- Thursday, 15 June, 9:00-10:30, Room Theatre Big Stage
- Session Chair: Luis M. Correia (IST - University of Lisbon & INESC, Portugal)
Marco Dolfi (University of Florence & CNIT, Italy); Simone Morosi (University of Florence - CNIT, Italy); Cicek Cavdar (KTH Royal Institute of Technology, Sweden); Enrico Del Re (University of Florence & CNIT, Italy)
As base stations (BS) are responsible for the large amount of energy consumed in cellular networks, energy efficient BS sleep mode techniques have the potential to save a significant amount of energy. However, assuming that BSs are able to alternate between sleeping and active states as frequently as possible may have a negative impact on network reliability, shortening BS lifetime. In this paper we propose a multiobjective optimization framework aimed at minimizing the power consumption and number of BS sleep mode switchings in heterogeneous cellular networks (HetNet), by jointly considering Quality of Service (QoS) requirements. We focus on the HetNet scenario in which macro and micro cells coexist. The Mixed Integer Quadratic Programming (MIQP) optimization technique is used to minimize the power consumption together with the number of BS sleep mode operations of both macro and micro cells. The trade-off between power consumption, sleep mode switchings and performance of the network is shown for different energy saving solutions. Results show that the proposed optimization can guarantee QoS target throughput for users and significant reduction of 50\% for macro and 73\% for micro BS respectively daily number of switchings, while still achieving 8\% savings in terms of daily energy consumption.
Haeyoung Lee, Seiamak Vahid and Klaus Moessner (University of Surrey, United Kingdom (Great Britain))
We consider the resource allocation with aggregation of multiple bands including unlicensed band for heterogeneous traffic. While the mobile data traffic including high volume of video traffic is expected to increase significantly, an efficient management of radio resources from multiple bands is required to guarantee the quality of service (QoS) of different traffic types. In this context, we formulate an optimal resource allocation by using different utility functions for heterogeneous traffic and the two-step resource allocation algorithm including resource grouping has been proposed. Simulation results demonstrate that the proposed algorithm enhances the connection robustness and shows good performance in terms of higher utility value of inelastic traffic even at high traffic loads by steering elastic traffic to unlicensed band.
Tachporn Sanguanpuak (University of Oulu, Finland); Sudarshan Guruacharya and Ekram Hossain (University of Manitoba, Canada); Nandana Rajatheva (University of Oulu, Finland); Matti Latva-aho (UoOulu, Finland)
The growing demand in indoor small cell networks has given rise to the concept micro-operators (MOs) for local service delivery. We model and analyze a spectrum sharing system involving such MOs where a buyer MO buys multiple licensed bands provided by the regulator. Also, all small cell base stations (SBSs) owned by a buyer MO can utilize multiple licensed bands at the same time which are also used by other MOs. A deterministic model in which the location of the SBSs are known can lead to unwieldy problem formulation, when the number of SBSs is large. Subsequently, we adopt a stochastic geometric model of the SBS deployment instead of a deterministic model. Assuming that the locations of the SBSs can be modeled as a homogeneous Poisson point process, we find the downlink signalto- interference-plus-noise ratio (SINR) coverage probability and average data rate for a typical user (UE) served by the buyer MO in a spectrum sharing environment. In order to satisfy the QoS constraint, we provide a greedy algorithm to find how many licensed bands and which band for the buyer MO to purchase from the regulator. We also derive the coverage probability of the buyer MO for interference the limited system. Also, we show that spectrum sharing for MO network is beneficial for both coverage and average data rate.
Ikram Ashraf (Oulu, Finland); Chen-Feng Liu (Centre for Wireless Communications, University of Oulu, Finland); Mehdi Bennis (Centre of Wireless Communications, University of Oulu, Finland); Walid Saad (Virginia Tech, USA)
Recently vehicle-to-vehicle (V2V) communication emerged as a key enabling technology to ensure traffic safety and other mission-critical applications. In this paper, a novel proximity and quality-of-service (QoS)-aware resource allocation for V2V communication is proposed. The proposed approach exploits the spatial-temporal aspects of vehicles in terms of their physical proximity and traffic demands, to minimize the total transmission power while considering queuing latency and reliability. Due to the overhead caused by frequent information exchange between vehicles and the roadside unit (RSU), the centralized problem is decoupled into two interrelated subproblems. First, a novel RSU-assisted virtual clustering mechanism is proposed to group vehicles in zones based on their physical proximity. Given the vehicles' traffic demands and their QoS requirements, resource blocks are assigned to each zone. Second, leveraging techniques from Lyapunov stochastic optimization, a power minimization solution is proposed for each V2V pair within each zone. Simulation results for a Manhattan model have shown that the proposed scheme outperforms the baseline in terms of average queuing latency reduction up to 97% and significant improvement in reliability.
Heikki Karvonen (University of Oulu, Centre for Wireless Communications, Finland); Matti Hämäläinen, Jari Iinatti and Carlos A Pomalaza-Ráez (University of Oulu, Finland)
The goal of this paper is to provide a comprehensive view of the coexistence nature of wireless technologies most likely to be found in health care scenarios' environment. The diversity and number of these technologies is increasing constantly leading to potential interference problems and performance degradation of wireless medical applications which are expected to become popular in 5G systems. The industrial, scientific and medical (ISM) bands in the 2.4 GHz are already very crowded to the point that the location and use of medical devices have to take into account the pervasive presence of other wireless devices operating in that region of the spectrum. A temporary solution is to use more the 5 GHz bands currently not heavily utilized. This scenario will change in the near future as other technologies such as MulteFire and unlicensed long-term evolution (LTE) solutions start operating in those bands. This paper provides a summary of the wireless technologies and devices present in hospitals and other medical care scenarios. It also provides recommendations for the rational share of the spectrum in those scenarios.