Handover decision for small cells: Algorithms, lessons learned and simulation study

Abstract

More and more cellular network operators enable the unplanned deployment of small-sized cellular stations by the end users into the predominant macrocellular network layout. This increases the spatial capacity of the cellular system and reduces the costs for installing, managing, and operating the radio access network. However, the impact of such an unplanned network densification on the robustness of cell handover (HO) still remains unclear and needs to be studied. For this purpose, in this paper we highlight the key aspects of the cell HO process in the presence of small cells and identify the main issues that affect its robustness. We summarize lessons learned from the rich literature on HO decision algorithms for small cells, and present an algorithm for alleviating interference in the cellular uplink while prolonging the battery lifetime of the user terminal. Based on the evaluation methodology of the Small Cell Forum, we conduct a comprehensive system-level simulation study to validate the accuracy of our findings and provide valuable insights on the key performance trade-offs inherent to the HO decision for small cells . 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 Abstract -More and more cellular network operators enable the unplanned deployment of small-sized cellular stations by the end users into the predominant macrocellular network layout. This increases the spatial capacity of the cellular system and reduces the costs for installing, managing, and operating the radio access network. However, the impact of such an unplanned network densification on the robustness of cell handover (HO) still remains unclear and needs to be studied. For this purpose, in this paper we highlight the key aspects of the cell HO process in the presence of small cells and identify the main issues that affect its robustness. We summarize lessons learned from the rich literature on HO decision algorithms for small cells, and present an algorithm for alleviating interference in the cellular uplink while prolonging the battery lifetime of the user terminal. Based on the evaluation methodology of the Small Cell Forum, we conduct a comprehensive system-level simulation study to validate the accuracy of our findings and provide valuable insights on the key performance trade-offs inherent to the HO decision for small cells.

Theoretical Analysis of REM-Based Handover Algorithm for Heterogeneous Networks

“…However, their method has two significant drawbacks: first, the estimated gain relies on the prediction of the sojourn time within the cell, which in turn reduces the applicability of the algorithm to hand-in only; and second, the method is aimed to pedestrians. On a similar note, Xenakis et al [24] introduce an HO decision algorithm for LTE that takes into account both the interference at the UE side and its battery life designed for indoor use. They optimize two HHMs: the first one skips cells that might compromise service continuity, i.e.…”

“…where β q = min arcsin R f /R c , β HF,p . Combining ( 16) and ( 23), the total picocell HF probability is derived in (24), as shown at the bottom of this page.…”

Quality of experience and quality of service‐aware handover for video transmission in heterogeneous networks

“…14 Although QoS-aware handovers have better performance at a HetNet scenario, it is not appropriate for multimedia applications due to poor performance. 24 Xenakis et al 25 give details about the benefits and challenges of using small cells in HetNet, highlighting the importance of considering smaller cells in the load balancing of network infrastructure. However, it does not consider video content application.…”

Dynamic Programming Based Content Placement Strategy for 5G and Beyond Cellular Networks

“…Indeed, as the network densification increases, this caching scheme becomes very complex and demands a robust handover decision algorithm. Hence, the predicted-location based caching can benefit the synergy of using effective handover techniques, such as the one proposed in [11]. In addition, the work in [12] presented a caching strategy based on the prediction of file popularity and future requests.…”