scholarly journals Congestion Probabilities in a Multi-Cluster C-RAN Servicing a Mixture of Traffic Sources

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2120
Author(s):  
Iskanter-Alexandros Chousainov ◽  
Ioannis Moscholios ◽  
Panagiotis Sarigiannidis
Keyword(s):  
Access Network ◽  
Compound Poisson Process ◽  
Form Solution ◽  
Arrival Process ◽  
Computational Resource ◽  
Cloud Radio Access Network ◽  
Resource Unit ◽  
Radio Access ◽  
The Common ◽  
Steady State Probabilities

A multi-cluster cloud radio access network (C-RAN) is considered in this paper where the remote radio heads (RRHs) form different clusters. A cluster includes RRHs that have the same radio resource unit capacity. In addition, all RRHs are separated from the common pool of computational resource units named baseband units. Each RRH accommodates calls whose arrival process can be random, quasi-random, or even bursty. The latter is modeled according to the compound Poisson process where calls arrive in the C-RAN in the form of batches whose size (in calls) is generally distributed. An arriving call requires a radio and a computational resource unit so as to be accepted in the C-RAN. If at least one of these units is not available, the call is blocked. To analyze the proposed multi-cluster C-RAN we model it as a loss system, show that the steady-state probabilities have a product form solution and propose an algorithm for the computation of congestion probabilities. The accuracy of the proposed algorithm is verified via simulation.

scholarly journals Performance Evaluation in Single or Multi-Cluster C-RAN Supporting Quasi-Random Traffic

2020 ◽  
Vol 16 (2) ◽  
pp. 170-179 ◽  
Author(s):  
Iskanter-Alexandros Chousainov ◽  
Ioannis Moscholios ◽  
Alexandros Kaloxylos ◽  
Michael Logothetis
Keyword(s):  
Accurate Determination ◽  
Access Network ◽  
Form Solution ◽  
Arrival Process ◽  
Computational Resource ◽  
Cloud Radio Access Network ◽  
Radio Access ◽  
Proposed Model ◽  
Convolution Algorithm ◽  
Rate Loss

In this paper, a cloud radio access network (C-RAN) is considered where the remote radio heads (RRHs) are separated from the baseband units (BBUs). The RRHs in the C-RAN are grouped in different clusters according to their capacity while the BBUs form a centralized pool of computational resource units. Each RRH services a finite number of mobile users, i.e., the call arrival process is the quasi-random process. A new call of a single service-class requires a radio and a computational resource unit in order to be accepted in the C-RAN for a generally distributed service time. If these resource units are unavailable, then the call is blocked and lost. To analyze the multi-cluster C-RAN, we model it as a single-rate loss system, show that a product form solution exists for the steady state probabilities and propose a convolution algorithm for the accurate determination of congestion probabilities. The accuracy of this algorithm is verified via simulation. The proposed model generalizes our recent model where the RRHs in the C-RAN are grouped in a single cluster and each RRH accommodates quasi-random traffic.

scholarly journals Multiservice Loss Models in Single or Multi-Cluster C-RAN Supporting Quasi-Random Traffic

2021 ◽  
Vol 11 (18) ◽  
pp. 8559
Author(s):  
Iskanter-Alexandros Chousainov ◽  
Ioannis Moscholios ◽  
Panagiotis Sarigiannidis ◽  
Michael Logothetis
Keyword(s):  
Access Network ◽  
Form Solution ◽  
Complex Case ◽  
Computational Resource ◽  
Call Blocking ◽  
Cloud Radio Access Network ◽  
Radio Access ◽  
Convolution Algorithm ◽  
Resource Requirements ◽  
Single Cluster

In this paper, a cloud radio access network (C-RAN) is considered where the baseband units form a pool of computational resource units and are separated from the remote radio heads (RRHs). Based on their radio capacity, the RRHs may form one or many clusters: a single cluster when all RRHs have the same capacity and multi-clusters where RRHs of the same radio capacity are grouped in the same cluster. Each RRH services the so-called multiservice traffic, i.e., calls from many service classes with various radio and computational resource requirements. Calls arrive in the RRHs according to a quasi-random process. This means that new calls are generated by a finite number of mobile users. Arriving calls require simultaneously computational and radio resource units in order to be accepted in the system, i.e., in the serving RRH. If their requirements are met, then these calls are served in the (serving) RRH for a service time which is generally distributed. Otherwise, call blocking occurs. We start with the single-cluster C-RAN and model it as a multiservice loss system, prove that the model has a product form solution, and determine time congestion probabilities via a convolution algorithm whose accuracy is validated with the aid of simulation. Furthermore, the previous model is generalized to include the more complex case of more than one clusters.

scholarly journals Energy-Effective Power Control Algorithm with Mobility Prediction for 5G Heterogeneous Cloud Radio Access Network

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2904 ◽  
Author(s):  
Hyebin Park ◽  
Yujin Lim
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Control Algorithm ◽  
Access Network ◽  
Mobility Prediction ◽  
Switching Operation ◽  
Cloud Radio Access Network ◽  
Radio Access ◽  
Power Control Algorithm ◽  
Heterogeneous Cloud

In 5G networks, heterogeneous cloud radio access network (H-CRAN) is considered a promising future architecture to minimize energy consumption and efficiently allocate resources. However, with the increase in the number of users, studies are performed to overcome the energy consumption problems. In this study, we propose a power control algorithm with mobility prediction to provide a high-energy efficiency for 5G H-CRAN. In particular, the proposed algorithm predicts UE mobility in vehicular mobility scenarios and performs remote radio head (RRH) switching operations based on % prediction results. We formulate an optimization problem to maximize the energy efficiency while satisfying the outage probability requirement. We then propose an RRH switching operation based on Markov mobility prediction and optimize the transmission power based on a gradient method. Simulation results demonstrate the improved energy efficiency compared with those of existing RRH switching-operation algorithms.

Robust Multigroup Multicast Beamforming Design for Backhaul-Limited Cloud Radio Access Network

2019 ◽  
Vol 26 (1) ◽  
pp. 189-193 ◽  
Author(s):  
Yiyun Chen ◽  
Shiwen He ◽  
Yongming Huang ◽  
Ju Ren ◽  
Luxi Yang
Keyword(s):  
Access Network ◽  
Radio Access Network ◽  
Cloud Radio Access Network ◽  
Radio Access ◽  
Multicast Beamforming
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