- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Using Physics Models to Analyze Aggregate Inline Measurement Data
摘要： A dilemma in cloud radio access networks (C-RANs) is how to keep a balance between the performance and the ef?ciency of centralized processing. To solve this problem, the joint design of training-based channel estimation and cluster formation are studied in this paper. To provide ef?cient cooperation strategies in C-RANs, individual C-RAN clusters are formed by the remote radio heads (RRHs), and a data-assisted channel estimation scheme is studied, which can reduce the redundant cost of training sequences. To ensure the performance of channel estimation and data transmissions, the cluster formation and the channel estimation are optimized jointly. In particular, an iterative training-based channel estimation scheme is designed by using convex optimization and the Broyden–Fletcher–Goldfarb–Shanno algorithm jointly. Moreover, a utility function of cluster formation can be established based on the estimates and the mean squared error of our proposed channel estimation algorithm, and the cluster formation of RRHs can be formulated as a coalitional formation game. Furthermore, a sub-optimal algorithm is also proposed to reduce the computational complexity. Finally, the simulation results are shown to evaluate the performance of our proposed algorithms.
关键词： optimization,Cloud-radio access networks,cluster formation,channel estimation,game theory
更新于2025-09-23 15:19:57
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Accelerated Degradation Test Investigation for Life-time Performance Analysis of LED Luminaires
摘要： As it becomes increasingly apparent that 4G will not be able to meet the emerging demands of future mobile communication systems, the question what could make up a 5G system, what are the crucial challenges, and what are the key drivers is part of intensive, ongoing discussions. Partly due to the advent of compressive sensing, methods that can optimally exploit sparsity in signals have received tremendous attention in recent years. In this paper, we will describe a variety of scenarios in which signal sparsity arises naturally in 5G wireless systems. Signal sparsity and the associated rich collection of tools and algorithms will thus be a viable source for innovation in 5G wireless system design. We will also describe applications of this sparse signal processing paradigm in Multiple Input Multiple Output random access, cloud radio access networks, compressive channel-source network coding, and embedded security. We will also emphasize an important open problem that may arise in 5G system design, for which sparsity will potentially play a key role in their solution.
关键词： massive random access,cloud radio access networks,embedded security,Compressed sensing,source coding
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE 3rd Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC) - Chongqing, China (2019.10.11-2019.10.13)] 2019 IEEE 3rd Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC) - Research on Laser Cavity Ring-down Spectroscopy Measurement for SF6 Decomposed Gases
摘要： As it becomes increasingly apparent that 4G will not be able to meet the emerging demands of future mobile communication systems, the question what could make up a 5G system, what are the crucial challenges, and what are the key drivers is part of intensive, ongoing discussions. Partly due to the advent of compressive sensing, methods that can optimally exploit sparsity in signals have received tremendous attention in recent years. In this paper, we will describe a variety of scenarios in which signal sparsity arises naturally in 5G wireless systems. Signal sparsity and the associated rich collection of tools and algorithms will thus be a viable source for innovation in 5G wireless system design. We will also describe applications of this sparse signal processing paradigm in Multiple Input Multiple Output random access, cloud radio access networks, compressive channel-source network coding, and embedded security. We will also emphasize an important open problem that may arise in 5G system design, for which sparsity will potentially play a key role in their solution.
关键词： massive random access,cloud radio access networks,embedded security,Compressed sensing,source coding
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Modulation of Conductivity in Manganese Vanadium Oxide
摘要： Cloud radio access network (C-RAN) and massive multiple-input multiple-output (MIMO) are recognized as two key technologies for the fifth-generation mobile networks. In this paper, we consider the energy efficiency-based user association problem in massive MIMO empowered C-RAN, where multiple antennae are clustered at each remote radio head (RRH). We first obtain the deterministic equivalent expression of the energy efficiency, and then propose three user association algorithms, named nearest-based user association (NBUA), single-candidate RRH user association (SCRUA), and multi-candidate RRHs user association (MCRUA), respectively. In NBUA and SCRUA, each user is associated with only one RRH, and in MCRUA, multiple RRHs can serve the same user. In our algorithms, the impact of the power consumption of fronthaul links and antennas is considered by allowing inefficient RRHs to be turned into sleep mode. We provide the numerical comparisons of the proposed algorithms and a state-of-the-art baseline, which associates each user with the nearest RRH. The results show that our proposed algorithms achieve higher energy efficiency than the baseline algorithm. The proposed MCRUA algorithm achieves a good balance between spectral and energy efficiency, and the performance gain is more significant when the number of users is large.
关键词： Cloud radio access networks,energy efficiency,massive MIMO,user association
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Effect of irradiance data on the optimal sizing of photovoltaic water pumping systems
摘要： Cloud radio access network (C-RAN) and massive multiple-input multiple-output (MIMO) are recognized as two key technologies for the fifth-generation mobile networks. In this paper, we consider the energy efficiency-based user association problem in massive MIMO empowered C-RAN, where multiple antennae are clustered at each remote radio head (RRH). We first obtain the deterministic equivalent expression of the energy efficiency, and then propose three user association algorithms, named nearest-based user association (NBUA), single-candidate RRH user association (SCRUA), and multi-candidate RRHs user association (MCRUA), respectively. In NBUA and SCRUA, each user is associated with only one RRH, and in MCRUA, multiple RRHs can serve the same user. In our algorithms, the impact of the power consumption of fronthaul links and antennas is considered by allowing inefficient RRHs to be turned into sleep mode. We provide the numerical comparisons of the proposed algorithms and a state-of-the-art baseline, which associates each user with the nearest RRH. The results show that our proposed algorithms achieve higher energy efficiency than the baseline algorithm. The proposed MCRUA algorithm achieves a good balance between spectral and energy efficiency, and the performance gain is more significant when the number of users is large.
关键词： user association,Cloud radio access networks,energy efficiency,massive MIMO
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE 4th Optoelectronics Global Conference (OGC) - Shenzhen, China (2019.9.3-2019.9.6)] 2019 IEEE 4th Optoelectronics Global Conference (OGC) - Optimal Design of High Energy Similariton Thulium-Doped Fiber Lasers
摘要： To decrease the training overhead and improve the channel estimation accuracy in uplink cloud radio access networks (C-RANs), a superimposed-segment training design is proposed. The core idea of the proposal is that each mobile station superimposes a periodic training sequence on the data signal, and each remote radio head prepends a separate pilot to the received signal before forwarding it to the centralized base band unit pool. Moreover, a complex-exponential basis-expansion-model based channel estimation algorithm to maximize a posteriori probability is developed. Simulation results show that the proposed channel estimation algorithm can effectively decrease the estimation mean square error and increase the average effective signal-to-noise ratio (AESNR) in C-RANs.
关键词： cloud radio access networks,Channel estimation
更新于2025-09-19 17:13:59