Long Zhao

Survey of Large-Scale MIMO Systems

The escalating teletraffic growth imposed by the proliferation of smartphones and tablet computers outstrips the capacity increase of wireless communications networks. Furthermore, it results in substantially increased carbon dioxide emissions. As a powerful countermeasure, in the case of full-rank channel matrices, MIMO techniques are potentially capable of linearly increasing the capacity or decreasing the transmit power upon commensurately increasing the number of antennas. Hence, the recent concept of large-scale MIMO (LS-MIMO) systems has attracted substantial research attention and been regarded as a promising technique for next-generation wireless communications networks. Therefore, this paper surveys the state of the art of LS-MIMO systems. First, we discuss the measurement and modeling of LS-MIMO channels. Then, some typical application scenarios are classified and analyzed. Key techniques of both the physical and network layers are also detailed. Finally, we conclude with a range of challenges and future research topics.

10 Gb/s hetsnets with millimeter-wave communications: access and networking - challenges and protocols

Heterogeneous and small cell networks (Het- SNets) increase spectral efficiency and throughput via hierarchical deployments. In order to meet the increasing requirements in capacity for future 5G wireless networks, millimeter-wave (mmWave) communications with unprecedented spectral resources have been suggested for 5G HetSNets. While the mmWave physical layer is well understood, major challenges remain for its effective and efficient implementation in Het- SNets from an access and networking point of view. Toward this end, we introduce a novel but 3GPP backwards-compatible frame structure, based on time-division duplex, which facilitates both high-capacity access and backhaul links. We then discuss networking issues arising from the multihop nature of the mmWave backhauling mesh. Finally, system-level simulations evaluate the performance of HetSNets with mmWave communications and corroborate the possibility of having capacities of tens of gigabits per second in emerging 5G systems.

Reliable and efficient autonomous driving: the need for heterogeneous vehicular networks

Autonomous driving technology has been regarded as a promising solution to reduce road accidents and traffic congestion, as well as to optimize the usage of fuel and lane. Reliable and highly efficient vehicle-to-vehicle and vehicle-to-infrastructure communications are essential for commercial autonomous driving vehicles to be on the road before 2020. The current article first presents the concept of heterogeneous vehicular networks (HetVNETs) for autonomous driving, in which an improved protocol stack is proposed to satisfy the communication requirements of not only safety but also non-safety services. We then consider and study in detail several typical scenarios for autonomous driving. In order to tackle the potential challenges raised by the autonomous driving vehicles in HetVNETs, new techniques from transmission to networking are proposed as potential solutions.

Round-Trip Energy Efficiency of Wireless Energy Powered Massive MIMO System With Latency Constraint

We consider a massive MIMO system with frequency-division duplex, where a base station (BS) transfers energy to multiple users in the downlink and the users simultaneously transmit information to the BS in the uplink using the harvested energy. The objective of this letter is to optimize the round-trip energy efficiency (EE) by transmit power allocation at the BS while guaranteeing the delay outage requirements of different users with Poisson traffic arrivals. The service rate and the delay outage probability are first derived. Then, the power allocation problem is formulated as a non-convex problem, which is then transformed into a convex one. The results indicate that the proposed power allocation can significantly improve the round-trip EE of wireless energy powered massive MIMO system.

Energy-efficient dual-layer coordinated beamforming scheme in multi-cell massive multiple-input–multiple-output systems

To improve the energy efficiency of multi-cell massive multiple-input–multiple-output system while guaranteeing the information transmission quality, this study proposes a dual-layer coordinated beamforming scheme. In the proposed scheme, the beamformer at each evolved node B (eNB) is divided into a cell-layer beamformer and a user-layer beamformer. The cell-layer beamformer is used to mitigate inter-cell interference (ICI) by exchanging long-term channel state information (CSI) among eNBs. The user-layer beamformer serves user according to the local real-time CSI at each eNB. On the basis of the dual-layer structure, the cell-layer beamformers, the user-layer beamformers, and power allocation are jointly optimised in order to minimise the total transmit power across all the eNBs subject to the signal-to-interference-plus-noise ratio requirements and single-antenna power constraints. To make the original problem solvable, the ICI is replaced by its upper bound. Then, the problem is partitioned into two convex sub-problems, and two iterative algorithms are proposed in order to find the sub-optimal solution to the original optimisation problem. Simulation results show that the proposed scheme performs better than two reference schemes including the existing zero-forcing scheme and coordinative multiple point schemes.

Cooperative Energy Broadcasting System With Massive MIMO

Different from information transmission, inter-cell interference benefits energy harvesting of energy users (EUs) in multi-cell scenario. Therefore, the objective of this letter is to maximize the average energy harvesting utility of multiple EUs by leveraging inter-cell cooperation. Considering channel state information (CSI) delay, a cooperative energy precoder with centralized implementation is first proposed when the energy stations (ESs) employ massive multiple-input multiple-output. Then, its distributed implementation is presented in terms of a local constraint at each ES and information exchange among ESs. Results indicate that the cooperative energy transfer significantly outperforms the non-cooperative energy transfer with either perfect or delay CSI, and the proposed energy precoder with proportional fairness utility can balance the harvested energy and fairness among different EUs.

Beamformer Design and Utility Optimization for Hybrid Information and Energy Transfer With Massive MIMO

Consider a massive multiple-input multiple-output (MIMO) system, where the base station employing space-division multiple access simultaneously transmits information and energy to the information and energy users, respectively. The objective is to maximize the energy harvesting utility of the energy users, while guaranteeing the outage probability requirements of the information users. Since conventional beamformers, such as the maximum ratio transmission (MRT) and zero-forcing (ZF) beamformers, are designed for information transmission, a hybrid beamformer is first proposed to improve both the spectral efficiency (SE) of the information users and the harvested power (HP) of the energy users. Then, based on the analysis of SE and HP, the utility maximization problem is formulated and solved, followed by the proposal of a power allocation scheme for the hybrid information and energy transfer system. Theoretical and simulated results are presented to show that the hybrid beamformer is able to improve the SE-HP trade-off in comparison to the MRT and ZF beamformers, and gives the best energy harvesting utility at the expense of moderate complexity.

Traffic-aware resource allocation schemes for HetNet based on CDSA

The control-data separation architecture (CDSA) has been regarded as a promising solution to effectively manage the heterogeneous network (HetNet) in the fifth-generation mobile communication systems. Thus, this study investigates the resource allocation problems in CDSA-based HetNet. To meet various requirements of data transmission, the authors first present a new framework with flexible resource management and efficient traffic control. In this framework, the control-data transmission supported by macro cell evolved nodeB is time-sensitive and continuous with high reliability. On the basis of it, a traffic-aware resource allocation approach is proposed to improve the resource efficiency. Once the traffic-congestion requirements of the pattern are satisfied with the minimum spectrum, the throughput of small cells is simultaneously maximised due to orthogonal spectrum between macro and small cells by using this approach. Moreover, the traffic-congestion analytical result is elaborately derived in terms of current network state. Three adaptive resource allocation schemes for implementing this approach are also designed with different complexities. Numerical results validate the accuracy of the proposed analytical method, and also indicate that the traffic-aware resource allocation approach is more efficient than the static one.

Resource Optimization of Wireless Information and Energy Supply Control Systems With Massive MIMO

We study a wireless information and energy supply control system with frequency-division operation. In the considered system, a control station (CS) with a massive antenna array transmits energy and control information to multiple control terminals (CTs), and the CTs simultaneously transmit sensing information to the CS using harvested energy. The objective of this letter is to minimize the maximum control cost among all the CTs through resource allocation, while satisfying the transmission rate requirements of both the sensing and control information. The transmission rates are first derived, and then, a relationship between control cost and power allocation is established. Finally, we prove that all the CTs should have the same control cost to meet the min–max criterion, based on which a resource allocation scheme is proposed for the min–max problem. Numerical results indicate that the proposed resource allocation scheme is able to significantly reduce the system control cost.

Massive MIMO-Assisted Energy Transfer Technology

This chapter considers a downlink massive MIMO system, where the base station simultaneously sends information and energy to information users and energy users, respectively. The aim is to maximize the minimum harvested energy among the energy users while meeting the rate requirements of information users. With perfect CSI, the problem is solved by obtaining the asymptotically optimal power allocation of information users and the combination coefficients of the energy precoder. For the CSI estimation in time-division duplex systems, orthogonal pilot sequences are employed by information users during the uplink, and one common pilot sequence is shared by all energy users. It is shown that the energy harvesting performance of such a shared pilot scheme is always better than that of the orthogonal pilot scheme. Further, exploiting the inter-cell interference in multi-cell systems, a joint precoder is proposed for cooperative energy transfer, for which both the centralized and distributed implementations are given. Results indicate that the cooperative energy transfer always outperforms the non-cooperative scheme with either perfect or estimated CSI.