Search

In the development of analog signal compressive sensing (CS), the degradation of reconstruction performance under noise is the main bottleneck because the CS framework is very sensitive to noise. This paper proposes an adaptive channelization-based orthogonal matching pursuit algorithm (C-OMP) combining the channelization and the adaptive iteration methods. The proposed C-OMP has two steps: channel screening and global iteration. Based on the proposed method, the original signal can be recovered adaptively in high probability of success with fewer observations under the noise background. Simultaneously, the noise can be reduced as much as possible to enhance the output signal-to-noise ratio (SNR) by excluding the noise channel during the channel screening and separating noise atoms during the global iteration. The relationship between the probability of successful reconstruction and the number of observations is mathematically analyzed. Furthermore, the parameter settings, computational complexity, and output SNR are analytically evaluated. The simulation results confirm the analytical results and further demonstrate the effectiveness and advantages of the C-OMP in the noise environment. Overall, the proposed algorithm considerably improves the performance of the analog signal CS in the practical noisy environment. [ABSTRACT FROM AUTHOR]

This correspondence paper studies joint beamforming optimization and time allocation for a wireless powered two-way hybrid-relay network. As a general relaying architecture accommodating the existing relaying architectures in the literature as two special cases, we consider the two-way communication system where both energy-harvesting (EH) relays and non-EH relays exist. We aim to maximize the minimum rate by jointly optimizing the distributed beamforming vector at the relays, the energy beamforming matrix at the non-EH relays, and the EH time allocation with the energy constraints at the relays. The formulated problem is intractable to solve because the objective function and the energy constraints are highly nonconvex. We solve the optimization problem using the successive convex approximation. Simulations demonstrate that the proposed iterative algorithm considerably outperforms any existing approaches. [ABSTRACT FROM AUTHOR]

This paper studies the joint beamforming design and time allocation for a two-way energy harvesting (EH) relay network, where a single-antenna base station and a single-antenna user communicate with each other through multiple-single antenna EH relay nodes, and an external multiantenna power beacon wirelessly power the relays. Unlike the existing studies that assumed the symmetric two-way relaying scenario, we assume a more practical scenario of asymmetric two-way relaying considering different traffic demands on the downlink and uplink. In this paper, we design the optimal beamforming vectors at the relays and at the power beacon jointly with the time allocation between information and EH transmissions, in the sense of maximizing the sum rate of the asymmetric information transmission under the EH constraints at the relays, and the power constraint at the power beacon. The formulated optimization problem is nonconvex, and thus, it is difficult to solve. To solve this challenging problem, we propose an iterative algorithm based on the semidefinite relaxation and the successive convex approximation techniques. Also, to reduce the computational complexity, we propose an efficient noniterative scheme based on the maximum-ratio transmission. The performance of the proposed schemes is demonstrated through simulations. [ABSTRACT FROM AUTHOR]