Subcarrier allocation based Simultaneous Wireless Information and Power Transfer algorithm in 5G cooperative OFDM communication systems

In this paper, we study the hybrid beamforming for the wideband mmWave multiuser MIMO-OFDM system. We characterize the frequency-dependent beam angle problem, i.e., beam squint effect. Firstly, we extend the mmWave channel model from the Saleh-Valenzuela representation with the consideration of beam squint. Secondly, a two-tier hybrid beamforming is proposed to achieve the maximum spectral efficiency in wideband mmWave multiuser MIMO-OFDM system. In the first tier, the Rotman lens array is adopted as the analog precoder to provide true-time-delay (TTD) and reduce the beam squint impairment. Moreover, the first-tier baseband precoder is designed based on block diagonalization (BD) to cancel inter-user interference. We further consider the finite spatial resolution and power leakage problem of the lens array. The second-tier hybrid precoder is proposed to collect the leak power with the phase shifter array. The optimal second-tier hybrid precoder design is formulated as the matrix factorization problem, and the two-tier hybrid precoding algorithm is based on the alternative minimization. It is found that both the beam squint and frequency-selective effect should be considered in the wideband mmWave system. Simulation results show that the proposed two-tier hybrid precoder could reduce beam squint impairment and inter-user interference, and could approximate to the optimal full-digital precoder with much fewer RF chains.

Section: Power Leakage In Finite-resolution Lens Arraymentioning

confidence: 99%

Rotman lens-based two-tier hybrid beamforming for wideband mmWave MIMO-OFDM system with beam squint

Liu

Zhu

2018

“…Recently, various indoor localization technologies [1][2][3][4], such as WiFi, ultra-wideband, radio frequency identification, and pedestrian dead reckoning (PDR), have been developed. Among them, WiFi and PDR have been regarded as two of the most popular indoor localization solutions, since both of them require no additional hardware cost.…”

Section: Introductionmentioning

confidence: 99%

WiFi/PDR-integrated indoor localization using unconstrained smartphones

Jian

Liu

et al. 2019

Self Cite

In this paper, we propose a WiFi/pedestrian dead reckoning (PDR)-integrated localization approach based on unscented Kalman filters (UKF). The UKF integrating WiFi localization with PDR is used for ultimate location estimation. Instead of setting process and measurement noise-related parameters empirically as previous works, the error covariance of user heading estimation in PDR state model can be accurately estimated by developing another UKF, while the measurement noise statistics in WiFi localization are estimated by deploying a kernel density estimation-based model. Another developed UKF is used for device attitude tracking in user heading estimation of PDR. Besides, in order to adapt the unconstrained carrying positions and orientations of smartphones, we propose a robust carrying position recognition method based on orientation invariant features. Experimental results show that the proposed WiFi/PDR-integrated localization approach may improve traditional approaches in terms of reliability and localization accuracy.

“…Wireless communication and information technology have been developed to the fifth generation (5G) [1][2][3][4][5], which enabled the realization of various applications based on radio signals [6][7][8][9][10], including satellite systems [11][12][13], however, they could not be used in an underwater environment. Wireless sensor network (WSN) is wildly used in an underwater environment to collect and transmit data.…”

Section: Introductionmentioning

confidence: 99%

Improved energy-balanced algorithm for underwater wireless sensor network based on depth threshold and energy level partition

Pan

Qin

et al. 2019

Considering the insufficient global energy consumption optimization of the existing routing algorithms for Underwater Wireless Sensor Network (UWSN), a new algorithm, named improved energy-balanced routing (IEBR), is designed in this paper for UWSN. The algorithm includes two stages: routing establishment and data transmission. During the first stage, a mathematical model is constructed for transmission distance to find the neighbors at the optimal distances and the underwater network links are established. In addition, IEBR will select relays based on the depth of the neighbors, minimize the hops in a link based on the depth threshold, and solve the problem of data transmission loop. During the second stage, the links built in the first stage are dynamically changed based on the energy level (EL) differences between the neighboring nodes in the links, so as to achieve energy balance of the entire network and extend the network lifetime significantly. Simulation results show that compared with other typical energy-balanced routing algorithms, IEBR presents superior performance in network lifetime, transmission loss, and data throughput.