scholarly journals Energy-Efficient Resource Allocation for NOMA-Enabled Internet of Vehicles

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xin Chen ◽  
Zhuo Ma ◽  
Teng Ma ◽  
Xu Liu ◽  
Ying Chen
Keyword(s):  
Resource Allocation ◽  
Multiple Access ◽  
High Reliability ◽  
Rapid Development ◽  
Computation Time ◽  
Allocation Model ◽  
Internet Of Vehicles ◽  
V2v Communication ◽  
Markov Decision ◽  
Energy Efficient Resource Allocation

With the rapid development of Internet of vehicles (IoV) technology, the distribution of vehicles on the highway becomes more dense and the highly reliable communication between vehicles becomes more important. Nonorthogonal multiple access (NOMA) is a promising technology to meet the multiple access volume and the high reliability communication demands of IoV. To meet the Vehicle-to-Vehicle (V2V) communication requirements, a NOMA-based IoV system is proposed. Firstly, a NOMA-based resource allocation model in IoV is developed to maximize the energy efficiency (EE) of the system. Secondly, the established model is transformed into a Markov decision process (MDP) model and a deep reinforcement learning-based subchannel and power allocation (DSPA) algorithm is designed. An event trigger block is used to reduce computation time. Finally, the simulation results show that NOMA can significantly improve the system performance compared to orthogonal multiaccess, and the proposed DSPA algorithm can significantly improve the system EE and reduce the computation time.

A multi-sided market of personal data resource allocation: An empirical study of China’s car-hailing platform

2021 ◽  
pp. 178359172110512
Author(s):  
Lei Huang ◽  
Miltos Ladikas ◽  
Guangxi He ◽  
Julia Hahn ◽  
Jens Schippl
Keyword(s):  
Resource Allocation ◽  
Market Structure ◽  
Market Competition ◽  
Rapid Development ◽  
Personal Data ◽  
Application Programming Interface ◽  
Allocation Mechanism ◽  
Allocation Model ◽  
Data Resource ◽  
Technology And Economy

The current rapid development of online car-hailing services creates a serious challenge to the existing paradigm of market governance and antitrust policy. However, the debate on the market structure of the car-hailing platform requires more empirical evidence to uncover its functions. This research adopts an interdisciplinary methodology based on computer science and economics, and including software reverse engineering tools applied to the interoperability of the terminal application and resource allocation model, to demonstrate the topological market structure of personal data resources allocation in China’s car-hailing industry. Within the discussion of the hybrid nature of technology and economy, the analysis results clearly show that China’s car-hailing platform services present a multi-sided market structure when seen from the perspective of personal data resource allocation. Personal data resource (PDR), that is considered an essential market resource, is applied as an asset transferred unhindered between platforms via the application programming interface, and thus, creating a new market allocation mechanism. The connection between the car-hailing platforms and social media platforms is an essential aspect of the market competition in the domain. As applications of online platforms increase in the global context, this research offers a new perspective in personal data resource allocation with implications for the governance of the platform economy.

scholarly journals Energy-Efficient Resource Allocation for NOMA-based Backscatter Communications

2020 ◽  
Author(s):  
Yongjun Xu ◽  
Zhijin Qin ◽  
Guan Gui
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Power Efficiency ◽  
Multiple Access ◽  
Base Station ◽  
Spectrum Efficiency ◽  
Quadratic Transformation ◽  
Backscatter Communication ◽  
Efficient Resource ◽  
Energy Efficient Resource Allocation

Backscatter communication (BackCom) is a promising technique for achieving high spectrum efficiency and power efficiency in the future Internet of Things systems. The capacity of BackCom networks can be maximized by optimizing the backscatter time and the reflection coefficient (RC). However, system energy efficiency (EE) cannot be guaranteed usually. In this paper, we investigate the energy-efficient resource allocation problem of a non-orthogonal multiple access (NOMA)-based BackCom. Particularly, the base station (BS) transmits signals to two cellular users based on the NOMA protocol, meanwhile, a backscatter device backscatters the signals to users using the passive radio technology. The total EE of the considered system is maximized by jointly optimizing power allocation for each NOMA user and the RC of backscatter device where the decoding order and the quality of service (QoS) of each user are guaranteed. To solve such a non-convex problem, we develop an efficient iterative algorithm to obtain the optimal solutions by using Dinkelbach's method and the quadratic transformation approach. Numerical results show that the proposed algorithm can significantly improve the system EE compared with the orthogonal multiple access (OMA) scheme and the NOMA system without backscatter devices.

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