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Bo Ai

Publications and source records attributed to Bo Ai.

At least 289 records · Page 16Linked to original sources

Probabilistic Two-Ray Model for Air-to-Air Channel in Built-Up Areas

In this paper, we present a probabilistic two-ray (PTR) path loss model for air-to-air (AA) propagation channel in built-up areas. Based on the statistical model of city deployment, the PTR path loss model can be applied to suburban, urban, dense urban, and high-rise urban. The path loss is optimally fitted as the Weibull distribution and its fluctuation is fitted as the Normal distribution in ray-tracing simulations. The good agreements between our model and ray tracing indicate the proposed model can provide a useful tool for accurate and quick prediction for aerial platforms. As an extended research of PTR model, we extract the shadowing factor by numerous simulations and propose the altitude-dependent shadowing model. The result shows that the proposed shadowing model has very good consistent with the measurement-based model, which indicates that our research performs well in the extensibility and generality.

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Multi-Antenna Channel Interpolation via Tucker Decomposed Extreme Learning Machine

Channel interpolation is an essential technique for providing high-accuracy estimation of the channel state information (CSI) for wireless systems design where the frequency-space structural correlations of multi-antenna channel are typically hidden in matrix or tensor forms. In this letter, a modified extreme learning machine (ELM) that can process tensorial data, or ELM model with tensorial inputs (TELM), is proposed to handle the channel interpolation task. The TELM inherits many good properties from ELMs. Based on the TELM, the Tucker decomposed extreme learning machine (TDELM) is proposed for further improving the performance. Furthermore, we establish a theoretical argument to measure the interpolation capability of the proposed learning machines. Experimental results verify that our proposed learning machines can achieve comparable mean squared error (MSE) performance against the traditional ELMs but with 15% shorter running time, and outperform the other methods for a 20% margin measured in MSE for channel interpolation.

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Resource Allocation for Device-to-Device Communications in Multi-Cell Multi-Band Heterogeneous Cellular Networks

Heterogeneous cellular networks (HCNs) with millimeter wave (mm-wave) communications are considered as a promising technology for the fifth generation mobile networks. Mm-wave has the potential to provide multiple gigabit data rate due to the broad spectrum. Unfortunately, additional free space path loss is also caused by the high carrier frequency. On the other hand, mm-wave signals are sensitive to obstacles and more vulnerable to blocking effects. To address this issue, highly directional narrow beams are utilized in mm-wave networks. Additionally, device-to-device (D2D) users make full use of their proximity and share uplink spectrum resources in HCNs to increase the spectrum efficiency and network capacity. Towards the caused complex interferences, the combination of D2D-enabled HCNs with small cells densely deployed and mm-wave communications poses a big challenge to the resource allocation problems. In this paper, we formulate the optimization problem of D2D communication spectrum resource allocation among multiple micro-wave bands and multiple mm-wave bands in HCNs. Then, considering the totally different propagation conditions on the two bands, a heuristic algorithm is proposed to maximize the system transmission rate and approximate the solutions with sufficient accuracies. Compared with other practical schemes, we carry out extensive simulations with different system parameters, and demonstrate the superior performance of the proposed scheme. In addition, the optimality and complexity are simulated to further verify effectiveness and efficiency.

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An Empirical Air-to-Ground Channel Model Based on Passive Measurements in LTE

In this paper, a recently conducted measurement campaign for unmanned-aerial-vehicle (UAV) channels is introduced. The downlink signals of an in-service long-time-evolution (LTE) network which is deployed in a suburban scenario were acquired. Five horizontal and five vertical flight routes were considered. The channel impulse responses (CIRs) are extracted from the received data by exploiting the cell specific signals (CRSs). Based on the CIRs, the parameters of multipath components (MPCs) are estimated by using a high-resolution algorithm derived according to the space-alternating generalized expectation-maximization (SAGE) principle. Based on the SAGE results, channel characteristics including the path loss, shadow fading, fast fading, delay spread and Doppler frequency spread are thoroughly investigated for different heights and horizontal distances, which constitute a stochastic model.

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Coalition Game based Full-duplex Concurrent Scheduling in Millimeter Wave Wireless Backhaul Network

With the development of self-interference (SI) cancelation technology, full-duplex (FD) communication becomes possible. FD communication can theoretically double the spectral efficiency. When the time slot (TS) resources are limited and the number of flows is large, the scheduling mechanism of the flows becomes more important. Therefore, the effectiveness of FD scheduling mechanism for the flows is studied in millimeter wave wireless backhaul network with the limited TS resources. We proposed a full duplex concurrent scheduling algorithm based on coalition game (FDCG) to maximize the number of flows with their QoS requirements satisfied. We transformed the problem of maximizing the number of flows with their QoS requirements satisfied into the problem of maximizing sum rate of concurrently scheduled flows in each slot. We obtained the scheduled flows with maximum sum rate in first slot by using coalition game.And then with certain restrictions, the maximum sum rate of concurrently scheduled flows can also be achieved in subsequent time slots. The simulation results show that the proposed FDCG algorithm can achieve superior performance in terms of the number of flows that meet their QoS requirements and system throughput compared with other three algorithms.

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Relay-Assisted and QoS Aware Scheduling to Overcome Blockage in mmWave Backhaul Networks

In the scenario where small cells are densely deployed, the millimeter wave (mmWave) wireless backhaul network has been widely used. However, mmWave is easily blocked by obstacles, and how to forward the data of the blocked flows is still a significant challenge. To ensure backhauling capacity, the quality of service (QoS) requirements of flows should be satisfied. In this paper, we investigate the problem of optimal scheduling to maximize the number of flows satisfying their QoS requirements with relays exploited to overcome blockage. To achieve a practical solution, we propose a relay-assisted and QoS aware scheduling scheme for the backhaul networks, called RAQS. It consists of a relay selection algorithm and a transmission scheduling algorithm. The relay selection algorithm selects non-repeating relays with high link rates for the blocked flows, which helps to achieve the QoS requirements of flows as soon as possible. Then, according to the results of relay selection, the transmission scheduling algorithm exploits concurrent transmissions to satisfy the QoS requirements of flows as much as possible. Extensive simulations show RAQS can effectively overcome the blockage problem, and increase the number of completed flows and network throughput compared with other schemes. In particular, the impact of relay selection parameter is also investigated to further guide the relay selection.

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Device-to-Device Communications Enabled Multicast Scheduling with the Multi-Level Codebook in mmWave Small Cells

With the exponential growth of mobile data, there are increasing interests to deploy small cells in millimeter wave (mmWave) bands to underlay the conventional homogeneous macrocell network as well as in exploiting device-to-device (D2D) communications to improve the efficiency of the multicast service that supports content-based mobile applications. To compensate for high propagation loss in the mmWave band, high-gain directional antennas have to be employed, while it is critical to optimize multicast service in order to improve the network performance. In this paper, an efficient multicast scheduling scheme is proposed for small cells in the mmWave band, called MD2D, where both D2D communications in close proximity and multi-level antenna codebook are utilized. Specifically, a user partition and multicast path planning algorithm is proposed to partition the users in the multicast group into subsets and to determine the transmission node for each subset, so as to achieve optimal utilization of D2D communications and multi-level antenna codebook. Then a multicast scheduling algorithm schedules the transmission for each subset. Furthermore, in order to optimize the network performance, the optimal choice of user partition thresholds is analyzed. Performance evaluation demonstrate that the MD2D achieves the best performance, in terms of network throughput and energy efficiency, compared with other existing schemes. MD2D improves the network throughput compared with the second-best scheme by about 27\%.

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Resource Allocation for Device-to-Device Communications Underlaying Heterogeneous Cellular Networks Using Coalitional Games

Heterogeneous cellular networks (HCNs) with millimeter wave (mmWave) communications included are emerging as a promising candidate for the fifth generation mobile network. With highly directional antenna arrays, mmWave links are able to provide several-Gbps transmission rate. However, mmWave links are easily blocked without line of sight. On the other hand, D2D communications have been proposed to support many content based applications, and need to share resources with users in HCNs to improve spectral reuse and enhance system capacity. Consequently, an efficient resource allocation scheme for D2D pairs among both mmWave and the cellular carrier band is needed. In this paper, we first formulate the problem of the resource allocation among mmWave and the cellular band for multiple D2D pairs from the view point of game theory. Then, with the characteristics of cellular and mmWave communications considered, we propose a coalition formation game to maximize the system sum rate in statistical average sense. We also theoretically prove that our proposed game converges to a Nash-stable equilibrium and further reaches the near-optimal solution with fast convergence rate. Through extensive simulations under various system parameters, we demonstrate the superior performance of our scheme in terms of the system sum rate compared with several other practical schemes.

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Mobility-aware Caching Scheduling for Fog Computing in mmWave Band

As an extension of cloud computing, fog computing at the edge of networks provides low latency, location awareness, and real-time interactions. At the same time, millimeter wave (mmWave) communications are able to provide directional multi-gigabit transmission rates with large available bandwidth. Based on the user mobile trajectories in a region, several activity hotspots that users pass by frequently can be obtained. By caching popular content at the edge nodes near the hotspots, users can download the cached content directly at a short distance, and the user experience can be significantly improved. Considering multiple hotspots in a region, how to efficiently schedule the transmission for the caching at edge nodes becomes a key problem. In this paper, we focus on the problem of mobility aware transmission scheduling for caching at edge nodes near hotspots, and utilize multi-hop relaying and concurrent transmissions to achieve better performance. After formulating the optimal scheduling problem as a stochastic nonlinear mixed integer program, we propose a mobility aware caching scheduling scheme, called MHRC (Multi-Hop Relaying based Caching), where multi-hop D2D paths are established for edge nodes, and concurrent transmissions are exploited in the scheduling of caching at edge nodes. Extensive performance evaluation demonstrates MHRC achieves more than 1x higher expected cached data amount compared with state-of-the-art schemes.

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Mixed-ADC/DAC Multipair Massive MIMO Relaying Systems: Performance Analysis and Power Optimization

High power consumption and expensive hardware are two bottlenecks for practical massive multiple-input multiple-output (mMIMO) systems. One promising solution is to employ low-resolution analog-to-digital converters (ADCs) and digital-to-analog converters (DACs). In this paper, we consider a general multipair mMIMO relaying system with a mixed-ADC/DAC architecture, in which some antennas are connected to low-resolution ADCs/DACs, while the rest of the antennas are connected to high-resolution ADCs/DACs. Leveraging on the additive quantization noise model, both exact and approximate closed-form expressions for the achievable rate are derived. It is shown that the achievable rate can approach the unquantized one by using only 2-3 bits of resolutions. Moreover, a power scaling law is presented to reveal that the transmit power can be scaled down inversely proportional to the number of antennas at the relay. We further propose an efficient power allocation scheme by solving a complementary geometric programming problem. In addition, a trade-off between the achievable rate and power consumption for different numbers of low-resolution ADCs/DACs is investigated by deriving the energy efficiency. Our results reveal that the large antenna array can be exploited to enable the mixed-ADC/DAC architecture, which significantly reduces the power consumption and hardware cost for practical mMIMO systems.

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Deep Learning Based Fast Multiuser Detection for Massive Machine-Type Communication

Massive machine-type communication (MTC) with sporadically transmitted small packets and low data rate requires new designs on the PHY and MAC layer with light transmission overhead. Compressive sensing based multiuser detection (CS-MUD) is designed to detect active users through random access with low overhead by exploiting sparsity, i.e., the nature of sporadic transmissions in MTC. However, the high computational complexity of conventional sparse reconstruction algorithms prohibits the implementation of CS-MUD in real communication systems. To overcome this drawback, in this paper, we propose a fast Deep learning based approach for CS-MUD in massive MTC systems. In particular, a novel block restrictive activation nonlinear unit, is proposed to capture the block sparse structure in wide-band wireless communication systems (or multi-antenna systems). Our simulation results show that the proposed approach outperforms various existing algorithms for CS-MUD and allows for ten-fold decrease of the computing time.

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Physical Layer Security over Fluctuating Two-Ray Fading Channels

Ensuring the physical layer security (PHY-security) of millimeter wave (mmWave) communications is one of the key factors for the success of 5G. Recent field measurements show that conventional fading models cannot accurately model the random fluctuations of mmWave signals. To tackle this challenge, the fluctuating two-ray (FTR) fading model has been proposed. In this correspondence, we comprehensively analyze the PHY-security in mmWave communications over FTR fading channels. More specifically, we derive analytical expressions for significant PHY-security metrics, such as average secrecy capacity, secrecy outage probability, and the probability of strictly positive secrecy capacity, with simple functions. The effect of channel parameters on the PHY-security has been validated by numerical results.

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Millimeter-Wave Propagation Modeling and Measurement

Millimeter wave (mmWave) communication is one of the most promising technologies in fifth generation (5G) mobile networks due to its access to a large amount of available spectrum resources. Despite the theoretical potential of a high data rate, there are still several key technical challenges with using mmWave in mobile networks, such as severe pathloss, high penetration loss, narrow beamwidth, etc. Hence, accurate and reliable knowledge of mmWave channel propagation characteristics is essential for developing 5G wireless communication systems. In this article, the fundamental characteristics of mmWave are first presented. Then, two main channel modeling methods are discussed. Finally, in order to investigate the channel characteristics at the mmWave band, measurement campaigns using three different large-scale array topologies are carried out and the typical channel parameters are extracted and analyzed.

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Spatial Modulation Aided Layered Division Multiplexing: A Spectral Efficiency Perspective

In this paper, spatial modulation (SM) is introduced to layered division multiplexing (LDM) systems for enlarging the spectral efficiency over broadcasting transmission. Firstly, the SM aided LDM (SM-LDM) system is proposed, in which different layered services utilize SM for terrestrial broadcasting transmission with different power levels. Then a spectral efficiency (SE) analysis framework for SM-LDM systems is proposed, which is suitable for the SM-LDM systems with linear combining. Moreover, the closed-form SE lower bound of SM-LDM systems with maximum ratio combining (MRC) is derived, which is based on this framework. Since the theoretical SE analysis of single transmit antenna (TA) LDM systems with MRC and spatial multiplexing (SMX) aided LDM systems with MRC lacks a closed-form expression, the closed-form SE is also derived for these systems. Monte Carlo simulations are provided to verify the tightness of our proposed SE lower bound. Furthermore, it can be shown via simulations that our proposed SM-LDM systems always have a better SE performance than single-TA LDM systems, which can even outperform the SE of SMX aided LDM (SMX-LDM) systems.

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Spectral Efficiency of Multipair Massive MIMO Two-Way Relaying with Hardware Impairments

We consider a multipair massive multiple-input multiple-output (MIMO) two-way relaying system, where multiple pairs of single-antenna devices exchange data with the help of a relay employing a large number of antennas $N$. The relay consists of low-cost components that suffer from hardware impairments. A large-scale approximation of the spectral efficiency (SE) with maximum ratio (MR) processing is derived in closed form, and the approximation is tight as $N \to \infty$. It is revealed that for a fixed hardware quality, the impact of the hardware impairments vanishes asymptotically when $N$ grows large. Moreover, the impact of the impairments may even vanish when the hardware quality is gradually decreased with $N$, if a scaling law is satisfied. Finally, numerical results validate that multipair massive MIMO two-way relaying systems are robust to hardware impairments at the relay.

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Waveform Candidates for 5G Networks: Analysis and Comparison

As the next generation cellular system, 5G network is required to provide a large variety of services for different kinds of terminals, from traditional voice and data services over mobile phones to small packet transmission over massive machine-type terminals. Although orthogonal-subcarrier based waveform has been widely used nowadays in many practical systems, it can hardly meet the future requirements in the coming 5G networks. Therefore, more flexible waveforms have been proposed to address the unprecedented challenges. In this article, we will provide comprehensive analysis and comparison for the typical waveform candidates. To obtain insightful analysis, we will not only introduce the basic principles of the waveforms but also reveal the underlying characteristics of each waveform. Moreover, a comprehensive comparison in terms of different performance metrics will be also presented in this article, which provide an overall understanding of the new waveforms.

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A Survey on High-Speed Railway Communications: A Radio Resource Management Perspective

High-speed railway (HSR) communications will become a key feature supported by intelligent transportation communication systems. The increasing demand for HSR communications leads to significant attention on the study of radio resource management (RRM), which enables efficient resource utilization and improved system performance. RRM design is a challenging problem due to heterogenous quality of service (QoS) requirements and dynamic characteristics of HSR wireless communications. The objective of this paper is to provide an overview on the key issues that arise in the RRM design for HSR wireless communications. A detailed description of HSR communication systems is first presented, followed by an introduction on HSR channel models and characteristics, which are vital to the cross-layer RRM design. Then we provide a literature survey on state-of-the-art RRM schemes for HSR wireless communications, with an in-depth discussion on various RRM aspects including admission control, mobility management, power control and resource allocation. Finally, this paper outlines the current challenges and open issues in the area of RRM design for HSR wireless communications.

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Quality of Service Improvement for High-Speed Railway Communications

With the fast development of high-speed railways, a call for fulfilling the notion of communication at "anytime, anywhere" for high-speed train passengers in the Train Operating Control System is on the way. In order to make a realization of that, new railway wireless communication networks are needed. The most promising one is the Long Term Evolution for Railway which will provide broadband access, fast handover, and reliable communication for high mobility users. However, with the increase of speed, the system is subjected to high bit error rate, Doppler frequency shift and handover failure just like other system does. This paper is trying to solve these problems by employing MIMO technique. Specifically, the goal is to provide higher data rate, higher reliability, less delay, and other relative quality of services for passengers. MIMO performance analysis, resource allocation, and access control for handover and various services in a two-hop model are proposed in this paper. Analytical results and simulation results show that the proposed model and schemes perform well in improving the system performances.

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