System Capacity Analysis for Ultra-Dense Multi-Tier Future Cellular Networks

Shah, Syed Waqas Haider; Mian, Adnan Noor; Mumtaz, Shahid; Crowcroft, Jon

doi:10.1109/access.2019.2911409

Cited by 21 publications

(20 citation statements)

References 24 publications

(26 reference statements)

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“…That is, UEs are associated with their nearest RUs, and unused RUs do not need to emit radio waves. The received power of the desired signal can be enlarged whereas that of interference is reduced [25], [26]. Resultant SINR can be raised and thus overall system throughput is improved.…”

Section: B Simulation Resultsmentioning

confidence: 99%

Small Cells Enabled by Crowdsourced Radio Units Mounted on Parked Vehicles for Smart City

et al. 2020

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A large number of small cells are densely deployed in the era of 5G and beyond 5G mobile networks to achieve high rate and low latency data transmission. Small cells are composed with fixed ground radio units (RUs) in the conventional networks, and thus the utilization rate of them is drastically deteriorated due to the spatio-temporal patterns of mobile traffic demand. To address this problem, adaptive network architectures have been investigated to reconfigure networks on demand using small cells mounted on moving objects such as vehicles and drones. However, it has been difficult to establish stable communication link to ground nodes in high-speed environments with these schemes. Therefore, this paper proposes a concept of small cells composed with crowdsourced RUs mounted on parked vehicles. They are activated based on the traffic demand in surrounding area by road side units (RSUs) assuming a smart city. The proposed idea is based on the correlation between the distribution of people and the occupancy rate of parking lots. It can efficiently improve user throughput with relatively small number of RUs. The feasibility of the proposed scheme is validated through numerical analysis, computer simulations, and experimental results.

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Section: B Simulation Resultsmentioning

confidence: 99%

Small Cells Enabled by Crowdsourced Radio Units Mounted on Parked Vehicles for Smart City

et al. 2020

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“…For the pheromone update, we create several sets of solutions according to the number of objectives. The first objective in the resource allocation process is maximizing the users' transmission capacities as:

\max C_{k, n}^{K} = w {l o g}_{2} false(1 + γ_{k, n} false) \forall n \in N,

where w is the bandwidth of the n th RB and γ k , n is the SINR of the k th user on the n th RB. γ k , n is calculated as

γ_{k, n} = \frac{P_{k, n} H_{k, n}}{N_{0} + \sum_{k^{'} \in normalK false/ k} P_{k^{'}, n} H_{k^{'}, n}},

where P k , n is the transmission power of the k th user on the n th RB and H k , n is the channel gain of the k th user on the n th RB.…”

Section: System Model and Algorithm Descriptionmentioning

confidence: 99%

Multiobjective optimization‐based radio resource allocation and sharing algorithm for D2D‐based V2V communication

Feki

Belghith

Zarai

2019

Trans Emerging Tel Tech

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Vehicular communication systems have recently attracted a lot of attention because of their potential to improve road efficiency, comfort, and safety. In this paper, we investigate the resource management problem for device‐to‐device–based vehicle‐to‐vehicle communication. A multiobjective radio resource allocation and sharing algorithm is proposed based on a swarm intelligence algorithm called ant colony optimization (ACO). First, for the resource allocation process, three objective functions are formulated to maximize the users' transmission capacity, reduce the mobile transmission power, and minimize the intracell interference. Second, for the resource sharing process, we define two objective functions to optimize the resource utilization and reduce the intercell interference. Finally, a weighted sum method is used to join these objective functions and define one multiobjective optimization problem. The ACO algorithm is used to determine the Pareto optimal solution. Simulation results show that the proposed algorithm performs well and achieves promising performance in terms of network sum rate, packet drop rate, average queuing delay, resource utilization, and mobile's transmission power.

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“…To alleviate the spectrum scarcity problem in cellular networks, network densification by deploying small cells is considered as one of the most feasible solutions [8]. However, achieving capacity growth through network densification will ultimately experience severe inter-cell interference.…”

Section: Introductionmentioning

confidence: 99%

Statistical Qos Guarantees for Licensed-Unlicensed Spectrum Interoperable D2D Communication

2020

Self Cite

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In this paper, we propose network-assisted device-to-device (D2D) communication in licensed and unlicensed spectrum interoperable networks, to improve D2D users' throughput while alleviating the spectrum scarcity issue of cellular networks. The idea of licensed and unlicensed spectrum interoperability is based on the findings of the IEEE 1932.1 working group. Conventionally, D2D users were only able to communicate by using either cellular or non-cellular networks and no interoperability mechanism was available. The proposed scheme brings in many benefits including but not limited to higher D2D users' throughput, alleviation in spectrum scarcity issue of cellular networks, and better network management. However, ensuring quality-of-service (QoS) in this dynamic environment is a challenging task. To this end, we analyze the QoS using a well-known analytical tool "Effective Capacity (EC)" for eNodeB-assisted as well as WiFi-assisted D2D communication. Moreover, we also see the impact of neighboring cells' load and full-duplex transceiver at eNodeB and WiFi access point on the EC of D2D users. Simulation results show that EC increases with a decrease in neighboring cell's load and decreases when more stringent QoS constraints are imposed. Results also show that the maximum sustainable source rate at the transmitter's queue increases with an increase in maximum allowed packet delay but converges to a maximum value soon after that. INDEX TERMS Licensed-unlicensed spectrum interoperatability, D2D communication, effective capacity, quality-of-service.

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System Capacity Analysis for Ultra-Dense Multi-Tier Future Cellular Networks

Cited by 21 publications

References 24 publications

Small Cells Enabled by Crowdsourced Radio Units Mounted on Parked Vehicles for Smart City

Small Cells Enabled by Crowdsourced Radio Units Mounted on Parked Vehicles for Smart City

Multiobjective optimization‐based radio resource allocation and sharing algorithm for D2D‐based V2V communication

Statistical Qos Guarantees for Licensed-Unlicensed Spectrum Interoperable D2D Communication

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