16 research outputs found
Resource and power management in next generation networks
The limits of today’s cellular communication systems are constantly being tested by
the exponential increase in mobile data traffic, a trend which is poised to continue
well into the next decade. Densification of cellular networks, by overlaying smaller
cells, i.e., micro, pico and femtocells, over the traditional macrocell, is seen as an
inevitable step in enabling future networks to support the expected increases in data
rate demand. Next generation networks will most certainly be more heterogeneous
as services will be offered via various types of points of access (PoAs). Indeed, besides
the traditional macro base station, it is expected that users will also be able to
access the network through a wide range of other PoAs: WiFi access points, remote
radio-heads (RRHs), small cell (i.e., micro, pico and femto) base stations or even
other users, when device-to-device (D2D) communications are supported, creating
thus a multi-tiered network architecture. This approach is expected to enhance the
capacity of current cellular networks, while patching up potential coverage gaps.
However, since available radio resources will be fully shared, the inter-cell interference
as well as the interference between the different tiers will pose a significant
challenge. To avoid severe degradation of network performance, properly managing
the interference is essential. In particular, techniques that mitigate interference such
Inter Cell Interference Coordination (ICIC) and enhanced ICIC (eICIC) have been
proposed in the literature to address the issue. In this thesis, we argue that interference
may be also addressed during radio resource scheduling tasks, by enabling
the network to make interference-aware resource allocation decisions.
Carrier aggregation technology, which allows the simultaneous use of several
component carriers, on the other hand, targets the lack of sufficiently large portions
of frequency spectrum; a problem that severely limits the capacity of wireless networks.
The aggregated carriers may, in general, belong to different frequency bands,
and have different bandwidths, thus they also may have very different signal propagation
characteristics. Integration of carrier aggregation in the network introduces
additional tasks and further complicates interference management, but also opens
up a range of possibilities for improving spectrum efficiency in addition to enhancing
capacity, which we aim to exploit. In this thesis, we first look at the resource allocation in problem in dense multitiered
networks with support for advanced features such as carrier aggregation and
device-to-device communications. For two-tiered networks with D2D support, we
propose a centralised, near optimal algorithm, based on dynamic programming principles,
that allows a central scheduler to make interference and traffic-aware scheduling
decisions, while taking into consideration the short-lived nature of D2D links.
As the complexity of the central scheduler increases exponentially with the number
of component carriers, we further propose a distributed heuristic algorithm to tackle
the resource allocation problem in carrier aggregation enabled dense networks. We
show that the solutions we propose perform significantly better than standard solutions
adopted in cellular networks such as eICIC coupled with Proportional Fair
scheduling, in several key metrics such as user throughput, timely delivery of content
and spectrum and energy efficiency, while ensuring fairness for backward compatible
devices.
Next, we investigate the potentiality to enhance network performance by enabling
the different nodes of the network to reduce and dynamically adjust the
transmit power of the different carriers to mitigate interference. Considering that
the different carriers may have different coverage areas, we propose to leverage this
diversity, to obtain high-performing network configurations. Thus, we model the
problem of carrier downlink transmit power setting, as a competitive game between
teams of PoAs, which enables us to derive distributed dynamic power setting algorithms.
Using these algorithms we reach stable configurations in the network,
known as Nash equilibria, which we show perform significantly better than fixed
power strategies coupled with eICIC
The Impact of Digital Technologies on Business Internationalization Process
This paper discusses and analyses the impact of digital technology on business internationalization with focus on a case study of a developing country. There is evidence showing digital technology contributed on the development and advancement of the competitive international market. Accordingly, many companies are considering the change adopts the business model. Businesses lean towards believing that the use of digital technology enables them building the better relationship with customers and suppliers, improving their business process, and in some cases even simulating them in restructuring the entire business industry. In well-established businesses, technology has become the basis of every work in the process. Nonetheless, the situation maybe different in an uncertain business’ environment, specifically with businesses in developing countries. Consequently, this research is quantitatively focused in observing and measuring the impact of digital technology on international business within a developing country. The development of digital technology, types of digital technology, application of digital technology, digital transformation of the supply chain are examined through a quantitative research approach. Nonetheless, the globalization of enterprises and their entry into new markets are challenging the businesses as the global scale factors are putting pressure from increasing competition worldwide. This problem maybe more noticeable among the businesses based in the developing countries. In this respect, it may be questioned whether businesses from these countries can keep competing by using the latest technologies and how they succeed to use these technologies in their international operations
Distributed Downlink Power Control for Dense Networks with Carrier Aggregation
Given the proven benefits cell densification brings in terms of capacity and coverage, it is certain that 5G networks will be even more heterogeneous and dense. However, as smaller cells are introduced in the network, interference will inevitably become a serious problem as they are expected to share the same radio resources. Another central feature envisioned for future cellular networks is carrier aggregation (CA), which allows users to simultaneously use several component carriers of various widths and frequency bands. By exploiting the diversity of the different carriers, CA can also be used to effectively mitigate the interference in the network. In this paper, we leverage the above key features of next-generation cellular networks and formulate a downlink power setting problem for the different available carriers. Using game theory, we design a distributed algorithm that lets cells dynamically adjust different transmit powers for the different carriers. The proposed solution greatly improves network performance by reducing interference and power consumption, while ensuring coverage for as many users as possible. We compare our scheme with other interference mit- igation techniques, in a realistic large-scale scenario. Numerical results show that our solution outperforms the existing schemes in terms of user throughput, energy, and spectral efficiency
Mmwave Beam Management in Urban Vehicular Networks
Millimeter-wave (mmwave) communication represents a potential solution to
capacity shortage in vehicular networks. However, effective beam alignment
between senders and receivers requires accurate knowledge of the vehicles'
position for fast beam steering, which is often impractical to obtain in real
time. We address this problem by leveraging the traffic signals regulating
vehicular mobility: as an example, we may coordinate beams with red traffic
lights, as they correspond to higher vehicle densities and lower speeds. To
evaluate our intuition, we propose a tractable, yet accurate, mmwave
communication model accounting for both the distance and the heading of
vehicles being served. Using such a model, we optimize the beam design and
define a low-complexity, heuristic strategy. For increased realism, we consider
as reference scenario a large-scale, real-world mobility trace of vehicles in
Luxembourg. The results show that our approach closely matches the optimum and
always outperforms static beam design based on road topology alone. Remarkably,
it also yields better performance than solutions based on real-time mobility
information
Graph-based Model for Beam Management in Mmwave Vehicular Networks
Mmwave bands are being widely touted as a very promising option for future 5G
networks, especially in enabling such networks to meet highly demanding rate
requirements. Accordingly, the usage of these bands is also receiving an
increasing interest in the context of 5G vehicular networks, where it is
expected that connected cars will soon need to transmit and receive large
amounts of data. Mmwave communications, however, require the link to be
established using narrow directed beams, to overcome harsh propagation
conditions. The advanced antenna systems enabling this also allow for a complex
beam design at the base station, where multiple beams of different widths can
be set up. In this work, we focus on beam management in an urban vehicular
network, using a graph-based approach to model the system characteristics and
the existing constraints. In particular, unlike previous work, we formulate the
beam design problem as a maximum-weight matching problem on a bipartite graph
with conflicts, and then we solve it using an efficient heuristic algorithm.
Our results show that our approach easily outperforms advanced methods based on
clustering algorithms
Interference-Aware Downlink and Uplink Resource Allocation in HetNets with D2D Support
We address the resource allocation problem in an LTE-based 2-tier heterogeneous network where in-band D2D communications are supported under network control. The different communication paradigms share the same radio resources, thus they may interfere. We devise a dynamic programming approach to efficiently schedule download and upload traffic, by 1) efficiently matching communicating endpoints and 2) assigning radio resources in an interference-aware manner while accounting for the characteristics of the content to be delivered. To this end, we develop an accurate model of the system and apply approximate dynamic programming to solve it. Our solution allows us to deal with realistic large-scale scenarios. In such scenarios, we compare our approach to today's networks where eICIC techniques and proportional fairness scheduling are implemented. Results highlight that our solution increases the system throughput while greatly reducing energy consumption. We also show that D2D mode, established either in the downlink or uplink, can effectively support delivery of highly popular content without significantly harming macrocell or microcell traffic, leading to increased system capacity. Interestingly, we find that D2D mode can also be a low-cost alternative to microcells
Mmwave Beam Management in Urban Vehicular Networks
Millimeter-wave (mmwave) communication repre- sents a potential solution to capacity shortage in vehicular net- works. However, effective beam alignment between senders and receivers requires accurate knowledge of the vehicles’ position for fast beam steering, which is often impractical to obtain in real time. We address this problem by leveraging the traffic signals regulating vehicular mobility: as an example, we may coordinate beams with red traffic lights, as they correspond to higher vehicle densities and lower speeds. To evaluate our intuition, we propose a tractable, yet accurate, mmwave communication model accounting for both the distance and the heading of vehicles being served. Using such a model, we optimize the beam design and define a low-complexity, heuristic strategy. For increased realism, we consider as reference scenario a large-scale, real- world mobility trace of vehicles in Luxembourg. The results show that our approach closely matches the optimum and always outperforms static beam design based on road topology alone. Remarkably, it also yields better performance than solutions based on real-time mobility information