Enabling Soft Frequency Reuse and Stienen's Cell Partition in Two-Tier Heterogeneous Networks: Cell Deployment and Coverage Analysis
Heterogeneous cellular networks (HetNets) are one of the key enabling technologies for fifth generation (5 G) networks. In HetNets, the use of small base stations (SBSs) inside the coverage area of a macro base station (MBS) offers higher throughput and improved coverage. However, such multi-tier base station deployment introduces new challenges, e.g., (i) All users experience significant inter-cell interference (ICI) due to frequency reuse, (ii) SBS associated users experience severe MBS-interference due to higher MBS transmit power, and (iii) MBS coverage edge users receive lower signal-to-interference ratio (SIR) due to longer distances. To address the aforementioned challenges, this wor…
Outage Probability Analysis of User-Centric SBS-Based HCNets Under Hybrid Rician/Rayleigh Fading
To model dense user equipment (UE) distribution in heterogeneous cellular networks (HCNets), the Poisson cluster process (PCP) has emerged as a promising tool. In user-centric HCNets where UEs are distributed according to a PCP around a small base station (SBS), the network performance has been commonly studied in literature under a Rayleigh fading environment assumption. However, such an assumption may not hold in user-centric HCNets given the possible existence of a strong line-of-sight (LOS) link between UEs and BSs due to a relatively short transmission distance. This letter analyzes the performance of user-centric SBS based HCNets by considering that the desired LOS link experiences Ri…
Decoupled Downlink-Uplink Coverage Analysis with Interference Management for Enriched Heterogeneous Cellular Networks
Heterogeneous cellular networks (HetCNets) offer a promising solution to cope with the current cellular coverage crunch. Due to the large transmit power disparity, while following maximum power received (MPR) association scheme, a larger number of users are associated with macro-cell BS (MBS) than small-cell BSs (SBSs). Therefore, an imbalance load arrangement takes place across the HetCNets. Hence, using cell range expansion-based cell association, we can balance the load across the congested MBS. However, using MPR association scheme, users’ offloading leads to two challenges: 1) macro-cell interference , in which the MBS interferes with the offloaded users, and 2) coupled downlink-uplink…
A novel faster failure detection strategy for link connectivity using Hello messaging in mobile ad hoc networks
Faster failure detection is one of the main steps responsible for efficient link connectivity in mobile ad hoc networks (MANETs). Under a random behaviour of network nodes and link/node failure, th...
A Comprehensive Utility Function for Resource Allocation in Mobile Edge Computing
In mobile edge computing (MEC), one of the important challenges is how much resources of which mobile edge server (MES) should be allocated to which user equipment (UE). The existing resource allocation schemes only consider CPU as the requested resource and assume utility for MESs as either a random variable or dependent on the requested CPU only. This paper presents a novel comprehensive utility function for resource allocation in MEC. The utility function considers the heterogeneous nature of applications that a UE offloads to MES. The proposed utility function considers all important parameters, including CPU, RAM, hard disk space, required time, and distance, to calculate a more realis…
A Deep Learning Approach for Energy Efficient Computational Offloading in Mobile Edge Computing
Mobile edge computing (MEC) has shown tremendous potential as a means for computationally intensive mobile applications by partially or entirely offloading computations to a nearby server to minimize the energy consumption of user equipment (UE). However, the task of selecting an optimal set of components to offload considering the amount of data transfer as well as the latency in communication is a complex problem. In this paper, we propose a novel energy-efficient deep learning based offloading scheme (EEDOS) to train a deep learning based smart decision-making algorithm that selects an optimal set of application components based on remaining energy of UEs, energy consumption by applicati…
Performance analysis of user-centric SBS deployment with load balancing in heterogeneous cellular networks: A Thomas cluster process approach
Abstract In conventional heterogeneous cellular networks (HCNets), the locations of user equipments (UEs) and base stations (BSs) are modeled randomly using two different homogeneous Poisson point processes (PPPs). However, this might not be a suitable assumption in case of UE distribution because UE density is not uniform everywhere in HCNets. Keeping in view the existence of nonuniform UEs, the small base stations (SBSs) are assumed to be deployed in the areas with high UE density, which results in correlation between UEs and BS locations. In this paper, we analyse the performance of HCNets with nonuniform UE deployment containing a union of clustered and uniform UE sets. The clustered UE…
Computational Offloading in Mobile Edge with Comprehensive and Energy Efficient Cost Function: A Deep Learning Approach
In mobile edge computing (MEC), partial computational offloading can be intelligently investigated to reduce the energy consumption and service delay of user equipment (UE) by dividing a single task into different components. Some of the components execute locally on the UE while the remaining are offloaded to a mobile edge server (MES). In this paper, we investigate the partial offloading technique in MEC using a supervised deep learning approach. The proposed technique, comprehensive and energy efficient deep learning-based offloading technique (CEDOT), intelligently selects the partial offloading policy and also the size of each component of a task to reduce the service delay and energy …
Capacity driven small cell deployment in heterogeneous cellular networks : Outage probability and rate coverage analysis
Author's accepted manuscript. This is the peer reviewed version of the following article: Ullah, A., Haq Abbas, Z., Muhammad, F., Abbas, G. & Lei, J. (2020). Capacity driven small cell deployment in heterogeneous cellular networks: Outage probability and rate coverage analysis. Transactions on Emerging Telecommunications Technologies, 31(6): e3876, which has been published in final form at https://doi.org/10.1002/ett.3876. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.