Leveraging intelligence from network CDR data for interference aware energy consumption minimization

Cell densification is being perceived as the panacea for the imminent capacity crunch. However, high aggregated energy consumption and increased inter-cell interference (ICI) caused by densification, remain the two long-standing problems. We propose a novel network orchestration solution for simultaneously minimizing energy consumption and ICI in ultra-dense 5G networks. The proposed solution builds on a big data analysis of over 10 million CDRs from a real network that shows there exists strong spatio-temporal predictability in real network traffic patterns. Leveraging this we develop a novel scheme to pro-actively schedule radio resources and small cell sleep cycles yielding substantial energy savings and reduced ICI, without compromising the users QoS. This scheme is derived by formulating a joint Energy Consumption and ICI minimization problem and solving it through a combination of linear binary integer programming, and progressive analysis based heuristic algorithm. Evaluations using: 1) a HetNet deployment designed for Milan city where big data analytics are used on real CDRs data from the Telecom Italia network to model traffic patterns, 2) NS-3 based Monte-Carlo simulations with synthetic Poisson traffic show that, compared to full frequency reuse and always on approach, in best case, proposed scheme can reduce energy consumption in HetNets to 1/8th while providing same or better Qo

Optimization of 5G Second Phase Heterogeneous Radio Access Networks with Small Cells

Due to the exponential increase in high data-demanding applications and their services per coverage area, it is becoming challenging for the existing cellular network to handle the massive sum of users with their demands. It is conceded to network operators that the current wireless network may not be capable to shelter future traffic demands. To overcome the challenges the operators are taking interest in efficiently deploying the heterogeneous network. Currently, 5G is in the commercialization phase. Network evolution with addition of small cells will develop the existing wireless network with its enriched capabilities and innovative features. Presently, the 5G global standardization has introduced the 5G New Radio (NR) under the 3rd Generation Partnership Project (3GPP). It can support a wide range of frequency bands (<6 GHz to 100 GHz). For different trends and verticals, 5G NR encounters, functional splitting and its cost evaluation are well-thought-out. The aspects of network slicing to the assessment of the business opportunities and allied standardization endeavours are illustrated. The study explores the carrier aggregation (Pico cellular) technique for 4G to bring high spectral efficiency with the support of small cell massification while benefiting from statistical multiplexing gain. One has been able to obtain values for the goodput considering CA in LTE-Sim (4G), of 40 Mbps for a cell radius of 500 m and of 29 Mbps for a cell radius of 50 m, which is 3 times higher than without CA scenario (2.6 GHz plus 3.5 GHz frequency bands). Heterogeneous networks have been under investigation for many years. Heterogeneous network can improve users service quality and resource utilization compared to homogeneous networks. Quality of service can be enhanced by putting the small cells (Femtocells or Picocells) inside the Microcells or Macrocells coverage area. Deploying indoor Femtocells for 5G inside the Macro cellular network can reduce the network cost. Some service providers have started their solutions for indoor users but there are still many challenges to be addressed. The 5G air-simulator is updated to deploy indoor Femto-cell with proposed assumptions with uniform distribution. For all the possible combinations of apartments side length and transmitter power, the maximum number of supported numbers surpassed the number of users by more than two times compared to papers mentioned in the literature. Within outdoor environments, this study also proposed small cells optimization by putting the Pico cells within a Macro cell to obtain low latency and high data rate with the statistical multiplexing gain of the associated users. Results are presented 5G NR functional split six and split seven, for three frequency bands (2.6 GHz, 3.5GHz and 5.62 GHz). Based on the analysis for shorter radius values, the best is to select the 2.6 GHz to achieve lower PLR and to support a higher number of users, with better goodput, and higher profit (for cell radius u to 400 m). In 4G, with CA, from the analysis of the economic trade-off with Picocell, the Enhanced multi-band scheduler EMBS provide higher revenue, compared to those without CA. It is clearly shown that the profit of CA is more than 4 times than in the without CA scenario. This means that the slight increase in the cost of CA gives back more than 4-time profit relatively to the ”without” CA scenario.Devido ao aumento exponencial de aplicações/serviços de elevado débito por unidade de área, torna-se bastante exigente, para a rede celular existente, lidar com a enormes quantidades de utilizadores e seus requisitos. É reconhecido que as redes móveis e sem fios atuais podem não conseguir suportar a procura de tráfego junto dos operadores. Para responder a estes desafios, os operadores estão-se a interessar pelo desenvolvimento de redes heterogéneas eficientes. Atualmente, a 5G está na fase de comercialização. A evolução destas redes concretizar-se-á com a introdução de pequenas células com aptidões melhoradas e características inovadoras. No presente, os organismos de normalização da 5G globais introduziram os Novos Rádios (NR) 5G no contexto do 3rd Generation Partnership Project (3GPP). A 5G pode suportar uma gama alargada de bandas de frequência (<6 a 100 GHz). Abordam-se as divisões funcionais e avaliam-se os seus custos para as diferentes tendências e verticais dos NR 5G. Ilustram-se desde os aspetos de particionamento funcional da rede à avaliação das oportunidades de negócio, aliadas aos esforços de normalização. Exploram-se as técnicas de agregação de espetro (do inglês, CA) para pico células, em 4G, a disponibilização de eficiência espetral, com o suporte da massificação de pequenas células, e o ganho de multiplexagem estatística associado. Obtiveram-se valores do débito binário útil, considerando CA no LTE-Sim (4G), de 40 e 29 Mb/s para células de raios 500 e 50 m, respetivamente, três vezes superiores em relação ao caso sem CA (bandas de 2.6 mais 3.5 GHz). Nas redes heterogéneas, alvo de investigação há vários anos, a qualidade de serviço e a utilização de recursos podem ser melhoradas colocando pequenas células (femto- ou pico-células) dentro da área de cobertura de micro- ou macro-células). O desenvolvimento de pequenas células 5G dentro da rede com macro-células pode reduzir os custos da rede. Alguns prestadores de serviços iniciaram as suas soluções para ambientes de interior, mas ainda existem muitos desafios a ser ultrapassados. Atualizou-se o 5G air simulator para representar a implantação de femto-células de interior com os pressupostos propostos e distribuição espacial uniforme. Para todas as combinações possíveis do comprimento lado do apartamento, o número máximo de utilizadores suportado ultrapassou o número de utilizadores suportado (na literatura) em mais de duas vezes. Em ambientes de exterior, propuseram-se pico-células no interior de macro-células, de forma a obter atraso extremo-a-extremo reduzido e taxa de transmissão dados elevada, resultante do ganho de multiplexagem estatística associado. Apresentam-se resultados para as divisões funcionais seis e sete dos NR 5G, para 2.6 GHz, 3.5GHz e 5.62 GHz. Para raios das células curtos, a melhor solução será selecionar a banda dos 2.6 GHz para alcançar PLR (do inglês, PLR) reduzido e suportar um maior número de utilizadores, com débito binário útil e lucro mais elevados (para raios das células até 400 m). Em 4G, com CA, da análise do equilíbrio custos-proveitos com pico-células, o escalonamento multi-banda EMBS (do inglês, Enhanced Multi-band Scheduler) disponibiliza proveitos superiores em comparação com o caso sem CA. Mostra-se claramente que lucro com CA é mais de quatro vezes superior do que no cenário sem CA, o que significa que um aumento ligeiro no custo com CA resulta num aumento de 4-vezes no lucro relativamente ao cenário sem CA

Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks

Soaring capacity and coverage demands dictate that future cellular networks need to soon migrate towards ultra-dense networks. However, network densification comes with a host of challenges that include compromised energy efficiency, complex interference management, cumbersome mobility management, burdensome signaling overheads and higher backhaul costs. Interestingly, most of the problems, that beleaguer network densification, stem from legacy networks' one common feature i.e., tight coupling between the control and data planes regardless of their degree of heterogeneity and cell density. Consequently, in wake of 5G, control and data planes separation architecture (SARC) has recently been conceived as a promising paradigm that has potential to address most of aforementioned challenges. In this article, we review various proposals that have been presented in literature so far to enable SARC. More specifically, we analyze how and to what degree various SARC proposals address the four main challenges in network densification namely: energy efficiency, system level capacity maximization, interference management and mobility management. We then focus on two salient features of future cellular networks that have not yet been adapted in legacy networks at wide scale and thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and device-to-device (D2D) communications. After providing necessary background on CoMP and D2D, we analyze how SARC can particularly act as a major enabler for CoMP and D2D in context of 5G. This article thus serves as both a tutorial as well as an up to date survey on SARC, CoMP and D2D. Most importantly, the article provides an extensive outlook of challenges and opportunities that lie at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201

Efficient energy management in ultra-dense wireless networks

The increase in demand for more network capacity has led to the evolution of wireless networks from being largely Heterogeneous (Het-Nets) to the now existing Ultra-dense (UDNs). In UDNs, small cells are densely deployed with the goal of shortening the physical distance between the base stations (BSs) and the UEs, so as to support more user equipment (UEs) at peak times while ensuring high data rates. Compared to Het-Nets, Ultra-dense networks (UDNs) have many advantages. These include, more network capacity, higher flexibility to routine configurations, and more suitability to achieve load-balancing, hence, fewer blind spots as well as lower call blocking probability. It should be noted that, in practice, due to the high density of deployed small cells in Ultra-Dense Networks, a number of issues, or rather concerns, come with this evolution from Het-Nets. Among these issues include problems with efficient radio resource management, user cell association, inter- and intra-cell interference management and, last but not least, efficient energy consumption. Some of these issues which impact the overall network efficiency are largely due to the use of obsolete algorithms, especially those whose resource allocation is based solely on received signal power (RSSP). In this paper, the focus is solely on the efficient energy management dilemma and how to optimally reduce the overall network energy consumption. Through an extensive literature review, a detailed report into the growing concern of efficient energy management in UDNs is provided in Chapter 2. The literature review report highlights the classification as well as the evolution of some of the Mobile Wireless Technologies and Mobile Wireless Networks in general. The literature review report provides reasons as to why the energy consumption issue has become a very serious concern in UltraDense networks as well as the various techniques and measures taken to mitigate this. It is shown that, due to the increasing Mobile Wireless Systems’ carbon footprint which carries serious negative environmental impact, and the general need to lower operating costs by the network operators, the management of energy consumption increases in priority. By using the architecture of a Fourth Generation Long Term Evolution (4G-LTE) UltraDense Network, the report further shows that more than 65% of the overall energy consumption is by the access network and base stations in particular. This phenomenon explains why most attention in energy efficiency management in UDNs is largely centred on reducing the energy consumption of the deployed base stations more than any other network components like the data servers or backhauling features used. Furthermore, the report also provides detailed information on the methods/techniques, their classification, implementation, as well as a critical analysis of the said implementations in literature. This study proposes a sub-optimal algorithm and Distributed Cell Resource Allocation with a Base Station On/Off scheme that aims at reducing the overall base station power consumption in UDNs, while ensuring that the overall Quality of Service (QoS) for each User Equipment (UE) as specified in its service class is met. The modeling of the system model used and hence formulation of the Network Energy Efficiency (NEE) optimization problem is done viii using stochastic geometry. The network model comprises both evolved Node B (eNB) type macro and small cells operating on different frequency bands as well as taking into account factors that impact NEE such as UE mobility, UE spatial distribution and small cells spatial distribution. The channel model takes into account signal interference from all base stations, path loss, fading, log normal shadowing, modulation and coding schemes used on each UE’s communication channels when computing throughout. The power consumption model used takes into account both static (site cooling, circuit power) and active (transmission or load based) base station power consumption. The formulation of the NEE optimization problem takes into consideration the user’s Quality-of-service (QoS), inter-cell interference, as well as each user’s spectral efficiency and coverage/success probability. The formulated NEE optimization problem is of type Nondeterministic Polynomial time (NP)-hard, due to the user-cell association. The proposed solution to the formulated optimization problem makes use of constraint relaxation to transform the NP-hard problem into a more solvable, convex and linear optimization one. This, combined with Lagrangian dual decomposition, is used to create a distributed solution. After cellassociation and resource allocation phases, the proposed solution in order to further reduce power consumption performs Cell On/Off. Then, by using the computer simulation tools/environments, the “Distributed Resource Allocation with Cell On/Off” scheme’s performance, in comparison to four other resource allocation schemes, is analysed and evaluated given a number of different network scenarios. Finally, the statistical and mathematical results generated through the simulations indicate that the proposed scheme is the closest in NEE performance to the Exhaustive Search algorithm, and hence superior to the other sub-optimal algorithms it is compared to