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.

Arterial blood pressure (ABP) holds substantial promise for proactive cardiovascular health management. Notwithstanding its potential, the invasive nature of ABP measurements confines their utility primarily to clinical environments, limiting their applicability for continuous monitoring beyond medical facilities. The conversion of photoplethysmography (PPG) signals into ABP equivalents has garnered significant attention due to its potential in revolutionizing cardiovascular disease management. Recent strides in PPG-to-ABP prediction encompass the integration of generative and discriminative models. Despite these advances, the efficacy of these models is curtailed by the latent space shift predicament, stemming from alterations in PPG data distribution across disparate hardware and individuals, potentially leading to distorted ABP waveforms. To tackle this problem, we present an innovative solution named the Latent Space Constraint Transformer (LSCT), leveraging a quantized codebook to yield robust latent spaces by employing multiple discretizing bases. To facilitate improved reconstruction, the Correlation-boosted Attention Module (CAM) is introduced to systematically query pertinent bases on a global scale. Furthermore, to enhance expressive capacity, we propose the Multi-Spectrum Enhancement Knowledge (MSEK), which fosters local information flow within the channels of latent code and provides additional embedding for reconstruction. Through comprehensive experimentation on both publicly available datasets and a private downstream task dataset, the proposed approach demonstrates noteworthy performance enhancements compared to existing methods. Extensive ablation studies further substantiate the effectiveness of each introduced module.

Abstract Here, fast time‐varying channels of high‐mobility vehicle‐to‐vehicle communications for massive multiple‐input multiple‐output orthogonal frequency division multiplexing systems are considered. Large‐scale uniform linear arrays are configured at the transmitter and receiver to separate multiple angle domain Doppler frequency offsets based on transmit and receive beamforming with high spatial resolution. Then, each beamforming branch comprises only one dominant Doppler frequency offset. Next, the conventional channel estimation method is performed for each beamforming branch, and carry out maximum‐ratio‐combining for data detection. Power spectrum density and Doppler spread of the equivalent link between the transmitter and receiver are derived and regarded as the criterion for assessing the residual channel time variation caused by limited antennas in practice. Interestingly, a scaling law between the asymptotic Doppler spread and the number of transceiver antennas shows that asymptotic Doppler spread is proportional to the maximum Doppler frequency offset and decreases at the rate of , where and are the number of transmit and receive antennas, respectively. Simulation results confirm the validity of the proposed Doppler suppression framework in high‐mobility vehicle‐to‐vehicle communications.

A channel time variation suppression scheme based on beamforming is proposed for high-mobility orthogonal frequency division multiplexing (OFDM) downlink transmissions. The residual channel time variation after Doppler shift compensation by finite resolution receive beamforming can be measured by the Doppler spread. The interchannel interference (ICI) due to the time-varying channel is then analyzed and the relation between the signal-to-interference ratio (SIR) and Doppler spread is given. Based on the derived Doppler spread and ICI, a beamforming network optimization scheme is proposed to reduce the channel time variation. A closed-form solution is first obtained to minimize the average ICI, which exploits the structure of a tridiagonal Toeplitz matrix. Next, an optimization problem is formulated to minimize the maximum Doppler spread to further verify the impact of average ICI on channel time variation. The sequential parametric convex approximation (SPCA) algorithm is exploited to solve the non-convex min-max problem. Numerical results verify the theoretical analysis.

In high-mobility massive multiple-input multiple-output (MIMO) systems, Doppler shifts compensation can be combined with beamforming network to effectively suppress the channel time variation. The key of the beamforming network lies in the optimization of the common configurable amplitudes and phases (CCAP) parameter. In this paper, we reveal more insights of this approach by conducting the in-depth analysis. First, we demonstrate that the CCAP parameter optimizes the beamforming network to reduce channel time variation and approximates in a semi-sinusoidal form. Then, a scaling law between the asymptotic Doppler spread and the number of antennas M is derived, revealing that the asymptotic Doppler spread decreases at a rate of 1/M. We further prove that the optimal CCAP parameter obtained from Jakes' channel model can be directly applied to more general cases, while the inverse proportionality between the resulting asymptotic Doppler spread and the number of antennas remains valid. Numerical results confirm the correctness of the theoretical analysis.

Unmanned aerial vehicles (UAVs) are playing an important role in wireless networks, due to their cost effectiveness and flexible deployment. Particularly, integrating UAVs into existing cellular networks has great potential to provide high-rate and ultra-reliable communications. In this paper, we investigate the uplink transmission in a cellular network from a UAV using non-orthogonal multiple access (NOMA) and from ground users to base stations (BSs). Specifically, we aim to maximize the sum rate of uplink from UAV to BSs in a specific band as well as from the UAV's co-channel users to their associated BSs via optimizing the precoding vectors at the multi-antenna UAV. To mitigate the interference, we apply successive interference cancellation (SIC) not only to the UAV-connected BSs, but also to the BSs associated with ground users in the same band. The precoding optimization problem with constraints on the SIC decoding and the transmission rate requirements is formulated, which is non-convex. Thus, we introduce auxiliary variables and apply approximations based on the first-order Taylor expansion to convert it into a second-order cone programming. Accordingly, an iterative algorithm is designed to obtain the solution to the problem with low complexity. Numerical results are presented to demonstrate the effectiveness of our proposed scheme.

The problem of power allocation with uncoordinated cooperative jamming is addressed in this paper to enhance the physical layer security of the single-input-single-output wiretap channel with single-antenna jammers. Differing from the existing works concerning the secrecy rate maximization, this paper studies the problem of minimizing the secrecy outage probability with fixed secrecy rate, where the channel state information concerning the eavesdropper is only known statistically. This problem is formulated as an optimization problem of power allocation for the jamming signals. We prove that the optimization problem is convex in essence, and the optimal solution is thus conveniently obtained by using the methods of golden section search and bi-section search. Simulation results show that the proposed approach is very efficient and can significantly enhance the physical layer security by reducing the secrecy outage probability.

In this paper, we investigate the uplink transmission in a cellular network from a UAV and ground users to ground base stations (BSs). Specifically, we aim to maximize the sum rate of the uplink from the UAV to ground BSs in a specific idle frequency band as well as from the co-channel users to their associated BSs by optimizing precoding vectors at UAV. To mitigate the interference, we apply successive interference cancellation (SIC) not only to the BSs connected with UAV using non-orthogonal multiple access (NOMA) for transmission, but also to other BSs communicating with ground users in the same band. The precoding optimization problem with constraints on the SIC decoding and the uplink transmission rate is formulated, which is non-convex and intractable. Thus, we introduce auxiliary variables and apply first-order approximations based on Taylor expansion to convert it into a second-order cone programming. An iterative algorithm is proposed with low complexity to calculate the solution to the non-convex precoding optimization problem. Numerical results demonstrate the effectiveness of our proposed scheme.

In this paper, we consider the frequency synchronization issue in orthogonal frequency division multiplexing distributed antenna systems. There may exist multiple carrier frequency offsets (CFOs) between the transmitter and distributed receive antennas. To solve the multi-CFO estimation problem, we first derive the blind maximum likelihood estimator, which has superior estimation performance, but exhibits high computational complexity. Furthermore, we develop a blind pairing-based efficient estimator (PBEE), which divides the multiple antennas into pairs of two. The two CFOs in each pair are jointly estimated with a carefully designed cost function, which proves to be exactly a cosine function parameterized by the two CFOs even with the effect of noise. Consequently, the joint estimation of the two CFOs can be simplified to the one-dimensional search optimization problem. The PBEE can achieve better CFO estimation performance than the existing competitors. From the theoretical mean square error (MSE) analysis of PBEE, we further derive the optimal antenna pairing scheme by minimizing the signal-to-noise ratio degradation caused by the uncompensated residual CFOs. Finally, the Cramér-Rao bound of CFO estimation is derived and numerical results are provided to corroborate the proposed studies.

Communications in high-mobility environments have received a lot of attention recently. In this paper, fast time-varying channels for massive multiple-input multiple-output (MIMO) systems are addressed. We derive the exact channel power spectrum density (PSD) for the uplink from a high-speed railway (HSR) to a base station (BS) and propose to further reduce the channel time variation via beamforming network optimization. A large-scale uniform linear array (ULA) is equipped at the HSR to separate multiple Doppler shifts in the angle domain through high-resolution transmit beamforming. Each branch comprises a dominant Doppler shift, which can be compensated to suppress the channel time variation, and we derive the channel PSD and the Doppler spread to assess the residual channel time variation. Interestingly, the channel PSD can be exactly expressed as the product of a pattern function and a beam-distortion function. The former reflects the impact of array aperture and is the converted radiation pattern of ULA, while the latter depends on the configuration of the beamforming directions. Inspired by the PSD analysis, we introduce a common configurable amplitudes and phases (CCAP) parameter to optimize the beamforming network, by partly removing the constant modulus quantized phase constraints of matched filter (MF) beamformers. In this way, the residual Doppler shifts can be ulteriorly suppressed, further reducing the residual channel time variation. The optimal CCAP parameter minimizing the Doppler spread is derived in a closed form. Numerical results are provided to corroborate both the channel PSD analysis and the superiority of the beamforming network optimization technique.

To estimate time-varying MIMO channel at base station, traditional downlink (DL) channel restoration schemes usually require the reconstruction for the covariance of downlink process noise vector, which is dependent on DL channel covariance matrix (CCM). However, the acquisition of the CCM leads to extremely high overhead in massive MIMO systems. To tackle this problem, we propose a novel scheme for DL channel tracking in this paper. First, by utilizing virtual channel representation (VCR), we develop a dynamic uplink (UL) massive MIMO channel model with the consideration of off-grid refinement. Then, a coordinate-wise expectation maximization (EM) algorithm is adopted for capturing model parameters, including the spatial signatures, time-correlation factors, off-grid bias, channel power, and noise power. By exploiting the UL/DL angle reciprocity, the spatial signatures, time-correlation factors and off-grid bias of the DL channel model can be reconstructed with the knowledge of UL. However, channel power and noise power are closely related with the carrier frequency, which cannot be perfectly inferred from the UL. Instead of discovering these two parameters with dedicated training, we resort to the optimal Bayesian Kalman filter (OBKF) method to accurately track the DL channel with partial prior knowledge. At the same time, the model parameters will be gradually restored. Specially, the factor-graph and the Metropolis Hastings MCMC are utilized within the OBKF framework. Finally, numerical results are provided to demonstrate the efficiency of our proposed scheme.

In this paper, we consider a downlink orthogonal frequency division multiplexing system from a base station to a high-speed train equipped with fully/partly calibrated massive uniform linear antenna-array (ULA) in wireless environments with abundant scatterers. Multiple Doppler frequency off- sets (DFOs) stemming from intensive propagation paths together with transceiver oscillator frequency offset (OFO) result in a fast time-varying frequency-selective channel. We develop an angle domain carrier frequency offset (CFO, a general designation for DFO and OFO) estimation approach. A high-resolution beamforming network is designed to separate different DFOs into a set of parallel branches in angle domain such that each branch is mainly affected by a single dominant DFO. Then, a joint estimation algorithm for both maximum DFO and OFO is developed for fully calibrated ULA. Next, its estimation mean square error performance is analyzed under inter-subarray mismatches. To mitigate the detrimental effects of inter-subarray mismatches, we introduce a calibration-oriented beamforming parameter and develop the corresponding modified joint estimation algorithm for partly calibrated ULA. Moreover, the Cramér-Rao lower bound of CFO estimation is derived. Both theoretical and numerical results are provided to corroborate the proposed method.

In this paper, we apply angle-domain Doppler compensation for high-mobility wideband massive multi-input multi-output (MIMO) uplink communications. The time-varying multipath channel is considered between high-speed terminal and static base station (BS), where multiple Doppler frequency offsets (DFOs) are associated with distinct angle of departures (AoDs). With the aid of large-scale uniform linear array (ULA) at the transmitter, we design a beamforming network to generate multiple parallel beamforming branches, each transmitting signal pointing to one particular angle. Then, the transmitted signal in each branch will experience only one dominant DFO when passing over the time-varying channel, which can be easily compensated before transmission starts. We theoretically analyze the Doppler spread of the equivalent uplink channel after angle-domain Doppler compensation, which takes into account both the mainlobe and sidelobes of the transmit beam in each branch. It is seen that the channel time-variation can be effectively suppressed if the number of transmit antennas is sufficiently large. Interestingly, the asymptotic scaling law of channel variation is obtained, which shows that the Doppler spread is proportional to the maximum DFO √ and decreases approximately as 1/√(M) (M is the number of transmit antennas) when M is sufficiently large. The numerical results are provided to corroborate the proposed scheme.

In this paper, we design a novel angle-domain adaptive filtering (ADAF)-based frequency synchronization method for massive multiple-input multiple-output (MIMO) multiuser uplink, which is suitable for users with either separate or overlapped angle-of-arrival (AoA) regions. We first introduce the angle-constraining matrix (ACM), which consists of a set of selected match-filter (MF) beamformers pointing to the AoAs of the interested user. Then, the adaptive beamformer can be acquired by appropriately designing the ADAF vector. Such beamformer can achieve a two-stage adaptive multiuser interference (MUI) suppression, i.e., inherently suppressing the MUI from distant users by ACM in the first stage and substantially mitigating the MUI from adjacent overlapping users by ADAF vector in the second stage. For both separate and mutually overlapping users, the carrier frequency offset (CFO) estimation and subsequent data detection can be performed individually for each user, which reduces the computational complexity. Moreover, ADAF is rather insensitive to imperfect AoA knowledge, making itself promising for multiuser uplink transmission. Numerical results are provided to show the effectiveness of the proposed method, as well as its superiority over existing competitors.

In this letter, we take the initiative in adaptively determining the optimal temporal filter (TF) length for space-time equalization (STE) schemes, where overfitting may occur under too large TF length. We specifically consider the system without employing cyclic-prefix such that the spectral efficiency could be maintained. Based on the delicately derived connection between the mean square error (MSE) of equalized training symbols and unknown data symbols, the MSE of the latter can be predicated and serves as the decision metric for determining the optimal TF length. Numerical results demonstrate that the proposed STE scheme with TF of adaptively optimized length can work properly, even in the presence of cochannel interference.

Pilot contamination attack is an important activity of active eavesdropping conducted by a malicious user during channel training phase. This attack is potentially harmful to the physical layer security. In this paper, motivated by the fact that frequency asynchronism could introduce divergence of the transmitted pilot signals between intended user and attacker, we propose a new uncoordinated frequency shift (UFS) scheme for detecting pilot contamination attack in multiple antenna system. During the reverse training phase of the UFS scheme, the legitimate user Bob deliberately introduces multiple random frequency shifts in the publicly known pilot sequence. Since eavesdropper Eve has no knowledge of these random frequency shifts, it is almost impossible for her to pretend exactly like Bob. This provides the opportunity to detect the presence of Eve. An attack detection algorithm is then developed based on source enumeration method. Both the asymptotic performance analysis and numerical results are provided to verify the proposed detection scheme. The proposed scheme is also enhanced based on noise power estimation to cope with attacks from a multi-antenna Eve. Furthermore, the proposed UFS scheme is extended by introducing general parameterized phase shifts. It is demonstrated that the proposed UFS scheme can achieve comparable detection performance as the existing superimposed random sequence based scheme, without sacrifice of legitimate channel estimation performance.

In this paper, we propose a frequency synchronization scheme for multiuser orthogonal frequency division multiplexing uplink with a large-scale uniform linear array at base station (BS) by exploiting the angle information of users. Considering that the incident signal at BS from each user can be restricted within a certain angular spread, the proposed scheme could perform carrier frequency offset (CFO) estimation for each user individually through a joint spatial-frequency alignment procedure and can be completed efficiently with the aid of fast Fourier transform. A multi-branch receive beamforming is further designed to yield an equivalent single user transmission model for which the conventional single-user channel estimation and data detection can be carried out. To make the study complete, theoretical performance analysis of the CFO estimation is also conducted. We further develop a user grouping scheme to deal with the unexpected scenarios that some users may not be separated well from the spatial domain. Finally, various numerical results are provided to verify the proposed studies.

In this paper, we propose a Doppler pre-compensation scheme for high-mobility orthogonal frequency division multiplexing (OFDM) uplink, where a high-speed terminal transmits signals to the base station (BS). Considering that the time-varying multipath channel consists of multiple Doppler frequency offsets (DFOs) with different angle of departures (AoDs), we propose to perform DFO pre-compensation at the transmitter with a large-scale uniform linear array (ULA). The transmitted signal passes through a beamforming network with high- spatial resolution to produce multiple parallel branches. Each branch transmits signal towards one direction thus the transmitted signal is affected by one dominant DFO when passing over the time-varying channel. Therefore, we can compensate the DFO for each branch at the transmitter previously. Theoretical analysis for the Doppler spread of the equivalent uplink channel is also conducted. It is found that when the number of transmit antennas is sufficiently large, the time-variation of channel can be efficiently suppressed. Therefore, the performance will not degrade significantly if we apply the conventional time- invariant channel estimation and equalization methods at the receiver. Simulation results are provided to verify the proposed scheme.

This paper proposes a new nonadaptive (NADP) transmission scheme with adjustable power allocation based on the instantaneous channel state information (CSI) of the main channel for the multiple-input-single-output-single-eavesdropper (MISOSE) system. With the assistance of the adjustable power allocation ratio, we can improve the secure transmission performance under the constraints of secrecy outage probability (SOP) and upper bound rate (UBR). To verify the superiority of our new approach, we consider the multi-antenna communication systems with NADP scheme and give the optimal solution for achieving the maximum secrecy throughput based on a two-dimensional (2-D) searching method. In addition, a good suboptimal solution is also provided to reduce the time complexity of the optimal solution. Simulation results are provided and confirm that the proposed NADP scheme has significant advantages over the existing work especially when the transmit power is high.

This paper studies the artificial noise (AN) aided secure transmission design in a multiple-input- single-output multicast channel where a common message is transmitted to multiple receivers and only statistical channel state information of the eavesdropper is available. In this scenario, there may be no valid null space which allows the AN not to affect the legitimate receivers, and the traditional null-space AN scheme may not be applicable. To find the optimal design, we formulate a secrecy outage probability (SOP) constrained secrecy rate maximization problem which applies to an arbitrary number of the receivers. We adopt a novel approximation of the intractable SOP constraint and establish an efficient algorithm which solves the approximated problem to global optimality. The effectiveness of AN as well as the proposed solution is confirmed by simulation results. It is shown that the AN aided approach performs much better than pure beamforming even when there is no valid null space.

The artificial noise (AN) aided beamforming design in the MISOME (multiple-input, single-output, multiple-eavesdropper) wiretap channel is studied from the perspective of secrecy outage. Unlike many existing works which directly adopted the traditional null-space AN scheme, we start with a general assumption on the structure of the transmit signal, and seek to find the optimal structure by solving a secrecy outage probability (SOP) constrained secrecy rate maximization problem. By generalizing several existing conclusions regarding a single-antenna eavesdropper, we prove that the null-space AN scheme is indeed optimal for an arbitrary number of the eavesdropper's antennas from the perspective of secrecy outage. The power allocation problem is also studied and the closed-form optimal solution is obtained. It is found that the increase in the eavesdropper's antenna number is equivalent to requiring a smaller SOP.

In this paper, we propose a new channel tracking method for massive multiple-input multiple-output (MIMO) systems under both the time-varying and spatial-varying circumstance. With spatial-temporal basis expansion model (ST-BEM), the channel information is decomposed into the spatial information and gain information, where the former is determined by the central angle as well as the angular spread of the incoming signal. We first blindly track the central angle by the extended Kalman filter (EKF) and obtain the angular spread through Taylor series expansion of the steering vector. Then, the channel gain information can be estimated with only a few pilot symbols. Various numerical results are provided to demonstrate the effectiveness of the proposed method.

In this paper, two blind carrier frequency offset (CFO) estimators for orthogonal frequency division multiplexing (OFDM) with distributed multi-antenna receiver are designed. We first propose a pairing based efficient estimator (PBEE), where multiple CFOs are divided and then estimated in pairs of two with a carefully designed cost function. This cost function is proven to be exactly a cosine function parameterized by the two CFOs even with the effect of noise. Consequently, the CFOs estimate can be obtained in closed-form after a one-dimensional search. Moreover, in order to improve the estimation performance, we further develop the maximum likelihood (ML) estimator. The computationally inefficient multi-dimensional search of ML estimator can be solved by introducing an extra one-step adjustment to the PBEE. Both the two estimators support fully loaded transmissions, which can save the spectral efficiency. Numerical results are provided to corroborate the proposed studies.

In this paper, we address the orthogonal frequency division multiplexing (OFDM) downlink transmission in scenarios abundant of scatters when the high- speed rail (HSR), equipped with partly calibrated massive uniform linear array (ULA), is in high- speed motion relative to the base station. A high- resolution beamforming network is designed to separate multiple Doppler frequency offsets (DFOs) in spatial domain into a series of parallel beamforming branches, such that each branch is mainly affected by single dominant DFO, wherein the conventional carrier frequency offset (CFO) compensation and subsequent data detection could be carried out individually. In view of this, a joint- estimation algorithm is proposed to jointly estimate the CFO and equivalent channel of each beamforming branch. Moreover, the calibration- oriented beamforming parameter (COBP) is introduced to mitigate the detrimental effects in presence of inter-subarray uncertainties. Both numerical and theoretical results are provided to corroborate the effectiveness of the proposed method.

Large-scale multi-input multi-output (MIMO) technique has drawn considerable research interest recently. However, multiuser transmissions in large-scale MIMO systems would face challenging estimation and compensation for multiple carrier frequency offsets (CFOs) that co-exist at the receiver. In this paper, we design a new frequency synchronization scheme in multiuser orthogonal frequency division multiplexing uplink with the aid of scattered pilot symbols. We specifically consider a base station with a large number of antennas and propose to assign a number of scattered pilot subcarriers to each user. With sufficient spatial dimensions offered by the large number of antennas, the designed scheme could estimate CFO for each user individually and eliminate the necessity of the multidimensional search. Moreover, after the CFO estimation, the receive beamforming matrix is further designed for inter-user interference cancelation, which yields an equivalent single user transmission model. The conventional single user channel estimation and data detection can then be performed. Finally, the numerical results are provided to verify the proposed studies.

In this paper, we investigate the physical-layer security of slow fading wiretap channel with channel estimation errors. We aim to maximize the reliable secrecy rate under constraints of secrecy outage probability and reliability outage probability. To this end, we propose an adaptive (ADP) transmission scheme in which the communication rate and secrecy rate are adaptively adjusted based on the estimated imperfect channel state information (CSI) of the legitimate channel. The optimal solution is obtained by solving a single-variable maximization problem, where the objective function is log-concave. Numerical results are provided to verify our approach as well as to show the impact of imperfect CSI on the secrecy throughput.

In this paper, we propose a new frequency synchronization scheme for multiuser orthogonal frequency division multiplexing (OFDM) uplink with a large-scale uniform linear array (ULA) at base station (BS). Considering that the incident signal at BS from each user can be restricted within a narrow angular spread, the proposed scheme performs carrier frequency offset (CFO) estimation for each user individually through a joint spatial-frequency alignment procedure. The basic idea behind is that with sufficient spatial dimension, the multiuser interference (MUI) effect can be effectively mitigated via beamforming with the steering vectors corresponding to any direction of arrival (DOA) of each user. A multi-branch receive beamforming is further designed for each user which results in an equivalent single user transmission model and the conventional single-user channel estimation and data detection can be carried out. We show that the proposed CFO estimation can be applied efficiently with the aided of fast Fourier transform (FFT). The theoretical CFO estimation performance analysis is also conducted. Various numerical results are provided to verify the proposed studies.

This paper studies the dirty-paper coding (DPC) based secure transmission in a multiuser broadcast channel. Since the encoding order of DPC determines which information-bearing signals must be treated as noise by potential eavesdroppers, adopting DPC enables the accurate characterization of the intrinsic secrecy as well as secrecy outage of multiuser broadcasting. Furthermore, the information-bearing signals can be designed to provide secrecy in addition to supporting normal (unclassified) transmission. To show this, we consider the scenario where one user requests secure transmission and the other users request normal transmission, and propose a hybrid secure transmission scheme which combines zero-forcing DPC and artificial noise (AN). By solving the secrecy rate maximization problem under constraints on the secrecy outage probability and the normal communication rates, we find that in addition to supporting the normal transmission, the proposed scheme has the potential to achieve a secrecy rate close to that of the traditional AN-based beamforming.

In this paper, we propose a new blind carrier frequency offset (CFO) estimation method for multiuser orthogonal frequency division multiplexing (OFDM) uplink transmissions. The spatial multiplexing is supported in the considered model that allows the subcarriers to be simultaneously occupied by multiple users. We propose to assign different null subcarriers to different users and design algorithm that can perform blind CFO estimation for each individual user with the aid of large number of receive antennas, which then removes the necessity of multidimensional searching. Numerical results are provided to corroborate the proposed studies.

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 propose a new computationally efficient blind carrier frequency offset (CFO) estimator for multi-input multi-output orthogonal frequency division multiplexing systems. A cost function is carefully designed and can be exactly expressed as the superposition of very few harmonically related cosine waves even with the effect of the noise. Using this property, the minimization of the designed cost function can be solved in a quite computationally efficient manner without any exhaustive grid search procedure. It is seen that the proposed estimator can achieve comparable estimation performance as existing competitors with substantially reduced computational burden. Moreover, in order to improve the estimation performance, we further develop an enhanced CFO estimator by introducing an additional one-step adjustment. We find that the enhanced estimator can attain almost the same estimation performance as the existing maximum likelihood estimator but with a lower order of computational burden. We provide both numerical results and theoretical performance analysis to corroborate the proposed studies.

In this paper, we propose a new efficient blind carrier frequency offset (CFO) estimator for multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. A cost function is carefully designed which can be exactly expressed as a superposition of very few harmonically related cosine waves even with the effect of noise. By using this property, the minimization of the designed cost function can be solved in a quite computationally efficient manner without any exhausted grid searching procedure. We provide numerical results to corroborate the proposed studies. It is seen that the proposed estimator can achieve comparable estimation performance with existing competitors with substantially reduced computational burden.

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 study, for interleaved orthogonal frequency division multiple access uplink with multi‐antenna receiver, we propose two generalised carrier frequency offset estimators which, respectively, exploit the subspace theory and maximum‐likelihood (ML) criterion. We find that, as long as the numbers of multipaths from two of the users are smaller than the number of antennas at the receiver, both the proposed estimators support fully loaded transmissions. We also derive the theoretical performance lower bound for the proposed ML estimator. The numerical results are then provided, which corroborate the proposed studies.

In this study, the authors propose a blind carrier frequency offset (CFO) estimation method for the tile structure orthogonal frequency division multiple access (OFDMA) uplink with multi‐antenna receiver. They employ an iterative approach to extract the signal component for each user gradually and propose a carefully designed CFO estimator to update the CFO estimate during the iterative procedure. The key ingredient of the proposed method is using few subcarriers on both sides within each tile as the ‘guard subcarriers’, which can greatly mitigate the effect of multi‐user interference. The proposed method supports not only fully loaded transmissions, but also the generalised assignment scheme that provides the flexibility for dynamical resource allocation. The numerical results are provided, which indicate that the proposed method can almost converge to the analytical lower bound within a few iterative cycles. It is seen that the proposed method also outperforms the existing competitor with multi‐antenna receiver in terms of estimation performance, especially with few adopted blocks.

ABSTRACT Cognitive radio (CR) is a promising technique for future wireless networks, which significantly improves spectrum utilization. In CR networks, when the primary users (PUs) appear, the secondary users (SUs) have to switch to other available channels to avoid the interference to PUs. However, in the multi‐SU scenario, it is still a challenging problem to make an optimal decision on spectrum handover because of the the accumulated interference constraint of PUs and SUs. In this paper, we propose an interference‐aware spectrum handover scheme that aims to maximize the CR network capacity and minimize the spectrum handover overhead by coordinating SUs’ handover decision optimally in the PU–SU coexisted CR networks. On the basis of the interference temperature model, the spectrum handover problem is formulated as a constrained optimization problem, which is in general a non‐deterministic polynomial‐time hard problem. To address the problem in a feasible way, we design a heuristic algorithm by using the technique of Branch and Bound. Finally, we combine our spectrum handover scheme with power control and give a convenient solution in a single‐SU scenario. Experimental results show that our algorithm can improve the network performance efficiently.Copyright © 2012 John Wiley & Sons, Ltd.

In this paper, we propose an Alamouti coded orthogonal frequency-division multiplexing (OFDM) scheme for amplify-and-forward (AF) relay networks that contain multiple distributed relay nodes. The frequency asynchronous nature of the distributed system is considered in our design. By implementing simple operations, e.g., time reversal, conjugation and amplification, the proposed scheme eliminates the needs of knowledge of both channel states and the frequency offsets at the relay nodes. We prove that when the frequency offsets among the relay nodes are smaller than a certain threshold, full spatial diversity can be achieved at the destination node even with the linear receivers, e.g., zero-forcing (ZF) receiver. Numerical results are provided to corroborate the proposed studies.

In this study, the authors develop a distributed space–time coding scheme for a two‐way relay network that contains multiple distributed relay nodes. Both the time and frequency asynchronous nature of the distributed system are considered in the design. Distributed convolutional coding is employed to handle multiple timing errors in the networks. The authors prove that under perfect frequency synchronisation, the proposed scheme can achieve both spatial and multipath diversity by linear receivers, such as linear zero‐forcing or minimum mean‐square‐error receiver, thus providing a low decoding complexity. The authors further find that frequency asynchronism has little effect on the designed scheme and show that the diversity can still be achieved almost surely (in the measured theoretic sense) under both time and frequency asynchronous scenarios. The authors also provide numerical results to corroborate the proposed studies.

In this paper, we design a new distributed angle estimation method for localization in wireless sensor networks (WSNs) under multipath propagation environment. We employ a two-antenna anchor that can emit two linear chirp waves simultaneously, and propose to estimate the angle of departure (AOD) of the emitted waves at each receiving node via frequency measurement of the local received signal strength indication (RSSI) signal. An improved estimation method is further proposed where multiple parallel arrays are adopted to provide the space diversity. The proposed methods rely only on radio transceivers and do not require frequency synchronization or precise time synchronization between the transceivers. More importantly, the angle is estimated at each sensor in a completely distributed manner. The performance analysis is derived and simulations are presented to corroborate the proposed studies.

In this paper, we develop a new carrier frequency offset (CFO) estimation scheme for interleaved orthogonal frequency division multiple access (OFDMA) transmission. We employ multi-antenna at the receiver and exploit the rank reduction approach to blindly estimate the CFOs of multiple users. The proposed scheme supports full load transmission that allows all sub-carriers being allocated to users, which is a significant advantage over the existing schemes. Both performance analysis and numerical results are provided to corroborate the proposed studies.

In this paper, we develop a new subspace based multiuser carrier frequency offset (CFO) estimation scheme for multi-input multi- output (MIMO) orthogonal frequency division multiple access (OFDMA) uplink transmission. We exploit the rank reduction approach by equipping multiple antennas at the receiver, in which the CFO of each user is derived blindly using one dimension (1-D) search individually. The proposed scheme supports the generalized subcarrier assignment scheme and full loaded transmission with all subcarriers being allocated to users. Numerical results are provided to corroborate the proposed studies.

In this paper, we develop a distributed space-time coding scheme to cope with both time and frequency asynchronism in two-way relay network (TWRN). The convolutional coding is employed to handle multiple timing errors in the networks. We prove that both the cooperative and the multipath diversities can be achieved by linear receivers, e.g., linear zero-forcing (ZF) or minimum mean square error (MMSE) receivers. Moreover, the diversity can be guaranteed almost surely under frequency asynchronism. Numerical results are then provided to corroborate the proposed studies.

Contrary to prior assumptions, recent measurements show that data center traffic is not constrained by network bisection bandwidth, but is instead prone to congestion loss caused by short traffic bursts. Compared to the cost and complexity of modifying data center architectures, a much more attractive option is to augment wired links with flexible wireless links in the 60 GHz band. Current proposals, however, are severely constrained by two factors. First, 60 GHz wireless links are limited by line-of-sight, and can be blocked by even small obstacles between the endpoints. Second, even beamforming links leak power, and potential interference will severely limit concurrent transmissions in dense data centers. In this paper, we explore the feasibility of a new wireless primitive for data centers, 3D beamforming. We explore the design space, and show how bouncing 60 GHz wireless links off reflective ceilings can address both link blockage and link interference, thus improving link range and number of current transmissions in the data center.

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.

Today's WiFi access points (APs) are ubiquitous, and provide critical connectivity for a wide range of mobile networking devices. Many management tasks, e.g. optimizing AP placement and detecting rogue APs, require a user to efficiently determine the location of wireless APs. Unlike prior localization techniques that require either specialized equipment or extensive outdoor measurements, we propose a way to locate APs in real-time using commodity smartphones. Our insight is that by rotating a wireless receiver (smartphone) around a signal-blocking obstacle (the user's body), we can effectively emulate the sensitivity and functionality of a directional antenna. Our measurements show that we can detect these signal strength artifacts on multiple smartphone platforms for a variety of outdoor environments. We develop a model for detecting signal dips caused by blocking obstacles, and use it to produce a directional analysis technique that accurately predicts the direction of the AP, along with an associated confidence value. The result is Borealis, a system that provides accurate directional guidance and leads users to a desired AP after a few measurements. Detailed measurements show that Borealis is significantly more accurate than other real-time localization systems, and is nearly as accurate as offline approaches using extensive wireless measurements.

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.

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.

In this paper, a novel method is proposed for carrier-frequency offset (CFO) estimation for multi-user in orthogonal frequency division multiple access (OFDMA) uplink. Generalized carrier assignment scheme (GCAS) is supported in order to allow dynamic resource allocation and provide more flexility. The base station is equipped with multi-antenna. Each user's CFO can be estimated by a closed form based on ESPRIT-like method utilizing the rotation invariance of the space-domain snapshot matrix. The method is still effective even in fully loaded system with all subcarriers allocated to users, and the computational complexity can be adjusted dynamically according to the system assignment scheme.

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.

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.