scholarly journals User-Number Threshold-based Base Station On/Off Control for Maximizing Coverage Probability

2022 ◽  
pp. 1-1
Author(s):  
Junghoon Noh ◽  
Byungju Lee ◽  
Seong-JUN Oh
Keyword(s):  
Coverage Probability ◽  
Base Station

scholarly journals An Optimum User Association Algorithm in Heterogeneous 5G Networks Using Standard Deviation of the Load

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1495
Author(s):  
Noha Hassan ◽  
Xavier Fernando
Keyword(s):  
Energy Efficiency ◽  
Standard Deviation ◽  
High Power ◽  
Coverage Probability ◽  
Base Station ◽  
Base Stations ◽  
Superior Performance ◽  
User Association ◽  
Optimum Number ◽  
Network Load

Fifth-generation (5G) wireless networks and beyond will be heterogeneous in nature, with a mixture of macro and micro radio cells. In this scenario where high power macro base stations (MBS) coexist with low power micro base stations (mBS), it is challenging to ensure optimal usage of radio resources to serve users with a multitude of quality of service (QoS) requirements. Typical signal to interference and noise ratio (SINR)-based user allocation protocols unfairly assign more users to the high power MBS, starving mBS. There have been many attempts in the literature to forcefully assign users to mBS with limited success. In this paper, we take a different approach using second order statistics of user data, which is a better indicator of traffic fluctuations. We propose a new algorithm for user association to the appropriate base station (BS) by utilizing the standard deviation of the overall network load. This is done through an exhaustive search of the best user equipment (UE)–BS combinations that provide a global minimum to the standard deviation. This would correspond to the optimum number of UEs assigned to every BS, either macro or micro. We have also derived new expressions for coverage probability and network energy efficiency for analytical performance evaluation. Simulation results prove the validity of our proposed methods to balance the network load, improve data rate, average energy efficiency, and coverage probability with superior performance compared with other algorithms.

scholarly journals Cellular coverage probability is independent of base station density under stochastic geometric models

2021 ◽  
Author(s):  
Hamed Nassar ◽  
Gehad Taher ◽  
El-Sayed El-Hady
Keyword(s):  
Cellular Networks ◽  
Coverage Probability ◽  
Base Station ◽  
Base Stations ◽  
Geometric Modelling ◽  
Geometric Models ◽  
Widespread Belief ◽  
Station Density

We prove that under stochastic geometric modelling of cellular networks, the coverage probability is <i>not</i> a function of base stations density, contrary to widespread belief. That is, we reveal that the base station density, $\lambda$, that is appears in a plethora of published cellular coverage probability expressions is superfluous.<br>

scholarly journals Cellular coverage probability is independent of base station density under stochastic geometric models

2021 ◽  
Author(s):  
Hamed Nassar ◽  
Gehad Taher ◽  
El-Sayed El-Hady
Keyword(s):  
Cellular Networks ◽  
Coverage Probability ◽  
Base Station ◽  
Base Stations ◽  
Geometric Modelling ◽  
Geometric Models ◽  
Widespread Belief ◽  
Station Density

We prove that under stochastic geometric modelling of cellular networks, the coverage probability is <i>not</i> a function of base stations density, contrary to widespread belief. That is, we reveal that the base station density, $\lambda$, that is appears in a plethora of published cellular coverage probability expressions is superfluous.<br>

scholarly journals Performance Analysis of Backhaul-Aware User Association in 5G Ultradense Heterogeneous Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Junpeng Yu ◽  
Hongtao Zhang ◽  
Yuqing Chen ◽  
Yaduan Ruan
Keyword(s):  
Heterogeneous Networks ◽  
Association Scheme ◽  
Coverage Probability ◽  
Network Performance ◽  
Performance Metrics ◽  
Density Ratio ◽  
Base Station ◽  
Base Stations ◽  
User Association ◽  
The Impact

In 5G ultradense heterogeneous networks, wireless backhaul, as one of the important base station (BS) resources that affect user services, has attracted more and more attention. However, a user would access to the BS which is the nearest for the user based on the conventional user association scheme, which constrains the network performance improvement due to the limited backhaul capacity. In this paper, using backhaul-aware user association scheme, semiclosed expressions of network performance metrics are derived in ultradense heterogeneous networks, including coverage probability, rate coverage, and network delay. Specifically, all possible access and backhaul links within the user connectable range of BSs and anchor base stations (A-BSs) are considered to minimize the analytical results of outage probability. The outage for the user occurs only when the access link or backhaul link which forms the link combination with the optimal performance is failure. Furthermore, the theoretical analysis and numerical results evaluate the impact of the fraction of A-BSs and the BS-to-user density ratio on network performance metric to seek for a more reasonable deployment of BSs in the practical scenario. The simulation results show that the coverage probability of backhaul-aware user association scheme is improved significantly by about 2× compared to that of the conventional user association scheme when backhaul is constrained.

Optimal Base Station Deployment with Downlink Rate Coverage Probability Constraint

2018 ◽  
Vol 7 (3) ◽  
pp. 340-343 ◽  
Author(s):  
Shubhajeet Chatterjee ◽  
Mohammad J. Abdel-Rahman ◽  
Allen B. MacKenzie
Keyword(s):  
Coverage Probability ◽  
Base Station ◽  
Probability Constraint

scholarly journals Optimizing Macro and Micro Base Stations Locations and User Associations in Heterogeneous Wireless Networks

2021 ◽  
Author(s):  
Noha Hassan
Keyword(s):  
Real Time ◽  
Coverage Probability ◽  
Communication Systems ◽  
Dimensional Space ◽  
Heterogeneous Wireless Networks ◽  
Base Station ◽  
Base Stations ◽  
Sequence Length ◽  
User Association ◽  
Signal Power

Heterogeneous Networks (HetNets) have gained the attraction of the communication industry recently, due to their promising ability to enhance the performance of future broadband Fifth Generation (5G) networks and are integral parts of 5G systems. They can be viewed in multi-dimensional space where, each slice represents a unique tier that has its own Base Station (BS)s and User Equipment (UE)s. Different tiers cooperate with each other for their mutual benefit. Data can be interactively exchanged among the tiers, and UEs have the flexibility to switch between the tiers. The cells in such a heterogeneous cellular networks have variable sizes, shapes, and coverage regions. However, in HetNets with ultra dense BSs, the distance between them gets very small and, they suffer from very high levels of mutual interference. To improve the performance of HetNets, we have done multiple contributions in this dissertation. First, we have developed analytical derivations for optimizing pilot sequence length which is a very crucial factor in acquiring the Channel State Information (CSI) and the channel estimation process in general. Poisson Point Process (PPP) has been widely used to allocate BSs among various tiers so far. However, BS locations obtained using PPP approach may not be optimum to reduce interference. Therefore, in this dissertation, BSs locations are optimized to reduce the interference and improve the coverage and received signal power. Also, we have derived expressions for static UEs coverage probability and network energy efficiency in HetNets. A proper UE association algorithm for HetNets is a great challenge. The classic max-Signal to Interference and Noise Ratio (SINR) or max-received signal strength (RSS) user association algorithms are inappropriate solutions for HetNets as UEs in this context will tend to connect to the Macro BS, which is the one with the highest signal power. A severe load imbalance and significant inefficiency arises and impacts the performance. The aforementioned algorithms tend to associate UEs to BSs with the best received signal power or signal quality. In HetNets, usually Macro BSs are the ones transmitting the strongest signals; hence most UEs tend to associate with the Macro BS leaving Micro BSs with less load. Also, the conventional max-SINR and max-RSS algorithms do not provide adequate results in multi-tier systems. We suggest two centralized algorithms, LSTD and RTLB, for an even UE association to provide fair load distribution. However RTLB outperforms LSTD in real time scenarios as it easily and quickly adapts to rapid network changes. Furthermore, we consider the mobility of nodes. We derive coverage probability for moving UEs considering both handover and no handover scenarios. Proposed algorithms are fast enough to associate the moving users to different Micro and Macro BSs appropriately in real time. Our algorithms are proved to be feasible and provide a path towards attainable future communication systems.

scholarly journals Optimizing Macro and Micro Base Stations Locations and User Associations in Heterogeneous Wireless Networks

2021 ◽  
Author(s):  
Noha Hassan
Keyword(s):  
Real Time ◽  
Coverage Probability ◽  
Communication Systems ◽  
Dimensional Space ◽  
Heterogeneous Wireless Networks ◽  
Base Station ◽  
Base Stations ◽  
Sequence Length ◽  
User Association ◽  
Signal Power

Heterogeneous Networks (HetNets) have gained the attraction of the communication industry recently, due to their promising ability to enhance the performance of future broadband Fifth Generation (5G) networks and are integral parts of 5G systems. They can be viewed in multi-dimensional space where, each slice represents a unique tier that has its own Base Station (BS)s and User Equipment (UE)s. Different tiers cooperate with each other for their mutual benefit. Data can be interactively exchanged among the tiers, and UEs have the flexibility to switch between the tiers. The cells in such a heterogeneous cellular networks have variable sizes, shapes, and coverage regions. However, in HetNets with ultra dense BSs, the distance between them gets very small and, they suffer from very high levels of mutual interference. To improve the performance of HetNets, we have done multiple contributions in this dissertation. First, we have developed analytical derivations for optimizing pilot sequence length which is a very crucial factor in acquiring the Channel State Information (CSI) and the channel estimation process in general. Poisson Point Process (PPP) has been widely used to allocate BSs among various tiers so far. However, BS locations obtained using PPP approach may not be optimum to reduce interference. Therefore, in this dissertation, BSs locations are optimized to reduce the interference and improve the coverage and received signal power. Also, we have derived expressions for static UEs coverage probability and network energy efficiency in HetNets. A proper UE association algorithm for HetNets is a great challenge. The classic max-Signal to Interference and Noise Ratio (SINR) or max-received signal strength (RSS) user association algorithms are inappropriate solutions for HetNets as UEs in this context will tend to connect to the Macro BS, which is the one with the highest signal power. A severe load imbalance and significant inefficiency arises and impacts the performance. The aforementioned algorithms tend to associate UEs to BSs with the best received signal power or signal quality. In HetNets, usually Macro BSs are the ones transmitting the strongest signals; hence most UEs tend to associate with the Macro BS leaving Micro BSs with less load. Also, the conventional max-SINR and max-RSS algorithms do not provide adequate results in multi-tier systems. We suggest two centralized algorithms, LSTD and RTLB, for an even UE association to provide fair load distribution. However RTLB outperforms LSTD in real time scenarios as it easily and quickly adapts to rapid network changes. Furthermore, we consider the mobility of nodes. We derive coverage probability for moving UEs considering both handover and no handover scenarios. Proposed algorithms are fast enough to associate the moving users to different Micro and Macro BSs appropriately in real time. Our algorithms are proved to be feasible and provide a path towards attainable future communication systems.

scholarly journals Cellular coverage probability is independent of base station density under stochastic geometric models

2021 ◽  
Author(s):  
Hamed Nassar
Keyword(s):  
Coverage Probability ◽  
Stochastic Geometry ◽  
Poisson Point Process ◽  
Euclidean Plane ◽  
Base Station ◽  
Base Stations ◽  
Cellular Communications ◽  
Huge Number ◽  
The Past ◽  
Station Density

Stochastic geometry (SG) has been extensively used to model cellular communications, under the assumption that the base stations (BS) are deployed as a Poisson point process in the Euclidean plane. This has spawned a huge number of articles over the past years for different scenarios, culminating in an equally huge number of expressions for the coverage probability in both the uplink (UL) and downink (DL) directions. The trouble is that those expressions include the BS density, $\lambda$, which we prove irrelevant in this article. We start by developing a SG model for a baseline cellular scenario, then prove that the coverage probability is independent of $\lambda$, contrary to popular belief.

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