MEC-Assisted Immersive VR Video Streaming Over Terahertz Wireless Networks: A Deep Reinforcement Learning Approach

Du, Jianbo; Yu, F. Richard; Lu, Guangyue; Wang, Junxuan; Jiang, Jing; Chu, Xiaoli

doi:10.1109/jiot.2020.3003449

Cited by 221 publications

(88 citation statements)

References 40 publications

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“…5G systems aim to provide a peak data rate of 10 Gbps per user [2] while 6G is expected to enhance capacity 10-100 times over 5G [3]. In addition to cellular network capacity demands, local wireless networks are expected to support Tbps data rates [4] to realize super bandwidth-hungry applications such as wireless virtual reality (VR) [5].…”

mentioning

confidence: 99%

Analyzing the Impact of Molecular Re-Radiation on the MIMO Capacity in High-Frequency Bands

Hoseini

Ding

Hassan

et al. 2020

IEEE Trans. Veh. Technol.

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In this paper, we show how the absorption and reradiation energy from molecules in the air can influence the Multiple Input Multiple Output (MIMO) performance in highfrequency bands, e.g., millimeter wave (mmWave) and terahertz. In more detail, some common atmosphere molecules, such as oxygen and water, can absorb and re-radiate energy in their natural resonance frequencies, such as 60 GHz, 180 GHz and 320 GHz. Hence, when hit by electromagnetic waves, molecules will get excited and absorb energy, which leads to an extra path loss and is known as molecular attenuation. Meanwhile, the absorbed energy will be re-radiated towards a random direction with a random phase. These re-radiated waves also interfere with the signal transmission. Although, the molecular re-radiation was mostly considered as noise in literature, recent works show that it is correlated to the main signal and can be viewed as a composition of multiple delayed or scattered signals. Such a phenomenon can provide non-line-of-sight (NLoS) paths in an environment that lacks scatterers, which increases spatial multiplexing and thus greatly enhances the performance of MIMO systems. Therefore in this paper, we explore the scattering model and noise models of molecular re-radiation to characterize the channel transfer function of the NLoS channels created by atmosphere molecules. Our simulation results show that the re-radiation can increase MIMO capacity up to 3 folds in mmWave and 6 folds in terahertz for a set of realistic transmit power, distance, and antenna numbers. We also show that in the high SNR, the re-radiation makes the open-loop precoding viable, which is an alternative to beamforming to avoid beam alignment sensitivity in high mobility applications.

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confidence: 99%

Analyzing the Impact of Molecular Re-Radiation on the MIMO Capacity in High-Frequency Bands

Hoseini

Ding

Hassan

et al. 2020

IEEE Trans. Veh. Technol.

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“…e United States and Japan were dedicated to artificial intelligence research in the 1980s and 1990s which promoted the peak of the second development. Benefiting from the breakthrough of deep learning and reinforcement learning algorithms, the exponential growth of network data and the qualitative leap in computing power, artificial intelligence has entered the third period of rapid development [19,20]. Artificial intelligence includes the following key technologies: computational vision technology, natural language processing technology, cross-media reasoning technology, intelligent adaptive learning technology, swarm intelligence technology, autonomous drone system technology, smart chip technology, and brain-computer interface technology, which can be widely used in various industries, such as healthcare, driverless cars [21], education development, games, entertainment, Internet of ings [22,23], maritime Internet of ings [24,25], and communication networks [26,27].…”

Section: Artificial Intelligence Technologymentioning

confidence: 99%

Recent Advances in Blockchain and Artificial Intelligence Integration: Feasibility Analysis, Research Issues, Applications, Challenges, and Future Work

Zhang¹,

Song

Liu

et al. 2021

Security and Communication Networks

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Blockchain constructs a distributed point-to-point system, which is a secure and verifiable mechanism for decentralized transaction validation and is widely used in financial economy, Internet of Things, large data, cloud computing, and edge computing. On the other hand, artificial intelligence technology is gradually promoting the intelligent development of various industries. As two promising technologies today, there is a natural advantage in the convergence between blockchain and artificial intelligence technologies. Blockchain makes artificial intelligence more autonomous and credible, and artificial intelligence can prompt blockchain toward intelligence. In this paper, we analyze the combination of blockchain and artificial intelligence from a more comprehensive and three-dimensional point of view. We first introduce the background of artificial intelligence and the concept, characteristics, and key technologies of blockchain and subsequently analyze the feasibility of combining blockchain with artificial intelligence. Next, we summarize the research work on the convergence of blockchain and artificial intelligence in home and overseas within this category. After that, we list some related application scenarios about the convergence of both technologies and also point out existing problems and challenges. Finally, we discuss the future work.

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“…erefore, each miner can execute tasks locally or offload to the MEC server m (AP m) or cloud center for execution. We use x n , y n , and z n to denote the task of miner n is processed by miner n itself, or by MEC server m, or the cloud center, respectively [3,22].…”

Section: System Modelmentioning

confidence: 99%

Cost-Effective Optimization for Blockchain-Enabled NOMA-Based MEC Networks

Sun

et al. 2021

Security and Communication Networks

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Blockchain technology has been widely used in many fields. However, the proof of work (PoW) problem in the mining process of mobile devices requires a large amount of computing resources and energy consumption, which brings huge challenges to mobile devices. Mobile edge computing (MEC) can effectively solve the above problems, allowing mobile devices to offload tasks to edge servers to relieve the pressure of limited computing resources on mobile devices. Nonorthogonal multiple access (NOMA) is good at improving spectrum efficiency, so that the system can accommodate more users. In this paper, we propose a new NOMA-based MEC-enabled blockchain framework. Under the conditions of a given task execution deadline, the decision of offloading, local computing resource allocation, user clustering and admission control, and transmit power control is jointly optimized to minimize the total cost of the system. Since the problem is hard to solve, we decouple it into subproblems for low-complexity solutions. First, we propose two heuristic algorithms to obtain the binary offloading decision and user association, and then closed-form solutions of local resource allocation and transmit power control are obtained under the required delay constraints. Simulation results show that our proposed algorithms perform good in cost reduction compared with other baseline algorithms.

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MEC-Assisted Immersive VR Video Streaming Over Terahertz Wireless Networks: A Deep Reinforcement Learning Approach

Abstract: This is a repository copy of MEC-assisted immersive VR video streaming over terahertz wireless networks: A deep reinforcement learning approach.

Cited by 221 publications

References 40 publications

Analyzing the Impact of Molecular Re-Radiation on the MIMO Capacity in High-Frequency Bands

Analyzing the Impact of Molecular Re-Radiation on the MIMO Capacity in High-Frequency Bands

Recent Advances in Blockchain and Artificial Intelligence Integration: Feasibility Analysis, Research Issues, Applications, Challenges, and Future Work

Cost-Effective Optimization for Blockchain-Enabled NOMA-Based MEC Networks

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