scholarly journals Increasing energy efficiency of Massive-MIMO network via base stations switching using reinforcement learning and radio environment maps

2021 ◽  
Vol 169 ◽  
pp. 232-242
Author(s):  
Marcin Hoffmann ◽  
Paweł Kryszkiewicz ◽  
Adrian Kliks
2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Paweł Kryszkiewicz ◽  
Adrian Kliks ◽  
Łukasz Kułacz ◽  
Hanna Bogucka ◽  
George P. Koudouridis ◽  
...  

Dynamic spectrum sharing can provide many benefits to wireless networks operators. However, its efficiency requires sophisticated control mechanisms. The more context information is used by it, the higher performance of networks is expected. A facility for collecting this information, processing it, and controlling base stations managed by various network operators is a so-called Radio Environment Map (REM) subsystem. This paper proposes REM-based schemes for the allocation of base stations power levels in 4G/5G networks, while considering interference generated to a licensed network. It is assumed that both networks have different profiles of served users, e.g., area of their positions and movement, which opens opportunities for spectrum sharing. The proposed schemes have been evaluated by means of extensive system-level simulations and compared with two widely adopted policy-based spectrum sharing reference schemes. Simulation results show that dynamic schemes utilizing rich context information outperforms static, policy-based spectrum sharing schemes.


Author(s):  
Arvind Kakria ◽  
Trilok Chand Aseri

Background & Objective: Wireless communication has immensely grown during the past few decades due to significant demand for mobile access. Although cost-effective as compared to their wired counterpart, maintaining good quality-of-service (QoS) in these networks has always remained a challenge. Multiple-input Multiple-output (MIMO) systems, which consists of multiple transmitter and receiver antennas, have been widely acknowledged for their QoS and transmit diversity. Though suited for cellular base stations, MIMO systems are not suited for small-sized wireless nodes due to their hardware complexity, cost, and increased power requirements. Cooperative communication that allows relays, i.e. mobile or fixed nodes in a communication network, to share their resources and forward other node’s data to the destination node has substituted the MIMO systems nowadays. To harness the full benefit of cooperative communication, appropriate relay node selection is very important. This paper presents an efficient single-hop distributed relay supporting medium access control (MAC) protocol (EDSRS) that works in the single-hop environment and improves the energy efficiency and the life of relay nodes without compensating the throughput of the network. Methods: The protocol has been simulated using NS2 simulator. The proposed protocol is compared with energy efficient cooperative MAC protocol (EECOMAC) and legacy distributed coordination function (DCF) on the basis of throughput, energy efficiency, transmission delay and an end to end delay with various payload sizes. Result and Conclusion: The result of the comparison indicates that the proposed protocol (EDSRS) outperforms the other two protocols.


2021 ◽  
Vol 11 (7) ◽  
pp. 2910
Author(s):  
Paweł Kaniewski ◽  
Janusz Romanik ◽  
Edward Golan ◽  
Krzysztof Zubel

In this paper, we present the concept of the Radio Environment Map (REM) designed to ensure electromagnetic situational awareness of cognitive radio networks. The map construction techniques based on spatial statistics are presented. The results of field tests done for Ultra High Frequency (UHF) range with different numbers of sensors are shown. Exemplary maps with selected interpolation techniques are presented. Control points where the signal from licensed users is correctly estimated are identified. Finally, the map quality is assessed, and the most promising interpolation techniques are selected.


Author(s):  
A. Papazafeiropoulos ◽  
H. Q. Ngo ◽  
P. Kourtessis ◽  
S. Chatzinotas ◽  
J. M. Senior

Author(s):  
Aya Mostafa Ahmed ◽  
Alaa Alameer Ahmad ◽  
Stefano Fortunati ◽  
Aydin Sezgin ◽  
Maria S. Greco ◽  
...  

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