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 User Association and Small-Cell Base Station On/Off Strategies for Energy Efficiency of Ultradense Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Jing Gao ◽  
Qing Ren ◽  
Pei Shang Gu ◽  
Xin Song
Keyword(s):  
Energy Efficiency ◽  
Optimization Method ◽  
Base Station ◽  
Small Cell ◽  
Base Stations ◽  
User Association ◽  
User Mobility ◽  
Efficient Design ◽  
Widespread Application ◽  
Cell Base

The widespread application of wireless mobile services and requirements of ubiquitous access have resulted in drastic growth of the mobile traffic and huge energy consumption in ultradense networks (UDNs). Therefore, energy-efficient design is very important and is becoming an inevitable trend. To improve the energy efficiency (EE) of UDNs, we present a joint optimization method considering user association and small-cell base station (SBS) on/off strategies in UDNs. The problem is formulated as a nonconvex nonlinear programming problem and is then decomposed into two subproblems: user association and SBS on/off strategies. In the user association strategy, users associate with base stations (BSs) according to their movement speeds and utility function values, under the constraints of the signal-to-interference ratio (SINR) and load balancing. In particular, taking care of user mobility, users are associated if their speed exceeds a certain threshold. The macrocell base station (MBS) considers user mobility, which prevents frequent switching between users and SBSs. In the SBS on/off strategy, SBSs are turned off according to their loads and the amount of time required for mobile users to arrive at a given SBS to further improve network energy efficiency. By turning off SBSs, negative impacts on user associations can be reduced. The simulation results show that relative to conventional algorithms, the proposed scheme achieves energy efficiency performance enhancements.

scholarly journals An Optimal Energy Efficiency of a Two-tier Network in Control-Data Separation Architecture

2020 ◽  
pp. 545-550
Author(s):  
Zaid Mujaiyid Putra Bin Ahmad Baidowi ◽  
◽  
Xiaoli Chu
Keyword(s):  
Energy Efficiency ◽  
Point Processes ◽  
Threshold Value ◽  
Base Station ◽  
Base Stations ◽  
Mobile Users ◽  
Maximization Problem ◽  
User Association ◽  
Data Separation ◽  
Cell Base

In this paper, we propose to maximize the Energy Efficiency (EE) of a two-tier network by jointly optimizing the number of active small cell base stations (SBSs) and the user-cell association. We apply the concept of signaling and data separation where a macro cell base station (MBS) provides full coverage while the SBSs provide high data transmission. First, we model the spatial distributions of the SBSs and mobile users following two independent Poisson Point Processes (PPP) and derive the expressions for the Signal-to-Interference Ratio (SIR), user cell associations, power consumption and energy efficiency of the Heterogeneous Network (HetNet). Then, we formulate the EE maximization problem and solve it by proposing the Switching off Decision and User Association (SODUA) algorithm. The algorithm associates a mobile user to an SBS that offers the highest SIR and calculates the load of each SBS. The algorithm, then, decides to switch off the SBSs that have fewer mobile users than a threshold value, where the mobile users will be offloaded to a nearby SBS that offers the highest SIR. Finally, we calculate the EE of the HetNet. We compare the EE achieved by the proposed algorithm (i.e. after offloading) and that "without offloading". The results show that the proposed algorithm improves the EE of the HetNet and that the EE cannot be further improved by switching off more SBSs than a certain number.

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.

scholarly journals EE-eICIC: Energy-Efficient Optimization of Joint User Association and ABS for eICIC in Heterogeneous Cellular Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Jie Zheng ◽  
Ling Gao ◽  
Hai Wang ◽  
Jinping Niu ◽  
Xiaoya Li ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Low Power ◽  
Cellular Networks ◽  
Interference Management ◽  
Algorithm Design ◽  
Base Stations ◽  
Superior Performance ◽  
User Association ◽  
Heterogeneous Cellular Networks ◽  
Generalized Fractional Programming

The densification and expansion of heterogeneous cellular networks (HetNets) pose new challenges on interference management and reduction of energy consumption. The 3GPP has proposed enhanced intercell interference coordination (eICIC) by making a macrocell silent in almost blank subframes (ABSs) to mitigate interference for low power base stations (BSs) in HetNets. However, energy efficiency (EE) is very crucial for the deployment of a large number of low power nodes as they consume a lot of energy. In this work, we develop a novel EE-eICIC algorithm to determine the amount of ABSs and user equipment (UE) that should associate with picocells or macrocells from energy efficiency perspective. Due to the nonsmooth and mixed combinatorial features of this formulation, we focus on a suboptimal algorithm design. Using generalized fractional programming and the convex programming theory, we propose an iterative and relaxed-rounding algorithm to solve the problem. Numerical results illustrate that the proposed EE-eICIC algorithm achieves superior performance in comparison with state-of-the-art methods in terms of energy efficiency of both system and user.

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 Energy Efficiency Maximization of Dynamic CoMP-JT Algorithm in Dense Small Cell Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
Xuefei Peng ◽  
Jiandong Li ◽  
Yifei Xu
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Optimal Solution ◽  
Small Cell ◽  
Base Stations ◽  
Maximization Problem ◽  
Second Phase ◽  
User Association ◽  
Coordinated Multipoint ◽  
Convex Problem

We firstly formulate the energy efficiency (EE) maximization problem of joint user association and power allocation considering minimum data rate requirement of small cell users (SUEs) and maximum transmit power constraint of small cell base stations (SBSs), which is NP-hard. Then, we propose a dynamic coordinated multipoint joint transmission (CoMP-JT) algorithm to improve EE. In the first phase, SUEs are associated with the SBSs close to them to reduce the loss of power by the proposed user association algorithm, where the associated SBSs of each small cell user (SUE) form a dynamic CoMP-JT set. In the second phase, through the methods of fractional programming and successive convex approximation, we transform the EE maximization subproblem of power allocation for SBSs into a convex problem that can be solved by proposed power allocation optimization algorithm. Moreover, we show that the proposed solution has a much lower computational complexity than that of the optimal solution obtained by exhaustive search. Simulation results demonstrate that the proposed solution has a better performance.

scholarly journals User Association and Power Control for Energy Efficiency Maximization in M2M-Enabled Uplink Heterogeneous Networks with NOMA

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5307 ◽  
Author(s):  
Shuang Zhang ◽  
Guixia Kang
Keyword(s):  
Energy Efficiency ◽  
Power Control ◽  
Heterogeneous Networks ◽  
Base Station ◽  
Sequential Optimization ◽  
User Association ◽  
Decode And Forward ◽  
Vast Number ◽  
Machine Type ◽  
Machine Type Communication

To support a vast number of devices with less energy consumption, we propose a new user association and power control scheme for machine to machine enabled heterogeneous networks with non-orthogonal multiple access (NOMA), where a mobile user (MU) acting as a machine-type communication gateway can decode and forward both the information of machine-type communication devices and its own data to the base station (BS) directly. MU association and power control are jointly considered in the formulated as optimization problem for energy efficiency (EE) maximization under the constraints of minimum data rate requirements of MUs. A many-to-one MU association matching algorithm is firstly proposed based on the theory of matching game. By taking swap matching operations among MUs, BSs, and sub-channels, the original problem can be solved by dealing with the EE maximization for each sub-channel. Then, two power control algorithms are proposed, where the tools of sequential optimization, fractional programming, and exhaustive search have been employed. Simulation results are provided to demonstrate the optimality properties of our algorithms under different parameter settings.

Development of a Hybrid Algorithm for User Association and Resource Allocation to Improve Load Balancing and Energy Efficiency in 5G HetNet

2020 ◽  
Vol 19 (1) ◽  
pp. 17-25
Author(s):  
Elvis Obi ◽  
Aliyu Danjuma Usman ◽  
Suleiman Muhammad Sani ◽  
Abdoulie Momodou Sunkary Tekanyi
Keyword(s):  
Resource Allocation ◽  
Energy Efficiency ◽  
Load Balancing ◽  
Bandwidth Allocation ◽  
Hybrid Algorithm ◽  
Control Algorithm ◽  
User Association ◽  
Network Load ◽  
Power Control Algorithm ◽  
Network Load Balancing

This paper presents the development and integration of a power control algorithm into the User Association Algorithm with Optimal Bandwidth Allocation (UAAOBA) to form a Hybrid Algorithm for User Association and Resource Allocation (HAUARA). The power control algorithm updates the transmit power of the Base Stations (BSs) towards a minimum transmit power that satisfies the minimum data rate requirement (1 Gbps) of the User Equipment UEs. The power update is achieved using the Newton Rhapson’s method and it adapts the transmit powers of the BSs to the number of their connected UEs. The developed HAUARA provides an optimal solution for user associations, bandwidth allocation, and transmit powers to UEs concurrently. This maximizes the network energy efficiency by coordinating the load fairness of the network while guaranteeing the quality of service requirement of the UEs. The network energy efficiency performance of the developed HAUARA is compared with that of the UAAOBA. The results show that the developed algorithm has network energy efficiency improvement of 12.36%, 10.58%, and 13.44% with respect to UAAOBA for increase number of macro BS antennas, pico BSs, and femto BSs, respectively. Also, the network load balancing performance of the developed HAUARA is compared with that of the UAAOBA. The results show that the developed algorithm has network load balancing improvement of 12.62%, 10.04%, and 10.34% with respect to UAAOBA for increase number of macro BS antennas, pico BSs, and femto BSs, respectively. This implies that the developed algorithm outperforms the UAAOBA in terms of network energy efficiency and load balancing.

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>

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