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<p>In this paper, we propose a novel three-dimensional (3D) near-field beamforming (BF) design for Large Intelligent Surface (LIS). We firstly investigate the definitions of near-field and far-field of LIS, and derive the Fresnel near-field region where amplitudes variations are negligible and only phase variations worsen the harvested array-gains. We show that the Fresnel region which covers the majority part of near-field, can be enlarged by a factor of four when considering possible imperfectness from a conventional two-dimensional (2D) far-field BF. Therefore, it is of interest to design analog 3D-BF than can recover array-gain losses in this region. Secondly, with the proved decomposition theorem we show that the optimal 3D-BF can be decomposed into a 2D far-field BF and a one-dimensional (1D) near-field BF. The 2D far-field BF compensates phase variations from mismatches in the azimuth and elevation angles, while the 1D near-field BF compensates remaining phases variations caused by distance differences from the UE to different antenna-elements on LIS. Such a proposed “2D+1D” BF design reduces codebook size significantly and is fully compatible with the existing far-field BF in the fifth-generation new-radio (5G-NR) system. Thirdly, we analyze an optimal codebook design for the 1D near-field BF, and show that with a small codebook it can perform close to optimal. Numerical results further verify that our proposal is effective and robust to recover array-gains in the near-field of LIS. </p>

The paper is dedicated to the multipath angle of arrival (AOA) estimation problem in millimeter wave (mmWave) 5G NR communication system. The case of a phased antenna array with a single digital port is considered. In this scenario, the conventional highly accurate subspace-based algorithms cannot be applied because of hardware restrictions. We proposed a novel subspace-based algorithm called power-based root minimal polynomial method (PR-MPM) that uses the spatial power spectrum to get an approximation of the signal correlation matrix. The power spectrum is measured via the conventional beam sweeping procedure over a finite number of directions. The efficiency of the proposed method is studied using the high-realistic ray-tracing-based channel model applied in mmWave IEEE 802.11ay standard. Simulation results show that AOAs can be precisely estimated using only single-port power measurement.

<p>In this paper, we consider applying probabilistic constellation shaping (PCS) to the fifth-generation new-radio (5G-NR) system. We propose a practical PCS transceiver design which is fully backward compatible to the existing 5G-NR system, and can bring significant improvements in block-error rate (BLER) and throughput. Further, we derive the properties of average-power, entropy-loss, and peak-to-average power-ratio (PAPR) increment in connection to the proposed PCS design. We show that an effective PCS can set the variance of a zero-mean Gaussian distribution for shaping to be around 0.5,making both the PAPR-increment and the entropy-loss to be at acceptable levels. Furthermore, we derive a necessary condition for PCS to attain a higher throughput than a uniform constellation. It shows that the normalized entropy-loss with PCS must be smaller than the BLER attained from transmissions with a uniform constellation. This is a critical observation and provides an important insight for the PCS design. Moreover, we also illustrate that the proposed PCS scheme can provide additional flexibilities in adjusting the effective code-rate without affecting the encoder. As a result, transitions among different MCSs can be smoother even with an adaptive modulation and coding scheme (MCS), and a better throughput-envelope can be obtained as signal-to-noise ratio (SNR) changes.</p>

<p>Precision positioning plays critical roles in 5G-Advanced and 6G systems for various indoor and outdoor applications. Conventionally, positioning accuracy can be dramatically degraded under non-line-of-sight channels or with moving terminal nodes (TNs). To overcome this issue, we propose an orthogonal time-frequency space (OTFS) based positioning with applying distributed cooperative positioning (DCoP) at the ends of TNs, which can yield an ultra-most precise positioning. This is so, since the positioning with OTFS is robust against channel delays and Doppler spreads, and superior to conventional orthogonal frequency-division multiplexing (OFDM) based positioning. Further, DCoP uses cooperations such that TNs can serve as additional anchor nodes (ANs) to others, and improves the positioning accuracy for all. With this proposal, we further elaborate the positioning-reference-signal with OTFS (PRS-OTFS) in delay-Doppler (DD) domain, and design an OTFS-transceiver that is backward compatible to OFDM. Furthermore, we also propose a DD-domain time-of-arrival estimation algorithm that exploits the OTFS waveform and outperforms conventional time-frequency based estimators. Moreover,  we propose a loopy belief-propagation algorithm associated with belief-discretizing for an effective implementation and message exchange in DCoP. In addition, we show that the average Cramer-Rao low-bound per TN can decrease faster than linearly in the number of cooperating TNs. We illustrate with simulations that the proposed OTFS-DCoP scheme is very effective in improving positioning accuracy within a few iterations, and robust against double-selective channels. </p>