Interference Aware Cognitive Femtocell Networks

Femtocells Access Points (FAP) are low power, plug and play home base stations which are designed to extend the cellular radio range in indoor environments where macrocell coverage is generally poor. They offer significant increases in data rates over a short range, enabling high speed wireless and mobile broadband services, with the femtocell network overlaid onto the macrocell in a dual-tier arrangement. In contrast to conventional cellular systems which are well planned, FAP are arbitrarily installed by the end users and this can create harmful interference to both collocated femtocell and macrocell users. The interference becomes particularly serious in high FAP density scenarios and compromises the ensuing data rate. Consequently, effective management of both cross and co-tier interference is a major design challenge in dual-tier networks. Since traditional radio resource management techniques and architectures for single-tier systems are either not applicable or operate inefficiently, innovative dual-tier approaches to intelligently manage interference are required. This thesis presents a number of original contributions to fulfill this objective including, a new hybrid cross-tier spectrum sharing model which builds upon an existing fractional frequency reuse technique to ensure minimal impact on the macro-tier resource allocation. A new flexible and adaptive virtual clustering framework is then formulated to alleviate co-tier interference in high FAP densities situations and finally, an intelligent coverage extension algorithm is developed to mitigate excessive femto-macrocell handovers, while upholding the required quality of service provision. This thesis contends that to exploit the undoubted potential of dual-tier, macro-femtocell architectures an interference awareness solution is necessary. Rigorous evidence confirms that noteworthy performance improvements can be achieved in the quality of the received signal and throughput by applying cognitive methods to manage interference

Interference mitigation in cognitive femtocell networks

“A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of Philosophy”.Femtocells have been introduced as a solution to poor indoor coverage in cellular communication which has hugely attracted network operators and stakeholders. However, femtocells are designed to co-exist alongside macrocells providing improved spatial frequency reuse and higher spectrum efficiency to name a few. Therefore, when deployed in the two-tier architecture with macrocells, it is necessary to mitigate the inherent co-tier and cross-tier interference. The integration of cognitive radio (CR) in femtocells introduces the ability of femtocells to dynamically adapt to varying network conditions through learning and reasoning. This research work focuses on the exploitation of cognitive radio in femtocells to mitigate the mutual interference caused in the two-tier architecture. The research work presents original contributions in mitigating interference in femtocells by introducing practical approaches which comprises a power control scheme where femtocells adaptively controls its transmit power levels to reduce the interference it causes in a network. This is especially useful since femtocells are user deployed as this seeks to mitigate interference based on their blind placement in an indoor environment. Hybrid interference mitigation schemes which combine power control and resource/scheduling are also implemented. In a joint threshold power based admittance and contention free resource allocation scheme, the mutual interference between a Femtocell Access Point (FAP) and close-by User Equipments (UE) is mitigated based on admittance. Also, a hybrid scheme where FAPs opportunistically use Resource Blocks (RB) of Macrocell User Equipments (MUE) based on its traffic load use is also employed. Simulation analysis present improvements when these schemes are applied with emphasis in Long Term Evolution (LTE) networks especially in terms of Signal to Interference plus Noise Ratio (SINR)

An interference-aware virtual clustering paradigm for resource management in cognitive femtocell networks

Femtocells represent a promising alternative solution for high quality wireless access in indoor scenarios where conventional cellular system coverage can be poor. They are randomly deployed by the end user, so only post deployment network planning is possible. Furthermore, this uncoordinated deployment creates severe interference to co-located femtocells, especially in dense deployments. This paper presents a new architecture using a generalised virtual cluster femtocell (GVCF) paradigm, which groups together FAP into logical clusters. It guarantees severely interfering and overlapping femtocells are assigned to different clusters. Since each cluster operates on different band of frequencies, the corresponding virtual cluster controller only has to manage its own FAPs, so the overall system complexity is low. The performance of the GVCF algorithm is analysed from both a resource availability and cluster number perspective. Simulation results conclusively corroborate the superior performance of the GVCF model in interference mitigation, particularly in high density FAP scenarios

Tight Lower Bounds on the Contact Distance Distribution in Poisson Hole Process

In this letter, we derive new lower bounds on the cumulative distribution function (CDF) of the contact distance in the Poisson Hole Process (PHP) for two cases: (i) reference point is selected uniformly at random from $\mathbb{R}^2$ independently of the PHP, and (ii) reference point is located at the center of a hole selected uniformly at random from the PHP. While one can derive upper bounds on the CDF of contact distance by simply ignoring the effect of holes, deriving lower bounds is known to be relatively more challenging. As a part of our proof, we introduce a tractable way of bounding the effect of all the holes in a PHP, which can be used to study other properties of a PHP as well.Comment: To appear in IEEE Wireless Communications Letter

Sensing and Sharing Schemes for Spectral Efficiency of Cognitive Radios

Increase in data traffic, number of users and their requirements laid to a necessity of more bandwidth. Cognitive radio is one of the emerging technology which addresses the spectrum scarcity issue. In this work we study the advantage of having collaboration between cognitive enabled small cell network and primary macrocell. Different from the existing works at spectrum sensing stage we are applying enhanced spectrum sensing to avoid probability of false alarms and missed detections which has impact on spectral efficiency. Later power control optimization for secondary users known as Hybrid spectrum sharing is used for further improvement of spectral efficiency. Furthermore, the failed packets of Primary users are taken care by high ranked relays which in turn decreases the average Primary user packet delay by 20% when compared between assisted Secondary user method and non-assisted Secondary user method.

Energy-Efficient Resource Allocation Optimization for Multimedia Heterogeneous Cloud Radio Access Networks

The heterogeneous cloud radio access network (H-CRAN) is a promising paradigm which incorporates the cloud computing into heterogeneous networks (HetNets), thereby taking full advantage of cloud radio access networks (C-RANs) and HetNets. Characterizing the cooperative beamforming with fronthaul capacity and queue stability constraints is critical for multimedia applications to improving energy efficiency (EE) in H-CRANs. An energy-efficient optimization objective function with individual fronthaul capacity and inter-tier interference constraints is presented in this paper for queue-aware multimedia H-CRANs. To solve this non-convex objective function, a stochastic optimization problem is reformulated by introducing the general Lyapunov optimization framework. Under the Lyapunov framework, this optimization problem is equivalent to an optimal network-wide cooperative beamformer design algorithm with instantaneous power, average power and inter-tier interference constraints, which can be regarded as the weighted sum EE maximization problem and solved by a generalized weighted minimum mean square error approach. The mathematical analysis and simulation results demonstrate that a tradeoff between EE and queuing delay can be achieved, and this tradeoff strictly depends on the fronthaul constraint