferences, the destination can acquire an interference-free signal, however the eavesdropper is still confused. This scheme can achieve positive secrecy rate even when the eavesdropper's channel is much better than the legitimate link, and only requires local channel state information (CSI) and a few parameters of the main link. An efficient sub-optimal algorithm for the majorization of system parameters is proposed to avoid global search and the practical case without eavesdropper's CSI is also considered. Simulation results demonstrate the effectiveness of the proposed scheme and algorithm.

This paper considers random wireless sensor networks where nodes are distributed randomly and form clusters to transmit the packets to relay clusters using cooperative multi-input-multi-output (CMIMO) technique. First, we study CMIMO energy consumption and divide it into intra-cluster energy consumption and inter-cluster energy consumption. Then we focus on analyzing the system performance in terms of overall packet error rate (PER) and energy consumption. Based on system performance metrics, we propose a new node sleep strategy, where overall energy consumption is minimized by coordinating inter-cluster transmitting energy consumption and the number of sensor nodes in activation. Compared to existing works, our contributions are (1) we consider random distribution of nodes and get a closed-form expression of overall PER that simplifies the energy minimization problem; (2) we analyze the tradeoff between overall energy consumption and nodes active rate. In simulation, we investigate the relationships among nodes active rate, inter-cluster transmitting energy consumption and the overall energy consumption. Furthermore, we discuss how these parameters are affected by the nodes density, the inter-cluster transmitting distance, the cluster radius and the intra-cluster energy consumption. Finally, we validate that the proposed nodes sleep strategy has significant energy savings compared with non-sleep cooperative transmission and direct transmission.

A new angle of departure (AOD) aided distributed localization approach for wireless sensor node is proposed in this paper. An L-shaped antenna array is arranged on anchor node end and the ground single antenna sensor node conduct its own line of sight AOD estimation for self-localization. Considering the limited degree of freedom provided by the anchor node can not guarantee a successful recognition to the LOS signal component in multipath environment, we adopt the minimum redundancy configuration. Via the intrinsic character of wireless channel, the maximum degree of freedom through performing two-dimension joint difference co-array operation can be obtained at sensor node end. Therefore, the sensor node can identify the LOS signal component in a very high probability with a rebuild degree of freedom increased virtual array. The validity of proposed methods are verified by numerical examples.

In this paper, we propose an energy-efficient cooperative geographic routing (ECGR) to reach energy-efficient routing in wireless sensor networks(WSN). ECGR fully takes advantage of cooperative diversity and geographic routing. At physical layer, the sensor nodes cooperatively transmit the same packet to achieve farther transmission distance of each hop. While at the network layer, ECGR adaptively selects the appropriate cooperative nodes to form forwarding clusters to forward the packet when we consider energy consumption and geographic information of the sensor nodes. In order to fully assess the energy consumption, we take circuit energy consumption of the sensor nodes into consideration. According to the description above, we increase the transmitting distance of each hop but decrease the hop number. Meanwhile, the overall network energy consumption is reduced and balanced among nodes to extend the life of the network.

In multiple-input multiple-output (MIMO) systems, transmit antenna selection is a very promising technique for reducing implementation cost and computational complexity. In this paper, we propose two novel fast near-optimal antenna selection algorithms based on channel capacity maximization, whose core idea is to use an effective iterative process to reduce computational complexity and retain near-optimal performance. Compared with the conventional algorithm, the proposed algorithms have lower computational complexity and achieve almost the same capacity and bit-error rate (BER) performance as the optimal one. In particular, the BER performance gain of the proposed algorithms is much larger than the conventional algorithms in correlated fading channels. Finally, computer simulations are presented to validate and demonstrate performance of our algorithms.

Traditional channel quantization based methods for encryption key generation usually suffer from the quantization error which may decrease the key agreement ratio between authorized users. In this paper, we make use of the reciprocity of the wireless channel in time-division duplex (TDD) mode, and adopt a closed-form robust Chinese remainder theorem (CRT) to extract the encryption key from the noisy channel estimations. The channel coefficients are regarded as the remainders in robust CRT, and the key is generated from the quotient output of the robust CRT. In addition, a remainder selection procedure is proposed to further improve its performance. Simulations demonstrate the effectiveness of the proposed method.

In this paper, we propose a distributed angle estimation method for wireless sensor network localization with multipath fading. The multiple antenna system is equipped at the anchor and the angle of departure (AOD) can be estimated individually at each sensor node with single antenna system. Further, we exploit the space diversity to improve the estimation performance by deploying multiple parallel arrays at the anchor. Analysis and simulations demonstrate the effectiveness of our method.

In this paper, an energy-efficient cooperative geographic routing (ECGR) is proposed for Wireless Sensor Networks(WSN). ECGR fully takes advantage of cooperative diversity and "multi-sensor diversity" to reach energy-efficient routing. At physical layer, thanks to the high redundancy of the nodes in WSN, the nodes that have correctly decoded the packet are selected to realize "multi-sensor diversity" gain, and these nodes form a new forwarding cluster in a distributed way to obtain transmit diversity. At the network layer, based on the geographic routing, ECGR makes the packet always rout toward the destination and avoids diverging routes, simultaneously. In this way, we increase the transmitting distance of each hop, meanwhile, the overall network energy consumption is reduced and are balanced among the sensor nodes to extend the life of the network. We also discuss an appropriate packet error rate (PER) to optimize average transmitting distance.

Self-localization system of wireless sensor networks based on angle of departure (AOD) is studied in this paper. In AOD model, anchor node with multi-antenna transmits orthogonal pilot signals to sensor node with single antenna, which entitles the sensor node to function as equipping multi-antenna. Given that the limited number of antenna at anchor nodes will result in degree of freedom (DOF) deficiency at sensor node when dealing with more multipath components (MPC), we adopt a novel method without requiring extra antennas. The proposed algorithm simultaneously includes the oscillator mismatch between anchor node and sensor node, i.e., carrier frequency offset (CFO). With the aid of anchor's movement and CFO, the equivalent antenna array at sensor node is expended by synthetic aperture procedure to a much larger one, which subsequently improve the estimation ability to MPCs. In addition, the close-form solutions of CFO and AOD are also derived. The effectiveness and performance of proposed algorithm are demonstrated by numerical simulations.

A novel distributed angle estimation method for wireless sensor network localization is proposed in this paper. The anchor emits two linear frequency modulation waves simultaneously using its equipped two antenna elements, while the angle of departure of the emitted waves can be estimated independently at each sensor. The method only relies on radio transceivers and requires no time or carrier frequency synchronization between the transceivers. It is also shown that the method can be improved to applied to mobile networks. Besides, the performance analysis and simulations are both presented to evaluate the proposed approach.

The Radio Interferometric Positioning System (RIPS) provides a localization method with high accuracy and simple hardware configuration for sensor networks by means of measuring the phase difference of the interference signal. However, due to the periodicity of phase, it is hard to determine the actual distance difference only from a single phase measurement. To solve the problem, RIPS makes multiple measurements at different frequencies so as to convert phase difference to distance difference, which is a computationally intensive searching process and not suitable for the energy-constrained wireless sensor nodes. In this paper, we propose an efficient ranging method based on Chinese Remainder Theorem (CRT). Meanwhile, we utilize some properties of the coefficients in the CRT algorithm to avoid the over-sensitivity of the traditional CRT, which increases the robustness of the algorithm. We apply this robust CRT algorithm to the ranging process which calculates the distance difference directly in a closed form equation and therefore reduces the response time and energy consumption of the ranging procedure.

A novel distributed TDoA (Time-Difference-of-Arrival) estimation method for wireless sensor networks (WSN) is proposed in this letter. Linear frequency modulation (LFM) waves are emitted from two anchors simultaneously to create an interference field. Through the frequency measurement of local RSSI (Received Signal Strength Indication) signal, the TDoA is estimated independently at each sensor to detect range difference from the sensor to the two anchors. Furthermore, an extended method applied to mobile sensors is also presented. The proposed method only relies on radio transceivers and requires no time synchronization for sensors. Simulations results demonstrate the effectiveness of our method.

Power saving in wireless sensor networks (WSNs) has been the focus of much recent research due to the fact that the nodes are usually battery-powered. Wireless communication accounts for a strikingly high proportion of the total power consumption, so we want to reduce the power consumption by adopting a low-power transceiver in the physical layer. IEEE 802.15.4 is a popular communication standard for WSNs which has many good features that can be used for power-saving. In this paper, we propose a simple transceiver for IEEE 802.15.4. It utilizes the constant-envelope feature of the offset quadrature phase shift keying (O-QPSK) signal with half-sine shaping defined in the standard to simplify the structure of the transceiver. Compared with conventional transceivers, the proposed transceiver adopts a hard-limiter rather than a digital-to-analog converter (DAC) and an analog-to-digital converter (ADC), which results in a simpler structure and lower power consumption, furthermore, the correlation operation could be efficiently implemented just by a reversible counter. The performance of the proposed transceiver is effectively demonstrated by both computer simulation and hardware test.

A novel distributed TDoA (Time-Difference-of-Arrival) estimation method for wireless sensor networks (WSN) in multipath environment is proposed in this paper. For the conventional narrow band system usually adopted in the wireless sensors, the frequency-hopping technique can be utilized to perform the estimation of the wide band frequency-domain channel response, by which the super-resolution TDoA estimation is conducted independently at each sensor to detect range difference from the sensor to the two anchors. The proposed method only relies on the conventional narrow band radio transceiver and each sensor conducts range estimation independently without any information exchange or time synchronization requirement, which is a distributed range estimation method more suitable for WSN.

In this paper, we propose an oblique projection-based robust linear receiver for spatial multiplexing systems in multi-cell environments. In our receiver design, we first obtain an oblique projection operator by using the received data, and then use such operator to extract the desired signal subspace and cancel the interference-plus-noise subspace from the received signals. After suppressing the unknown cochannel interference (CCI) included in the interference-plus-noise subspace, we further use zero-forcing (ZF) receiver to suppress the coantenna interference (CAI) and detect the desired transmitted symbols in the desired signal subspace. Finally, simulation results show that the proposed linear receiver obtains significant performance improvement over ZF receiver without considering the unknown CCI in the practical environments.

A novel distributed localization method for wireless sensor networks (WSN) is proposed in this paper. Linear frequency modulation (LFM) waves are emitted from two anchors simultaneously to create an interference field. Through the frequency measurement of local RSSI (Received Signal Strength Indication) signal, the TDoA (Time-Difference-of-Arrival) is estimated independently at each sensor to detect range difference from the sensor to the two anchors, by which the position can be determined. Furthermore, an extended method applied to mobile sensors is also presented. The proposed method only relies on radio transceivers and requires no time synchronization for sensors. Simulations results demonstrate the effectiveness of our method.

Two novel algorithms which exploit the fourth-order statistics are proposed for DOA and range estimation of the near-field narrow-band sources. Compared with most proposed methods which can identify only p sources with a (2p + 1)-element ULA (uniformly linear array), the proposed methods can identify 2p or 2p − 1 sources with the same one. Moreover, our methods calculate much fewer fourth-order statistics than conventional ones. Simulation results show that our two ESPRIT-based methods also provide improved performance over conventional ones because of more efficient use of received signals.

Based on the finite alphabet property of the communication signals and the subspace theory, a blind source separation algorithm for co-channel signals is presented. A comparison between the proposed method and MUSIC algorithm is made. Although their application backgrounds are different, their principles are similar. On the viewpoint of MUSIC algorithm, a new explanation for the proposed approach is given. Based on the subspace perturbation theory, the bit error rate (BER) performance analysis is also presented. Some key parameters, such as channel vector correlation coefficient, signal vector correlation coefficient, number of antennas and length of code vectors, are discussed. Finally, simulation results confirm our performance analysis.

Cyclic delay diversity (CDD) is a low-complexity transmit diversity technique for coded orthogonal frequency division multiplexing (OFDM), which transforms a mutiple-input channel into an equivalent single-input channel with increased frequency selectivity and provides additional frequency diversity. However, it makes channel estimation more difficulty due to the increased frequency selectivity. In this paper, we focus on the direct estimation of the equivalent single-input channel for CDD-OFDM systems. We first propose a cyclic cross-correlation channel estimation scheme based on the equispaced constant-modulus pilot structure. Using the statistical parameters of the channel and noise derived by the result of the cyclic cross-correlation channel estimation, we propose an improved channel estimation scheme based on the Wiener filter to reduce the estimation error further. Computation simulations are given to demonstrate the effectiveness of two proposed channel estimation schemes for CDD-OFDM systems.

In cooperative communications, due to distributed nature, cooperative transmission may not be either time or frequency synchronized. In this paper, we propose computationally efficient minimum mean square error (MMSE) and MMSE decision feedback equalizer (MMSE-DFE) equalizers for cooperative communication systems when multiple time offsets and frequency offsets present, where the equalization matrix inverses do not need to be retaken every symbol. Our proposed equalization methods apply to linear convolutively coded cooperative systems, where the linear convolutive space-time coding is used to achieve the full cooperative diversity when there are timing errors from the cooperative users or relay nodes, i.e., asynchronous cooperative communication systems.

Based on the ESPRIT-like method, a closed-form CDMA signal and DOA estimation approach without the knowledge of space-time channel and training sequence is presented in this paper. An auxiliary matrix is constructed by exploiting the special structure of the antenna array. The symbol vector and DOA are obtained from an eigenvalue-eigenvector pair of the auxiliary matrix even under imperfect carrier recovery. The carrier offset can be acquired easily by exploiting the finite alphabet property of the transmitted symbols. In comparison with conventional space-time linear multiuser detector, in which the knowledge of space-time channel is assumed known, the proposed method has the advantage of lower computation at the expense of little performance degradation. Finally, numeral simulations are presented.

Based on the subspace method, a closed-form CDMA signal and DOA estimation approach without the knowledge of space-time channel and training sequence is presented. An auxiliary matrix is constructed by exploiting the special structure of the antenna array. Then the symbols instead of their signal subspace are achieved by eigendecomposition of the auxiliary matrix. Therefore, the puzzle of separating the different users' signal from their signal subspace in conventional blind symbol estimation method is avoided. In comparison with the conventional space-time linear multiuser detector, in which the knowledge of space-time channel is assumed to be known, the proposed method has the advantage of lower computation without degrading the near-far resistance performance. Finally, numeral simulations are presented.

Based on the time-frequency distributions, a novel subspace method is proposed in this paper to estimate the directions-of-arrival (DOA) of non-stationary signals. The array time-frequency correlation matrix C/sub x/, instead of the traditional correlation matrix R/sub x/, is constructed and eigen-decomposed to separate the signal subspace and the noise subspace. By processing the observed data in both spatial domain and time-frequency domain simultaneously, the "signal selectivity" is achieved. Therefore DOA of signals with identical frequency band and time slot but with different time-frequency signatures can be extracted one by one, and the estimation performances are significantly improved over the conventional method. It is also proven herein that the traditional subspace methods are just the low-dimensional special cases of the proposed approach.

A beamforming algorithm suitable for space-time Rake receiver in CDMA system is addressed. The algorithm is the optimal solution in the sense of minimum variance when interference number approaches to infinite. Simulation results demonstrate that the proposed algorithm approximates to the Capon's MVDR (minimum variance distortionless response) beamformer when the interference number is much more than the number of array elements. In comparison with Capon's, the algorithm has the advantages of lower computation and no coherent problem. Based on the method described above, a space-time searcher and a spatial frequency detector are presented, by which a beam tracking algorithm is proposed. Simulation results demonstrate that the algorithm can efficiently track the direction of desired signals and has the advantages of lower static error and better dynamic tracking performance.