Concurrent Optimization of Coverage, Capacity, and Load Balance in HetNets Through Soft and Hard Cell Association Parameters

Asghar, Ahmad Bilal; Farooq, Hasan; Imran, Ali

doi:10.1109/tvt.2018.2846655

Cited by 34 publications

(33 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is intuitive that such massive deployments of nodes will create numerous problems, including uneven traffic load, unfair resource allocation, mobility management, backhaul congestion, etc. Among the aforementioned challenges, imbalanced load distribution between macro and small cells is a long‐standing problem in these HetNets, which results in inefficient utilization of systems' installed capacity and users' QoE degradation …”

Section: Introductionmentioning

confidence: 99%

“…Various load balancing (LB) solutions have been proposed (eg, see other works) to address the uneven load issue; however, they operate in reactive mode. Under the vast deployment of nodes such as HetNets, these reactive LB policies may become a bottleneck that hinders network to deliver contents seamlessly and leads to worse user experience.…”

Section: Introductionmentioning

confidence: 99%

“…The LB mechanism can be improved significantly through proactive traffic offloading by inferring the user entity (UE) behavior, along with network state information such as channel conditions, cell loads, etc. The imbalanced cell load problem in HetNets arises due to state‐of‐the‐art user‐cell association procedure, ie, maximum reference signal received power (Max‐RSRP) . Under this procedure, a UE selects the cell with the highest RSRP value.…”

Section: Introductionmentioning

confidence: 99%

“…In HetNets, MBS has higher transmission power than SBS; therefore, MBS attracts more UEs than SBS. Consequently, MBSs become congested, SBSs remain underutilized, and overall network faces severely uneven load distribution . In such a scenario, the congested cells also have to accommodate incoming traffic in addition to current UEs with the certain level of QoE provisioning.…”

Section: Introductionmentioning

confidence: 99%

“…The main goal of this scheme is to improve users' QoE in such a way that the offloaded UEs can get more physical resource blocks (PRB) from the new cell (if available) and remaining UEs at previously congested cells get relief from the congestion state and experience better downlink (DL) throughput. However, this reactive offloading mechanism activates CIOs after any or more cells become congested, without taking account of cell loads and users' QoE demand information, which might affect the signal‐to‐interference‐and‐noise ratio (SINR) of offloaded users adversely …”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Leveraging mobility and content caching for proactive load balancing in heterogeneous cellular networks

Manzoor

Mazhar

Asghar

et al. 2019

Trans Emerging Tel Tech

Self Cite

View full text Add to dashboard Cite

Evolution of cellular networks into dynamic, dense, and heterogeneous networks have introduced new challenges for cell resource optimization, especially in the imbalanced traffic load regions. Numerous load balancing schemes have been proposed to tackle this issue; however, they operate in a reactive manner that confines their ability to meet the top‐notch quality of experience demands. To address this challenge, we propose a novel proactive load balancing scheme. Our framework learns users' mobility and demands statistics jointly to proactively cache future contents during their stay at lightly loaded cells, which results in quality of experience maximization and load minimization. System level simulations are performed and compared with the state‐of‐the‐art reactive schemes.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Leveraging mobility and content caching for proactive load balancing in heterogeneous cellular networks

Manzoor

Mazhar

Asghar

et al. 2019

Trans Emerging Tel Tech

Self Cite

View full text Add to dashboard Cite

show abstract

An LSTM‐based cell association scheme for proactive bandwidth management in 5G fog radio access networks

Manzoor

Mian

Mazhar

2021

Int J Communication

View full text Add to dashboard Cite

Summary Cellular networks are evolving into dynamic, dense, and heterogeneous networks to meet the unprecedented traffic demands which introduced new challenges for cell resource management. To address this, various cell association schemes have been proposed. However, the current schemes ignore users' mobility information, and as a result, their cell admission and bandwidth allocation policy are reactive. In order to enable proactive bandwidth management in emerging 5G fog access radio networks (FRANs), we proposed a novel mobility‐aware cell association scheme (MACA) that exploits user's mobility and downlink rate demand information to associate it with the maximum rate offering cell. In MACA, the mobility prediction model consists of long‐short‐term memory (LSTM)‐based neural network that considers joint information of unique cell identification numbers with the corresponding sojourn times and predicts the user's most probable next cell. Later, the underlying future cell assignment is formulated as a convex problem and solved using the Lagrangian dual decomposition method and compared the proposed framework performance with Semi‐Markov, deep neural network (DNN), and MaxRSRP‐based cell association approaches in terms of the next cell prediction accuracy, the impact of downlink rate allocation, and user satisfaction percentage. MACA scheme is trained using two publicly available pedestrian datasets. Simulation results show that the proposed scheme performs significantly better than the other schemes and yields the average next cell prediction accuracy of 93.42%, 1.63 times higher downlink rates, and 56.8% users satisfied with the allocated bandwidth.

show abstract

A survey of mmWave user association mechanisms and spectrum sharing approaches: an overview, open issues and challenges, future research trends

et al. 2019

View full text Add to dashboard Cite

Concurrent Optimization of Coverage, Capacity, and Load Balance in HetNets Through Soft and Hard Cell Association Parameters

Cited by 34 publications

References 25 publications

Leveraging mobility and content caching for proactive load balancing in heterogeneous cellular networks

Leveraging mobility and content caching for proactive load balancing in heterogeneous cellular networks

An LSTM‐based cell association scheme for proactive bandwidth management in 5G fog radio access networks

A survey of mmWave user association mechanisms and spectrum sharing approaches: an overview, open issues and challenges, future research trends

Contact Info

Product

Resources

About