arXiv subjects

Shidong Zhou

Publications and source records attributed to Shidong Zhou.

At least 37 records · Page 2Linked to original sources

arXiv2019

Super Fast Beam and Channel Tracking in 2D Phased Antenna Arrays

Millimeter wave (mmWave) is an attractive candidate for high-speed mobile communications in the future. However, due to the propagation characteristics of mmWave, beam and and and and alignment becomes a key challenge for serving users with fast moving speeds. In this paper, we develop a joint beam and channel tracking algorithm that can track beams from the horizontal and vertical directions by using two-dimensional (2D) phased antenna arrays. A general sequence of optimal trial beamforming parameters is obtained to achieve the minimum Cramer-Rao lower bound (CRLB) of joint beam and channel tracking asymptotically as antenna number grows to infinity. This sequence is proved to be asymptotically optimal in different conditions, e.g., channel coefficients, path directions, and antenna array sizes. We prove that the proposed algorithm converges to the minimum CRLB in static scenarios. Simulation results show that our algorithm outperforms several existing algorithms in tracking accuracy and speed band.

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arXiv2019

Fast Analog Beam Tracking in Phased Antenna Arrays: Theory and Performance

The directionality of millimeter-wave (mmWave) communications introduces a significant challenge in serving fast-rotating/moving terminals, e.g., mobile AR/VR, high-speed vehicles, trains, UAVs.This challenge is exacerbated in mmWave systems using analog beamforming, because of the inherent non-convexity in the analog beam tracking problem. In this paper, we obtain the Cramér-Rao lower bound (CRLB) of beam tracking and optimize the analog beamforming vectors to get the minimum CRLB. Then, we develop a low complexity analog beam tracking algorithm that simultaneously optimizes the analog beamforming vector and the estimate of beam direction. Finally, by establishing a new basic theory, we provide the theoretical convergence analysis of the proposed analog beam tracking algorithm, which proves that the minimum CRLB of the MSE is achievable with high probability. Our simulations show that this algorithm can achieve faster tracking speed, higher tracking accuracy and higher data rate than several state-of-the-art algorithms. The key analytical tools used in our algorithm design are stochastic approximation and recursive estimation with a control parameter.

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arXiv2018

Joint Beam and Channel Tracking for Two-Dimensional Phased Antenna Arrays

Analog beamforming is a low-cost architecture for millimeter-wave (mmWave) mobile communications. However, it has two disadvantages for serving fast mobility users: (i) the mmWave beam in the wireless channel and the beam steered by analog beamforming have small angular spreads which are difficult to align with each other and (ii) the receiver can only observe the mmWave channel in one beam direction and rely on beam-probing algorithms to check other directions. In this paper, we develop a beam probing and tracking algorithm that can efficiently track fast-moving mmWave beams in three-dimensional (3D) space. This algorithm has several salient features: (1) fading channel supportive: it can simultaneously track the channel coefficient and two-dimensional (2D) beam direction in fading channel environments; (2) low probing overhead: it achieves the minimum probing requirement for joint beam and channel tracking; (3) fast tracking speed and high tracking accuracy: its tracking error converges to the minimum Cramer-Rao lower bound (CRLB) in static scenarios in theory and it outperforms several existing tracking algorithms with lower tracking error and faster tracking speed in simulations.

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arXiv2018

Blockage Modeling for Inter-layer UAVs Communications in Urban Environments

The impact of buildings blockage on the UAVs communications in different UAVs heights is studied, when UAVs fly in a given rectangular urban area. This paper analyzes the properties of blockage behavior of communication links between UAVs from layers of different heights, including two main stochastic properties, namely the blockage (or LOS) probabilities, and the state transition models (birth-death process of LOS propagation). Based on stochastic geometry methods, the relation between LOS probability and the parameters of the region and the buildings is derived and verified with simulations. Furthermore, based on the simulations of the channel state transition process, we also find the birth-death process can be modeled as a distance continuous Markov process, and the transition rates are also extracted with their relation with the height of layers.

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arXiv2018

Channel Model in Urban Environment for Unmanned Aerial Vehicle Communications

In order to develop and analyze reliable communications links for unmanned aerial vehicles (UAVs), accurate models for the propagation channel are required. The radio channel properties in the urban scenario are different from those in the suburb scenario and open area due to so many scattering paths from office buildings, especially when the UAV flies in the low altitude. We took some measurement campaigns on the campus of Tsinghua University with crowded apartments and office buildings. Based on the measurement result we extract the main parameters of pathloss model, and propose a simplified Saleh-Valenzuela (SV) model with specific parameters. The typical scene of central lawn is compared with the office buildings in the analysis of K-factor and root-mean-square (RMS) delay spread.

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arXiv2018

Coverage Probability Analysis of UAV Cellular Networks in Urban Environments

In this paper, we study coverage probabilities of the UAV-assisted cellular network modeled by 2-dimension (2D) Poisson point process. The cellular user is assumed to connect to the nearest aerial base station. We derive the explicit expressions for the downlink coverage probability for the Rayleigh fading channel. Furthermore, we explore the behavior of performance when taking the property of air-to-ground channel into consideration. Our analytical and numerical results show that the coverage probability is affected by UAV height, pathloss exponent and UAV density. To maximize the coverage probability, the optimal height and density of UAVs are studied, which could be beneficial for the UAV deployment design.

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arXiv2018

How to Mobilize mmWave: A Joint Beam and Channel Tracking Approach

Maintaining reliable millimeter wave (mmWave) connections to many fast-moving mobiles is a key challenge in the theory and practice of 5G systems. In this paper, we develop a new algorithm that can jointly track the beam direction and channel coefficient of mmWave propagation paths using phased antenna arrays. Despite the significant difficulty in this problem, our algorithm can simultaneously achieve fast tracking speed, high tracking accuracy, and low pilot overhead. In static scenarios, this algorithm can converge to the minimum Cramér-Rao lower bound of beam direction with high probability. Simulations reveal that this algorithm greatly outperforms several existing algorithms. Even at SNRs as low as 5dB, our algorithm is capable of tracking a mobile moving at an angular velocity of 5.45 degrees per second and achieving over 95\% of channel capacity with a 32-antenna phased array, by inserting only 10 pilots per second.

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arXiv2017

Analog Beam Tracking in Linear Antenna Arrays: Convergence, Optimality, and Performance

The directionality of millimeter-wave (mmWave) communications creates a significant challenge in serving fast-moving mobile terminals on, e.g., high-speed vehicles, trains, and UAVs. This challenge is exacerbated in mmWave systems using analog antenna arrays, because of the inherent non-convexity in the control of the phase shifters. In this paper, we develop a recursive beam tracking algorithm which can simultaneously achieve fast tracking speed, high tracking accuracy, low complexity, and low pilot overhead. In static scenarios, this algorithm converges to the minimum Cramér-Rao lower bound (CRLB) of beam tracking with high probability. In dynamic scenarios, even at SNRs as low as 0dB, our algorithm is capable of tracking a mobile moving randomly at an absolute angular velocity of 10-20 degrees per second, using only 5 pilot symbols per second. If combining with a simple TDMA pilot pattern, this algorithm can track hundreds of high-speed mobiles in 5G configurations. Our simulations show that the tracking performance of this algorithm is much better than several state-of-the-art algorithms.

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arXiv2017

Spectrum and Energy Efficient Beamspace MIMO-NOMA for Millimeter-Wave Communications Using Lens Antenna Array

The recent concept of beamspace multiple input multiple output (MIMO) can significantly reduce the number of required radio-frequency (RF) chains in millimeter-wave (mmWave) massive MIMO systems without obvious performance loss. However, the fundamental limit of existing beamspace MIMO is that, the number of supported users cannot be larger than the number of RF chains at the same time-frequency resources. To break this fundamental limit, in this paper we propose a new spectrum and energy efficient mmWave transmission scheme that integrates the concept of non-orthogonal multiple access (NOMA) with beamspace MIMO, i.e., beamspace MIMO-NOMA. By using NOMA in beamspace MIMO systems, the number of supported users can be larger than the number of RF chains at the same time-frequency resources. Particularly, the achievable sum rate of the proposed beamspace MIMO-NOMA in a typical mmWave channel model is analyzed, which shows an obvious performance gain compared with the existing beamspace MIMO. Then, a precoding scheme based on the principle of zero-forcing (ZF) is designed to reduce the inter-beam interferences in the beamspace MIMO-NOMA system. Furthermore, to maximize the achievable sum rate, a dynamic power allocation is proposed by solving the joint power optimization problem, which not only includes the intra-beam power optimization, but also considers the inter-beam power optimization. Finally, an iterative optimization algorithm with low complexity is developed to realize the dynamic power allocation. Simulation results show that the proposed beamspace MIMO-NOMA can achieve higher spectrum and energy efficiency compared with existing beamspace MIMO.

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arXiv2016

Massive MIMO with Multi-Antenna Users: When are Additional User Antennas Beneficial?

We analyze the performance of massive MIMO systems with $N$-antenna users. The benefit is that $N$ streams can be multiplexed per user, at the price of increasing the channel estimation overhead linearly with $N$. Uplink and downlink spectral efficiency (SE) expressions are derived for any $N$, and these are achievable using estimated channels and per-user-basis MMSE-SIC detectors. Large-system approximations of the SEs are obtained. This analysis shows that MMSE-SIC has similar asymptotic SE as linear MMSE detectors, indicating that the SE increase from having multi-antenna users can be harvested using linear detectors. We generalize the power scaling laws for massive MIMO to handle arbitrary $N$, and show that one can reduce the multiplication of the pilot power and payload power as $\frac{1}{M}$ where $M$ is the number of BS antennas, and still notably increase the SE with $M$ before reaching a non-zero asymptotic limit. Simulations testify our analysis and show that the SE increases with $N$. We also note that the same improvement can be achieved by serving $N$ times more single-antenna users instead, thus the additional user antennas are particular beneficial for SE enhancement when there are few active users in the system.

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arXiv2016

Capacity Analysis for Spatially Non-wide Sense Stationary Uplink Massive MIMO Systems

Channel measurements show that significant spatially non-wide-sense-stationary characteristics rise in massive MIMO channels. Notable parameter variations are experienced along the base station array, such as the average received energy at each antenna, and the directions of arrival of signals impinging on different parts of the array. In this paper, a new channel model is proposed to describe this spatial non-stationarity in massive MIMO channels by incorporating the concepts of partially visible clusters and wholly visible clusters. Furthermore, a closed-form expression of an upper bound on the ergodic sum capacity is derived for the new model, and the influence of the spatial non-stationarity on the sum capacity is analyzed. Analysis shows that for non-identically-and-independent-distributed (i.i.d.) Rayleigh fading channels, the non-stationarity benefits the sum capacity by bringing a more even spread of channel eigenvalues. Specifically, more partially visible clusters, smaller cluster visibility regions and a larger antenna array can all help to yield a well-conditioned channel, and benefit the sum capacity. This shows the advantage of using a large antenna array in a non-i.i.d. channel: the sum capacity benefits not only from a higher array gain, but also from a more spatially non-stationary channel. Numerical results demonstrate our analysis and the tightness of the upper bound.

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arXiv2016

Deployment of 5G Networking Infrastructure with Machine Type Communication Considerations

Designing optimal strategies to deploy small cell stations is crucial to meet the quality-of-service requirements in next-generation cellular networks with constrained deployment costs. In this paper, a general deployment framework is proposed to jointly optimize the locations of backhaul aggregate nodes, small base stations, machine aggregators, and multi-hop wireless backhaul links to accommodate both human-type and machine-type communications. The goal is to provide deployment solutions with best coverage performance under cost constraints. The formulated problem is shown to be a multi-objective integer programming for which it is challenging to obtain the optimal solutions. To solve the problem, a heuristic algorithm is proposed by combining Lagrangian relaxation, the weighted sum method, the $ε$-constraint method and tabu search to obtain both the solutions and bounds, for the objective function. Simulation results show that the proposed framework can provide solutions with better performance compared with conventional deployment models in scenarios where available fiber connections are scarce. Furthermore, the gap between obtained solutions and the lower bounds is quite tight.

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arXiv2016

Green 5G Heterogeneous Networks through Dynamic Small-Cell Operation

Traditional macro-cell networks are experiencing an upsurge of data traffic, and small-cells are deployed to help offload the traffic from macro-cells. Given the massive deployment of small-cells in a macro-cell, the aggregate power consumption of small-cells (though being low individually) can be larger than that of the macro-cell. Compared to the macro-cell base station (MBS) whose power consumption increases significantly with its traffic load, the power consumption of a small-cell base station (SBS) is relatively flat and independent of its load. To reduce the total power consumption of the heterogeneous networks (HetNets), we dynamically change the operating states (on and off) of the SBSs, while keeping the MBS on to avoid any service failure outside active small-cells. First, we consider that the wireless users are uniformly distributed in the network, and propose an optimal location-based operation scheme by gradually turning off the SBSs closer to the MBS. We then extend the operation problem to a more general case where users are non-uniformly distributed in the network. Although this problem is NP-hard, we propose a joint location and user density based operation scheme to achieve near-optimum (with less than 1\% performance loss in our simulations) in polynomial time.

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arXiv2015

Software-Defined Hyper-Cellular Architecture for Green and Elastic Wireless Access

To meet the surging demand of increasing mobile Internet traffic from diverse applications while maintaining moderate energy cost, the radio access network (RAN) of cellular systems needs to take a green path into the future, and the key lies in providing elastic service to dynamic traffic demands. To achieve this, it is time to rethink RAN architectures and expect breakthroughs. In this article, we review the state-of-art literature which aims to renovate RANs from the perspectives of control-traffic decoupled air interface, cloud-based RANs, and software-defined RANs. We then propose a software-defined hyper-cellular architecture (SDHCA) that identifies a feasible way of integrating the above three trends to enable green and elastic wireless access. We further present key enabling technologies to realize SDHCA, including separation of the air interface, green base station operations, and base station functions virtualization, followed by our hardware testbed for SDHCA. Besides, we summarize several future research issues worth investigating.

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arXiv2015

Joint Deployment of Small Cells and Wireless Backhaul Links in Next-Generation Networks

In this paper, a novel approach for optimizing the joint deployment of small cell base stations and wireless backhaul links is proposed. This joint deployment scenario is cast as a multi-objective optimization problem under the constraints of limited backhaul capacity and outage probability. To address the problem,a novel adaptive algorithm that integrates $ε$-method, Lagrangian relaxation and tabu search is proposed to obtain the Pareto optimal solution set. Simulation results show that the proposed algorithm is quite effective in finding the optimal solutions. The proposed joint deployment model can be used for planning small cell networks.

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arXiv2015

A Multi-cell MMSE Detector for Massive MIMO Systems and New Large System Analysis

In this paper, a new multi-cell MMSE detector is proposed for massive MIMO systems. Let $K$ and $B$ denote the number of users in each cell and the number of available pilot sequences in the network, respectively, with $B = βK$, where $β\ge 1 $ is called the pilot reuse factor. The novelty of the multi-cell MMSE detector is that it utilizes all $B$ channel directions that can be estimated locally at a base station, so that intra-cell interference, parts of the inter-cell interference and the noise can all be actively suppressed, while conventional detectors only use the $K$ intra-cell channels. Furthermore, in the large-system limit, a deterministic equivalent expression of the uplink SINR for the proposed multi-cell MMSE is derived. The expression is easy to compute and accounts for power control for the pilot and payload, imperfect channel estimation and arbitrary pilot allocation. Numerical results show that significant sum spectral efficiency gains can be obtained by the multi-cell MMSE over the conventional single-cell MMSE and the recent multi-cell ZF, and the gains become more significant as $β$ and/or $K$ increases. Furthermore, the deterministic equivalent is shown to be very accurate even for relatively small system dimensions.

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arXiv2015

A Multi-cell MMSE Precoder for Massive MIMO Systems and New Large System Analysis

In this paper, a new multi-cell MMSE precoder is proposed for massive MIMO systems. We consider a multi-cell network where each cell has $K$ users and $B$ orthogonal pilot sequences are available, with $B = βK$ and $β\ge 1$ being the pilot reuse factor over the network. In comparison with conventional single-cell precoding which only uses the $K$ intra-cell channel estimates, the proposed multi-cell MMSE precoder utilizes all $B$ channel directions that can be estimated locally at a base station, so that the transmission is designed spatially to suppress both parts of the inter-cell and intra-cell interference. To evaluate the performance, a large-scale approximation of the downlink SINR for the proposed multi-cell MMSE precoder is derived and the approximation is tight in the large-system limit. Power control for the pilot and payload, imperfect channel estimation and arbitrary pilot allocation are accounted for in our precoder. Numerical results show that the proposed multi-cell MMSE precoder achieves a significant sum spectral efficiency gain over the classical single-cell MMSE precoder and the gain increases as $K$ or $β$ grows. Compared with the recent M-ZF precoder, whose performance degrades drastically for a large $K$, our M-MMSE can always guarantee a high and stable performance. Moreover, the large-scale approximation is easy to compute and shown to be accurate even for small system dimensions.

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arXiv2015

Massive MIMO with Multi-cell MMSE Processing: Exploiting All Pilots for Interference Suppression

In this paper, a new state-of-the-art multi-cell MMSE scheme is proposed for massive MIMO networks, which includes an uplink MMSE detector and a downlink MMSE precoder. The main novelty is that it exploits all available pilots for interference suppression. Specifically, let $K$ and $B$ denote the number of users per cell and the number of orthogonal pilot sequences in the network, respectively, where $β= B/K$ is the pilot reuse factor. Then our multi-cell MMSE scheme utilizes all $B$ channel directions, that can be estimated locally at each base station, to actively suppress both intra-cell and inter-cell interference. The proposed scheme is particularly practical and general, since power control for the pilot and payload, imperfect channel estimation and arbitrary pilot allocation are all accounted for. Simulations show that significant spectral efficiency (SE) gains are obtained over the single-cell MMSE scheme and the multi-cell ZF, particularly for large $β$ and/or $K$. Furthermore, large-scale approximations of the uplink and downlink SINRs are derived, which are asymptotically tight in the large-system limit. The approximations are easy to compute and very accurate even for small system dimensions. Using these SINR approximations, a low-complexity power control algorithm is also proposed to maximize the sum SE.

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