arXiv subjects

Lingyang Song

Publications and source records attributed to Lingyang Song.

At least 73 records · Page 4Linked to original sources

arXiv2020

Reconfigurable Intelligent Surface (RIS) Assisted Wireless Coverage Extension: RIS Orientation and Location Optimization

Recently, reconfigurable intelligent surfaces (RIS) have attracted a lot of attention due to their capability of extending cell coverage by reflecting signals toward the receiver. In this letter, we analyze the coverage of a downlink RIS-assisted network with one base station (BS) and one user equipment (UE). Since the RIS orientation and the horizontal distance between the RIS and the BS have a significant influence on the cell coverage, we formulate an RIS placement optimization problem to maximize the cell coverage by optimizing the RIS orientation and horizontal distance. To solve the formulated problem, a coverage maximization algorithm (CMA) is proposed, where a closed-form optimal RIS orientation is obtained. Numerical results verify our analysis.

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arXiv2020

Sense-Store-Send: Trajectory Optimization for a Buffer-aided Internet of UAVs

In this letter, we study a buffer-aided Internet of unmanned aerial vehicles (UAVs) in which a UAV performs data sensing, stores the data, and sends it to the base station (BS) in cellular networks. To minimize the overall completion time for all the sensing tasks, we formulate a joint trajectory, sensing location, and sensing time optimization problem. To solve this NP-hard problem efficiently, we propose an iterative trajectory, sensing location and sensing time optimization (ITLTO) algorithm, and discuss the trade-off between sensing time and flying time. Simulation results show that the proposed algorithm can effectively reduce the completion time for the sensing tasks.

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arXiv2020

Beyond Intelligent Reflecting Surfaces: Reflective-Transmissive Metasurface Aided Communications for Full-dimensional Coverage Extension

In this paper, we study an intelligent omni-surface (IOS)-assisted downlink communication system, where the link quality of a mobile user (MU) can be improved with a proper IOS phase shift design. Unlike the intelligent reflecting surface (IRS) in most existing works that only forwards the signals in a reflective way, the IOS is capable to forward the received signals to the MU in either a reflective or a transmissive manner, thereby enhancing the wireless coverage. We formulate an IOS phase shift optimization problem to maximize the downlink spectral efficiency (SE) of the MU. The optimal phase shift of the IOS is analysed, and a branch-and-bound based algorithm is proposed to design the IOS phase shift in a finite set. Simulation results show that the IOS-assisted system can extend the coverage significantly when compared to the IRS-assisted system with only reflective signals.

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arXiv2020

On Spatial Multiplexing Using Reconfigurable Intelligent Surfaces

We consider an uplink multi-user scenario and investigate the use of reconfigurable intelligent surfaces (RIS) to optimize spatial multiplexing performance when a linear receiver is used. We study two different formulations of the problem, namely maximizing the effective rank and maximizing the minimum singular value of the RIS-augmented channel. We employ gradient-based optimization to solve the two problems and compare the solutions in terms of the sum-rate achievable when a linear receiver is used. Our results show that the proposed criteria can be used to optimize the RIS to obtain effective channels with favorable properties and drastically improve performance even when the propagation through the RIS contributes a small fraction of the received power.

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arXiv2020

Cooperative Internet of UAVs: Distributed Trajectory Design by Multi-agent Deep Reinforcement Learning

Due to the advantages of flexible deployment and extensive coverage, unmanned aerial vehicles (UAVs) have great potential for sensing applications in the next generation of cellular networks, which will give rise to a cellular Internet of UAVs. In this paper, we consider a cellular Internet of UAVs, where the UAVs execute sensing tasks through cooperative sensing and transmission to minimize the age of information (AoI). However, the cooperative sensing and transmission is tightly coupled with the UAVs' trajectories, which makes the trajectory design challenging. To tackle this challenge, we propose a distributed sense-and-send protocol, where the UAVs determine the trajectories by selecting from a discrete set of tasks and a continuous set of locations for sensing and transmission. Based on this protocol, we formulate the trajectory design problem for AoI minimization and propose a compound-action actor-critic (CA2C) algorithm to solve it based on deep reinforcement learning. The CA2C algorithm can learn the optimal policies for actions involving both continuous and discrete variables and is suited for the trajectory design. {Our simulation results show that the CA2C algorithm outperforms four baseline algorithms}. Also, we show that by dividing the tasks, cooperative UAVs can achieve a lower AoI compared to non-cooperative UAVs.

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arXiv2020

Reconfigurable Intelligent Surface Assisted Device-to-Device Communications

With the evolution of the 5G, 6G and beyond, device-to-device (D2D) communication has been developed as an energy-, and spectrum-efficient solution. In cellular network, D2D links need to share the same spectrum resources with the cellular link. A reconfigurable intelligent surface (RIS) can reconfigure the phase shifts of elements and create favorable beam steering, which can mitigate aggravated interference caused by D2D links. In this paper, we study a RIS-assisted single cell uplink communication network scenario, where the cellular link and multiple D2D links utilize direct propagation and reflecting one-hop propagation. The problem of maximizing the total system rate is formulated by jointly optimizing transmission powers of all links and discrete phase shifts of all elements. The formulated problem is an NP-hard mixed integer non-convex non-linear problem. To obtain practical solutions, we capitalize on alternating maximization and the problem is decomposed into two sub-problems. For the power allocation, the problem is a difference of concave functions (DC) problem, which is solved with the gradient descent method. For the phase shift, a local search algorithm with lower complexity is utilized. Simulation results show that deploying RIS and optimizing the phase shifts have a significant effect on mitigating D2D network interference.

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arXiv2020

Reconfigurable Intelligent Surface (RIS)-Enhanced Two-Way OFDM Communications

In this paper, we focus on the reconfigurable intelligent surface (RIS)-enhanced two-way device-to-device (D2D) multi-pair orthogonal-frequency-division-multiplexing (OFDM) communication systems. Specifically, we maximize the minimum bidirectional weighted sum-rate by jointly optimizing the sub-band allocation, the power allocation and the discrete phase shift (PS) design at the RIS. To tackle the main difficulty of the non-convex PS design at the RIS, we firstly formulate a semi-definite relaxation problem and further devise a low-complexity solution for the PS design by leveraging the projected sub-gradient method. We demonstrate the desirable performance gain for the proposed designs through numerical results.

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arXiv2020

Reconfigurable Intelligent Surfaces for Wireless Communications: Principles, Challenges, and Opportunities

Recently there has been a flurry of research on the use of reconfigurable intelligent surfaces (RIS) in wireless networks to create smart radio environments. In a smart radio environment, surfaces are capable of manipulating the propagation of incident electromagnetic waves in a programmable manner to actively alter the channel realization, which turns the wireless channel into a controllable system block that can be optimized to improve overall system performance. In this article, we provide a tutorial overview of reconfigurable intelligent surfaces (RIS) for wireless communications. We describe the working principles of reconfigurable intelligent surfaces (RIS) and elaborate on different candidate implementations using metasurfaces and reflectarrays. We discuss the channel models suitable for both implementations and examine the feasibility of obtaining accurate channel estimates. Furthermore, we discuss the aspects that differentiate RIS optimization from precoding for traditional MIMO arrays highlighting both the arising challenges and the potential opportunities associated with this emerging technology. Finally, we present numerical results to illustrate the power of an RIS in shaping the key properties of a MIMO channel.

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arXiv2020

Beyond D2D: Full Dimension UAV-to-Everything Communications in 6G

In this paper, we consider an Internet of unmanned aerial vehicles (UAVs) over cellular networks, where UAVs work as aerial users to collect various sensory data, and send the collected data to their transmission destinations over cellular links. Unlike the terrestrial users in the conventional cellular networks, different UAVs have various communication requirements due to their sensing applications, and a more flexible communication framework is in demand. To tackle this problem, we propose a UAV-to-Everything (U2X) networking, which enables the UAVs to adjust their communication modes full dimensionally according to the requirements of their sensing applications. In this article, we first introduce the concept of U2X communications, and elaborate on its three communication modes. Afterwards, we discuss the key techniques of the U2X communications, including joint sensing and transmission protocol, UAV trajectory design, and radio resource management. A reinforcement learning-based mathematical framework for U2X communications is then proposed. Finally, the extensions of the U2X communications are presented.

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arXiv2020

UAV-to-Device Underlay Communications: Age of Information Minimization by Multi-agent Deep Reinforcement Learning

In recent years, unmanned aerial vehicles (UAVs) have found numerous sensing applications, which are expected to add billions of dollars to the world economy in the next decade. To further improve the Quality-of-Service (QoS) in such applications, the 3rd Generation Partnership Project (3GPP) has considered the adoption of terrestrial cellular networks to support UAV sensing services, also known as the cellular Internet of UAVs. In this paper, we consider a cellular Internet of UAVs, where the sensory data can be transmitted either to base station (BS) via cellular links, or to mobile devices by underlay UAV-to-Device (U2D) communications. To evaluate the freshness of data, the age of information (AoI) is adopted, in which a lower AoI implies fresher data. Since UAVs' AoIs are determined by their trajectories during sensing and transmission, we investigate the AoI minimization problem for UAVs by designing their trajectories. This problem is a Markov decision problem (MDP) with an infinite state-action space, and thus we utilize multi-agent deep reinforcement learning (DRL) to approximate the state-action space. Then, we propose a multi-UAV trajectory design algorithm to solve this problem. Simulation results show that our algorithm achieves a lower AoI than greedy algorithm and policy gradient algorithm.

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arXiv2020

Deep Learning for Ultra-Reliable and Low-Latency Communications in 6G Networks

In the future 6th generation networks, ultra-reliable and low-latency communications (URLLC) will lay the foundation for emerging mission-critical applications that have stringent requirements on end-to-end delay and reliability. Existing works on URLLC are mainly based on theoretical models and assumptions. The model-based solutions provide useful insights, but cannot be directly implemented in practice. In this article, we first summarize how to apply data-driven supervised deep learning and deep reinforcement learning in URLLC, and discuss some open problems of these methods. To address these open problems, we develop a multi-level architecture that enables device intelligence, edge intelligence, and cloud intelligence for URLLC. The basic idea is to merge theoretical models and real-world data in analyzing the latency and reliability and training deep neural networks (DNNs). Deep transfer learning is adopted in the architecture to fine-tune the pre-trained DNNs in non-stationary networks. Further considering that the computing capacity at each user and each mobile edge computing server is limited, federated learning is applied to improve the learning efficiency. Finally, we provide some experimental and simulation results and discuss some future directions.

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arXiv2020

Sensing and Communication Tradeoff Design for AoI Minimization in a Cellular Internet of UAVs

In this paper, we consider the cellular Internet of unmanned aerial vehicles (UAVs), where UAVs sense data for multiple tasks and transmit the data to the base station (BS). To quantify the "freshness" of the data at the BS, we bring in the concept of the age of information (AoI). The AoI is determined by the time for UAV sensing and that for UAV transmission, and gives rise to a trade-off within a given period. To minimize the AoI, we formulate a joint sensing time, transmission time, UAV trajectory, and task scheduling optimization problem. To solve this problem, we first propose an iterative algorithm to optimize the sensing time, transmission time, and UAV trajectory for completing a specific task. Afterwards, we design the order in which the UAV performs data updates for multiple sensing tasks. The convergence and complexity of the proposed algorithm, together with the trade-off between UAV sensing and UAV transmission, are analyzed. Simulation results verify the effectiveness of our proposed algorithm.

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arXiv2020

Reconfigurable Intelligent Surfaces assisted Communications with Limited Phase Shifts: How Many Phase Shifts Are Enough?

Reconfigurable intelligent surface~(RIS) has drawn a great attention worldwide as it can create favorable propagation conditions by controlling the phase shifts of the reflected signals at the surface to enhance the communication quality. However, the practical RIS only has limited phase shifts, which will lead to the performance degradation. In this letter, we evaluate the performance of an uplink RIS assisted communication system by giving an approximation of the achievable data rate, and investigate the effect of limited phase shifts on the data rate. In particular, we derive the required number of phase shifts under a data rate degradation constraint. Numerical results verify our analysis.

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arXiv2019

Reconfigurable Intelligent Surfaces based RF Sensing: Design, Optimization, and Implementation

Using radio-frequency (RF) sensing techniques for human posture recognition has attracted growing interest due to its advantages of pervasiveness, contact-free observation, and privacy protection. Conventional RF sensing techniques are constrained by their radio environments, which limit the number of transmission channels to carry multi-dimensional information about human postures. Instead of passively adapting to the environment, in this paper, we design an RF sensing system for posture recognition based on reconfigurable intelligent surfaces (RISs). The proposed system can actively customize the environments to provide the desirable propagation properties and diverse transmission channels. However, achieving high recognition accuracy requires the optimization of RIS configuration, which is a challenging problem. To tackle this challenge, we formulate the optimization problem, decompose it into two subproblems and propose algorithms to solve them. Based on the developed algorithms, we implement the system and carry out practical experiments. Both simulation and experimental results verify the effectiveness of the designed algorithms and system. Compared to the random configuration and non-configurable environment cases, the designed system can greatly improve the recognition accuracy.

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arXiv2019

Hybrid Precoding Design for Reconfigurable Intelligent Surface aided mmWave Communication Systems

In this letter, we focus on the hybrid precoding (HP) design for the reconfigurable intelligent surface (RIS) aided multi-user (MU) millimeter wave (mmWave) communication systems. Specifically, we aim to minimize the mean-squared-error (MSE) between the received symbols and the transmitted symbols by jointly optimizing the analog-digital HP at the base-station (BS) and the phase shifts (PSs) at the RIS, where the non-convex element-wise constant-modulus constraints for the analog precoding and the PSs are tackled by resorting to the gradient-projection (GP) method. We analytically prove the convergence of the proposed algorithm and demonstrate the desirable performance gain for the proposed design through numerical results.

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arXiv2019

Reinforcement Learning for a Cellular Internet of UAVs: Protocol Design, Trajectory Control, and Resource Management

Unmanned aerial vehicles (UAVs) can be powerful Internet-of-Things components to execute sensing tasks over the next-generation cellular networks, which are generally referred to as the cellular Internet of UAVs. However, due to the high mobility of UAVs and the shadowing in the air-to-ground channels, UAVs operate in an environment with dynamics and uncertainties. Therefore, UAVs need to improve the quality of service (QoS) of sensing and communication without complete information, which makes reinforcement learning suitable to be employed in the cellular Internet of UAVs. In this article, we propose a distributed sense-and-send protocol to coordinate the UAVs for sensing and transmission. Then, we apply reinforcement learning in the cellular Internet of UAVs to solve key problems such as trajectory control and resource management. Finally, we point out several potential future research directions.

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arXiv2019

Device-to-Device Communications Underlaying Cellular Networks: To Use Unlicensed Spectrum or Not?

In this paper, we consider device-to-device (D2D) communications as an underlay to the cellular networks over both licensed and unlicensed spectrum, where Long Term Evolution (LTE) users utilize the spectrum orthogonally while D2D users share the spectrum with LTE users. In the system, each LTE and D2D user can access the licensed or unlicensed band for communications. To maximize the total throughput of the system, we leverage stochastic geometry to derive the throughput for each kind of users by modeling the deployment of users as Poisson point processes (PPPs), and investigate the spectrum access problem for these users. Since the problem is NP-hard, we propose a sequential quadratic programming (SQP) based algorithm to obtain the corresponding suboptimal solutions. Theoretically, we evaluate the system performance by analyzing the throughput regions. Simulation results validate the accuracy of the geometric analysis and verify the effectiveness of the proposed algorithm.

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arXiv2019

Hybrid Beamforming for Reconfigurable Intelligent Surface based Multi-user Communications: Achievable Rates with Limited Discrete Phase Shifts

Reconfigurable intelligent surface (RIS) has drawn considerable attention from the research society recently, which creates favorable propagation conditions by controlling the phase shifts of the reflected waves at the surface, thereby enhancing wireless transmissions. In this paper, we study a downlink multi-user system where the transmission from a multi-antenna base station (BS) to various users is achieved by the RIS reflecting the incident signals of the BS towards the users. Unlike most existing works, we consider the practical case where only a limited number of discrete phase shifts can be realized by the finite-sized RIS. Based on the reflection-dominated one-hop propagation model between the BS and users via the RIS, a hybrid beamforming scheme is proposed and the sum-rate maximization problem is formulated. Specifically, the continuous digital beamforming and discrete RIS-based analog beamforming are performed at the BS and the RIS, respectively, and an iterative algorithm is designed to solve this problem. Both theoretical analysis and numerical validations show that the RIS-based system can achieve a good sum-rate performance by setting a reasonable size of RIS and a small number of discrete phase shifts.

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