Jihong Zhang

Energy-Efficient Resource Allocation in TDMS-Based Wireless Powered Communication Networks

This letter considers a wireless powered communication network (WPCN) where users first harvest energy in downlink and then utilize the energy to transmit information signal in uplink simultaneously. Our goal is to maximize the energy efficiency (EE) of the network via joint time allocation and power control. However, directly solving this issue is of significant challenge due to its nonconvex property. By exploiting the nonlinear fractional programming, an iterative resource allocation method based on the Dinkelbach structure is proposed to solve the considered nonconvex optimization problem. In each iteration, we optimize power with fixed time allocation and then optimize time with a given power allocation. Simulation results are presented to show that the system EE is greatly improved by the proposed approach.

Performance Improvement of Deception Jamming Against SAR Based on Minimum Condition Number

This paper proposes a new approach to improve the error performance of the synergy netting deception jamming against synthetic aperture radar (SAR). The existing methods cannot tackle the issue of error amplification induced by the linear equations constructed for jamming coefficients calculation. To handle this problem, we develop an optimal layout for radar receivers to minimize the effect of the error by minimizing the condition number, which measures the sensitivity of the synergy deception jamming system to the perturbation. It is revealed that the devised approach relies little on the SAR kinematic parameters. To further improve the error performance of the jamming system, collaborative receivers, which provide more observations of time difference of arrivals, are introduced to perform a linear least-squares estimation. The error reduction level due to the cooperative receivers is analyzed. Simulation results are provided to illustrate the superiority of the proposed method.

On Proportional Fairness in Power Allocation for Two-Tone Spectrum-Sharing Networks

To efficiently trade off system sum rate and link fairness, power allocation in wireless spectrum-sharing networks often concentrates upon proportional fairness. The corresponding problem has been proved to be convex for a single tone but NP-hard for more than two tones. However, in the two-tone case, the complexity of the problem for achieving proportional fairness has not been addressed yet. In this paper, we prove that the issue of proportional-fairness optimization for the two-tone situation is NP-hard by reducing the problem of finding the maximum independent set in an undirected graph to it. Moreover, a computationally efficient algorithm is proposed to provide an efficient suboptimal solution. Simulation results are presented to illustrate the effectiveness of our proposal.

Single Channel SAR Deception Jamming Suppression via Dynamic Aperture Processing

This paper proposed a novel algorithm to suppress the deception jamming against the single channel synthetic aperture radar (SAR), which provides an effective and economic way to improve the anti-deception-jamming ability of the conventional SAR system. The dynamic apertures are employed to provide multiple observations about the time-frequency distributions of the deception jamming and real echoes. The amplitude loss in different dynamic apertures is modeled to formulate the optimization problem for deception jamming suppressing. Super-resolution scheme is also involved to tighten the feasible region of the problem. The effectiveness of the proposed algorithm is verified by simulation.

SAR deception jamming identification via differential feature enhancement

This paper proposes a new scheme for SAR deception jamming identification using single channel data. The time-frequency distributions of the real echoes and the deception jamming are modeled according to their formatting mechanisms. By filtering in the Doppler frequency domain, the differential features of the real and the false targets are retained. Then the distances between histograms are calculated to enhance the feature for false target identification. Targets in different size are set in the simulating experiment to verify the effectiveness of the proposed method.

Accurate and computationally efficient interpolation-based method for two-dimensional harmonic retrieval

Abstract Determining the frequencies of multiple resolvable exponentials is an important problem due to its application in diverse areas in science and engineering. In this paper, frequency estimation of two-dimensional (2-D) sinusoids is addressed. With the use of the periodogram in frequency domain, the required harmonics are first located coarsely. The characteristics of the 2-D spectrum is then analyzed, and the accurate estimates of the parameters are retrieved using an interpolation method iteratively. It is proved that at sufficiently high signal-to-noise ratio conditions, the harmonic estimates are asymptotically unbiased, and their variances are also analyzed. Furthermore, when only part of the data is observed, the proposed algorithm is tailored to get fast and accurate estimation results. Computer simulations are also included to compare the proposed approach with conventional 2-D harmonic retrieval schemes in terms of root mean square error performance and computational complexity.

Carrier Frequency Offset Estimation in Uplink OFDMA Systems: An Approach Relying on Sparse Recovery

This paper proposes a novel blind carrier frequency offset (CFO) estimator, namely the sparse recovery assisted CFO (SR-CFO) estimator, for the uplink orthogonal frequency-division multiple access (OFDMA) systems. By exploiting the sparsity embedded in the OFDMA data, the CFO estimation is formulated as an optimization problem of sparse recovery with high-resolution. Meanwhile, in order to enhance the estimation accuracy of CFOs, background noise and sampling errors are mitigated by exploiting the structure of the noise covariances matrix in the transformed observation data, and the asymptotic distribution of the sampling errors. Furthermore, we propose an approach for deriving the regularization parameter used by the SR-CFO estimator, so as to control the tradeoff between the data fitting error and the sparsity of solution. The performance of the proposed SR-CFO estimator along with other four existing estimators is investigated and compared. Numerical results show that the proposed SR-CFO estimator is superior to the state-of-the-art estimators in terms of the estimation reliability.

Accurate signal detection for BPSK-OFDM systems in time-varying channels

Abstract Binary phase shift keying (BPSK) orthogonal frequency division multiplexing (OFDM) has been adopted in the fourth-generation wireless communications. However, the real-valued property of BPSK-OFDM signals has not yet been utilized for channel equalization. In this work, this property is employed to develop a new equalizer based on the minimum mean square error (MMSE) criterion, leading to considerable enhancement in signal detection. In particular, the proposed equalizer is able to achieve 3 dB improvement over the existing MMSE equalizer in large signal-to-noise ratio region, and is more robust against channel estimation errors. Moreover, successive detection technique employed in the devised method is able to make use of diversity in time-varying channels, resulting in further performance enhancement. Additionally, the computational complexity of the proposed approach is analyzed. Simulation results are included to illustrate its performance superiority and computational attractiveness.