Using hypergraph theory to model coexistence management and coordinated spectrum allocation for heterogeneous wireless networks operating in shared spectrum

Electromagnetic waves in the Radio Frequency (RF) spectrum are used to convey wireless transmissions from one radio antenna to another. Spectrum utilisation factor, which refers to how readily a given spectrum can be reused across space and time while maintaining an acceptable level of transmission errors, is used to measure how efficiently a unit of frequency spectrum can be allocated to a specified number of users. The demand for wireless applications is increasing exponentially, hence there is a need for efficient management of the RF spectrum. However, spectrum usage studies have shown that the spectrum is under-utilised in space and time. A regulatory shift from static spectrum assignment to DSA is one way of addressing this. Licence exemption policy has also been advanced in Dynamic Spectrum Access (DSA) systems to spur wireless innovation and universal access to the internet. Furthermore, there is a shift from homogeneous to heterogeneous radio access and usage of the same spectrum band. These three shifts from traditional spectrum management have led to the challenge of coexistence among heterogeneous wireless networks which access the spectrum using DSA techniques. Cognitive radios have the ability for spectrum agility based on spectrum conditions. However, in the presence of multiple heterogeneous networks and without spectrum coordination, there is a challenge related to switching between available channels to minimise interference and maximise spectrum allocation. This thesis therefore focuses on the design of a framework for coexistence management and spectrum coordination, with the objective of maximising spectrum utilisation across geographical space and across time. The amount of geographical coverage in which a frequency can be used is optimised through frequency reuse while ensuring that harmful interference is minimised. The time during which spectrum is occupied is increased through time-sharing of the same spectrum by two or more networks, while ensuring that spectrum is shared by networks that can coexist in the same spectrum and that the total channel load is not excessive to prevent spectrum starvation. Conventionally, a graph is used to model relationships between entities such as interference relationships among networks. However, the concept of an edge in a graph is not sufficient to model relationships that involve more than two entities, such as more than two networks that are able to share the same channel in the time domain, because an edge can only connect two entities. On the other hand, a hypergraph is a generalisation of an undirected graph in which a hyperedge can connect more than two entities. Therefore, this thesis investigates the use of hypergraph theory to model the RF environment and the spectrum allocation scheme. The hypergraph model was applied to an algorithm for spectrum sharing among 100 heterogeneous wireless networks, whose geo-locations were randomly and independently generated in a 50 km by 50 km area. Simulation results for spectrum utilisation performance have shown that the hypergraph-based model allocated channels, on average, to 8% more networks than the graph-based model. The results also show that, for the same RF environment, the hypergraph model requires up to 36% fewer channels to achieve, on average, 100% operational networks, than the graph model. The rate of growth of the running time of the hypergraph-based algorithm with respect to the input size is equal to the square of the input size, like the graph-based algorithm. Thus, the model achieved better performance at no additional time complexity.Electromagnetic waves in the Radio Frequency (RF) spectrum are used to convey wireless transmissions from one radio antenna to another. Spectrum utilisation factor, which refers to how readily a given spectrum can be reused across space and time while maintaining an acceptable level of transmission errors, is used to measure how efficiently a unit of frequency spectrum can be allocated to a specified number of users. The demand for wireless applications is increasing exponentially, hence there is a need for efficient management of the RF spectrum. However, spectrum usage studies have shown that the spectrum is under-utilised in space and time. A regulatory shift from static spectrum assignment to DSA is one way of addressing this. Licence exemption policy has also been advanced in Dynamic Spectrum Access (DSA) systems to spur wireless innovation and universal access to the internet. Furthermore, there is a shift from homogeneous to heterogeneous radio access and usage of the same spectrum band. These three shifts from traditional spectrum management have led to the challenge of coexistence among heterogeneous wireless networks which access the spectrum using DSA techniques. Cognitive radios have the ability for spectrum agility based on spectrum conditions. However, in the presence of multiple heterogeneous networks and without spectrum coordination, there is a challenge related to switching between available channels to minimise interference and maximise spectrum allocation. This thesis therefore focuses on the design of a framework for coexistence management and spectrum coordination, with the objective of maximising spectrum utilisation across geographical space and across time. The amount of geographical coverage in which a frequency can be used is optimised through frequency reuse while ensuring that harmful interference is minimised. The time during which spectrum is occupied is increased through time-sharing of the same spectrum by two or more networks, while ensuring that spectrum is shared by networks that can coexist in the same spectrum and that the total channel load is not excessive to prevent spectrum starvation. Conventionally, a graph is used to model relationships between entities such as interference relationships among networks. However, the concept of an edge in a graph is not sufficient to model relationships that involve more than two entities, such as more than two networks that are able to share the same channel in the time domain, because an edge can only connect two entities. On the other hand, a hypergraph is a generalisation of an undirected graph in which a hyperedge can connect more than two entities. Therefore, this thesis investigates the use of hypergraph theory to model the RF environment and the spectrum allocation scheme. The hypergraph model was applied to an algorithm for spectrum sharing among 100 heterogeneous wireless networks, whose geo-locations were randomly and independently generated in a 50 km by 50 km area. Simulation results for spectrum utilisation performance have shown that the hypergraph-based model allocated channels, on average, to 8% more networks than the graph-based model. The results also show that, for the same RF environment, the hypergraph model requires up to 36% fewer channels to achieve, on average, 100% operational networks, than the graph model. The rate of growth of the running time of the hypergraph-based algorithm with respect to the input size is equal to the square of the input size, like the graph-based algorithm. Thus, the model achieved better performance at no additional time complexity

On the feasibility of the communications in the TVWS spectrum analysis and coexistence issue

In the last decade, the enormous growth in the wireless industry has come from using only a small part of the wireless spectrum, nominally less than 10% under 3 GHz. Nowadays, the vast majority of the available spectral resources have already been licensed. Measurements made by the Federal Communication Commission (FCC) have shown that a great part of the spectrum, although allocated, is virtually unused. For all this reasons, in the last years, several countries have already (USA) or are in the process (EU, China, Japan, South Korea) of switching off analog TV broadcasting in favor of Digital Terrestrial Television (DTT) broadcasting systems and digital switchover plans have driven a thorough review of TV spectrum exploitation. The resulting unused channels within this band are called “TV white spaces” (TVWS). Even after the redistribution of the digital TV channels, the problem of an efficient utilization of the allocated frequencies is still far from being solved. For example, there are still large territorial areas on which, although allocated, the TV channels result unused, due to coverage problems. New spectrum allocation approaches such as the dynamic spectrum access method have been studied. This new concept implies that the radio terminals have the capacity to monitor their own radio environment and consequently adapt to the transmission conditions on whatever frequency band are available (adaptive radio). If this concept is supplemented with the capacity of analyzing the surrounding radio environment in search of white spaces, the term adaptive radio is extended to Cognitive Radio (CR). The spectrum management rule of CR is that all new users for the spectrum are secondary (cognitive) users (SU) and requires that they must detect and avoid the primary (licensed) users (PU) in terms of used frequencies, transmission power and modulation scheme. In the TV bands specifically, the presence of PUs (e.g. TV broadcasters) can be revealed both performing a spectrum sensing operation and considering the information provided by the external databases called “geo-location databases” (GL-DB). The database provides, for a certain location, the list of the free TV channels and the allowable maximum effective isotropic radiated power (EIRP) for transmitting without harmful interference to incumbent users. Decision thresholds are still a critical parameter for protecting services in a scenario where cognitive devices would be operating. There are cases where the approach based on GL Spectrum Occupancy DB might not be available, either because the database does not exist for that area (for example in non densely populated areas) or in the case that access to the database is not possible (deep indoor operation, low populated areas etc.). Several studies have suggested that radio noise has increased significantly over the last decades and consequently the assumptions about decision thresholds and interference protection ratios might be outdated. The Hidden Node Margin (HNM) is a parameter that quantifies the difference between the potential interfered signal values at the location where it is measured or estimated by the cognitive device, and the actual value at the location where the receiving antenna for this signal is located. HNM is a key parameter to define the protection requirements that cognitive devices must comply in order not to create any harmful interference to broadcast receiving systems. In this context, this thesis goes in a precise direction, with four main topics related to the feasibility of communication cognitive systems operating in the TVWS, considering coexistence as the main operational issue. The first topic studies new spectrum sensing approaches in order to improve the more critical functionality of CRs. In the second topic an unlicensed indoor short-range distribution system for the wireless retransmission in the DTT band of High definition TV (HDTV) contents with immediate implementations as home entertainment systems has been carried out. The third topic of this thesis is about a particular database developed in order to provide information to easily calculate HNM values and associated statistics, TV Channel Occupancy and Man Made Noise Upper Limits. The empirical data for this work has been recorded in different locations of Spain and Italy during 2011 and 2012 thanks to the partnership between the Department of Electrical and Electronic Engineering (D.I.E.E.) of the University of Cagliari and the Department of Electronics and Telecommunications of the University of Bilbao (UPV/EHU). Finally in the last topic we focus on the IEEE 802.22 WRAN standard evaluating, thanks to extended measurements, the performance of an 802.22 system operating into the same coverage range of a DTT receiver