Price-Based Resource Allocation for Spectrum-Sharing Femtocell Networks: A Stackelberg Game Approach

This paper investigates the price-based resource allocation strategies for the uplink transmission of a spectrum-sharing femtocell network, in which a central macrocell is underlaid with distributed femtocells, all operating over the same frequency band as the macrocell. Assuming that the macrocell base station (MBS) protects itself by pricing the interference from the femtocell users, a Stackelberg game is formulated to study the joint utility maximization of the macrocell and the femtocells subject to a maximum tolerable interference power constraint at the MBS. Especially, two practical femtocell channel models: sparsely deployed scenario for rural areas and densely deployed scenario for urban areas, are investigated. For each scenario, two pricing schemes: uniform pricing and non-uniform pricing, are proposed. Then, the Stackelberg equilibriums for these proposed games are studied, and an effective distributed interference price bargaining algorithm with guaranteed convergence is proposed for the uniform-pricing case. Finally, numerical examples are presented to verify the proposed studies. It is shown that the proposed algorithms are effective in resource allocation and macrocell protection requiring minimal network overhead for spectrum-sharing-based two-tier femtocell networks.Comment: 27 pages, 7 figures, Submitted to JSA

Channel Access and Reliability Performance in Cognitive Radio Networks:Modeling and Performance Analysis

Doktorgradsavhandling ved Institutt for Informasjons- og kommunikasjonsteknologi, Universitetet i AgderAccording to the facts and figures published by the international telecommunication union (ITU) regarding information and communication technology (ICT) industry, it is estimated that over 3.2 billion people have access to the Internet in 2015 [1]. Since 2000, this number has been octupled. Meanwhile, by the end of 2015, there were more than 7 billion mobile cellular subscriptions in the world, corresponding to a penetration rate of 97%. As the most dynamic segment in ICT, mobile communication is providing Internet services and consequently the mobile broadband penetration rate has reached 47% globally. Accordingly, capacity, throughput, reliability, service quality and resource availability of wireless services become essential factors for future mobile and wireless communications. Essentially, all these wireless technologies, standards, services and allocation policies rely on one common natural resource, i.e., radio spectrum. Radio spectrum spans over the electromagnetic frequencies between 3 kHz and 300 GHz. Existing radio spectrum access techniques are based on the fixed allocation of radio resources. These methods with fixed assigned bandwidth for exclusive usage of licensed users are often not efficient since most of the spectrum bands are under-utilized, either/both in the space domain or/and in the time domain. In reality, it is observed that many spectrum bands are largely un-occupied in many places [2], [3]. For instance, the spectrum bands which are exclusively allocated for TV broadcasting services in USA remain un-occupied from midnight to early morning according to the real-life measurement performed in [4]. In addition to the wastage of radio resources, spectrum under-utilization constraints spectrum availability for other intended users. Furthermore, legacy fixed spectrum allocation techniques are not capable of adapting to the changes and interactions in the system, leading to degraded network performance. Unlike in the static spectrum allocation, a fraction of the radio spectrum is allocated for open access as license-free bands, e.g., the industrial, scientific and medical (ISM) bands (902-928, 2400-2483.5, 5725-5850 MHz). In 1985, the federal communications commission (FCC) permitted to use the ISM bands for private and unlicensed occupancy, however, under certain restrictions on transmission power [5]. Consequently, standards like IEEE 802.11 for wireless local area networks (WLANs) and IEEE 802.15 for wireless personal area networks (WPAN) have grown rapidly with open access spectrum policies in the 2.4 GHz and 5 GHz ISM bands. With the co-existence of both similar and dissimilar radio technologies, 802.11 networks face challenges for providing satisfactory quality of service (QoS). This and the above mentioned spectrum under-utilization issues motivate the spectrum regulatory bodies to rethink about more flexible spectrum access for licenseexempt users or more efficient radio spectrum management. Cognitive radio (CR) is probably the most promising technology for achieving efficient spectrum utilization in future wireless networks

Dynamic Spectrum Reservation for CR Networks in the Presence of Channel Failures: Channel Allocation and Reliability Analysis

(c) 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this[EN] Providing channel access opportunities for new service requests and guaranteeing continuous connections for ongoing flows until service completion are two challenges for service provisioning in wireless networks. Channel failures, which are typically caused by hardware and software failures or/and by intrinsic instability in radio transmissions, can easily result in network performance degradation. In cognitive radio networks (CRNs), secondary transmissions are inherently vulnerable to connection breaks due to licensed users' arrivals as well as channel failures. To explore the advantages of channel reservation on performance improvement in error-prone channels, we propose and analyze a dynamic channel reservation (DCR) algorithm and a dynamic spectrum access (DSA) scheme with three access privilege variations. The key idea of the DCR algorithm is to reserve a dynamically adjustable number of channels for the interrupted services to maintain service retainability for ongoing users or to enhance channel availability for new users. Furthermore, the DCR algorithm is embedded in the DSA scheme enabling spectrum access of primary and secondary users with different access privileges based on access flexibility for licensed shared access. The performance of such a CRN in the presence of homogeneous and heterogeneous channel failures is investigated considering different channel failure and repair rates.The work of V. Pla was supported by the Spanish Ministry of Economy, Industry and Competitiveness under Grant TIN2013-47272-C2-1-R.Balapuwaduge, IAM.; Li, F.; Pla, V. (2018). Dynamic Spectrum Reservation for CR Networks in the Presence of Channel Failures: Channel Allocation and Reliability Analysis. IEEE Transactions on Wireless Communications. 17(2):882-898. https://doi.org/10.1109/TWC.2017.2772240S88289817

Propagation modelling and resource allocation in mobile radio communications

Over the past years, ray tracing (RT) models popularity has been increasing. From the nineties, RT has been used for field prediction in environment such as indoor and urban environments. Nevertheless, with the advent of new technologies, the channel model has become decidedly more dynamic and to perform RT simulations at each discrete time instant become computationally expensive. In this thesis, a new dynamic ray tracing (DRT) approach is presented in which from a single ray tracing simulation at an initial time t0, through analytical formulas we are able to track the motion of the interaction points. The benefits that this approach bring are that Doppler frequencies and channel prediction can be derived at every time instant, without recurring to multiple RT runs and therefore shortening the computation time. DRT performance was studied on two case studies and the results shows the accuracy and the computational gain that derives from this approach. Another issue that has been addressed in this thesis is the licensed band exhaustion of some frequency bands. To deal with this problem, a novel unselfish spectrum leasing scheme in cognitive radio networks (CRNs) is proposed that offers an energy-efficient solution minimizing the environmental impact of the network. In addition, a network management architecture is introduced and resource allocation is proposed as a constrained sum energy efficiency maximization problem. System simulations demonstrate an increment in the energy efficiency of the primary users’ network compared with previously proposed algorithms

Efficient Identification and Utilization of Spectrum Opportunities in Cognitive Radio Networks.

There has been an exponential increase in spectrum demands due to new emerging wireless services and applications, making it harder to find unallocated spectrum bands for future usage. This potential resource scarcity is rooted at inefficient utilization of spectrum under static spectrum allocation. Therefore, a new concept of dynamic spectrum access (DSA) has been proposed to opportunistically utilize the legacy spectrum bands by cognitive radio (CR) users. Cognitive radio is a key technology for alleviating this inefficient spectrum utilization, since it can help discover spectrum opportunities (or whitespaces) in which legacy spectrum users do not temporarily use their assigned spectrum bands. In a DSA network, it is crucial to efficiently identify and utilize the whitespaces. We address this issue by considering spectrum sensing and resource allocation. Spectrum sensing is to discover spectrum opportunities and to protect the legacy users (or incumbents) against harmful interference from the CR users. In particular, sensing is an interaction between PHY and MAC layers where in the PHY-layer signal detection is performed, and in the MAC-layer spectrum sensing is scheduled and spectrum sensors are coordinated for collaborative sensing. Specifically, we propose an efficient MAC-layer sensing scheduling algorithm that discovers spectrum opportunities as much as possible for better quality-of-service (QoS), and as fast as possible for seamless service provisioning. In addition, we propose an optimal in-band spectrum sensing algorithm to protect incumbents by achieving the detectability requirements set by regulators (e.g., FCC) while incurring minimal sensing overhead. For better utilization of discovered spectrum opportunities, we pay our attention to resource allocation in the secondary spectrum market where legacy license holders temporarily lease their own spectrum to secondary wireless service providers (WSPs) for opportunistic spectrum access by CR users. In this setting, we investigate how a secondary WSP can maximize its profit by optimally controlling the admission and eviction of its customers (i.e., CR users). In addition, we also focus on the price and quality competition between co-located WSPs where they contend for enticing customers by providing more competitive service fee while leasing the channels with best matching quality.Ph.D.Electrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/78741/1/hyoilkim_1.pd

Medium access control design for distributed opportunistic radio networks

Existing wireless networks are characterized by a fixed spectrum assignment policy. However, the scarcity of available spectrum and its inefficient usage demands for a new communication paradigm to exploit the existing spectrum opportunistically. Future Cognitive Radio (CR) devices should be able to sense unoccupied spectrum and will allow the deployment of real opportunistic networks. Still, traditional Physical (PHY) and Medium Access Control (MAC) protocols are not suitable for this new type of networks because they are optimized to operate over fixed assigned frequency bands. Therefore, novel PHY-MAC cross-layer protocols should be developed to cope with the specific features of opportunistic networks. This thesis is mainly focused on the design and evaluation of MAC protocols for Decentralized Cognitive Radio Networks (DCRNs). It starts with a characterization of the spectrum sensing framework based on the Energy-Based Sensing (EBS) technique considering multiple scenarios. Then, guided by the sensing results obtained by the aforementioned technique, we present two novel decentralized CR MAC schemes: the first one designed to operate in single-channel scenarios and the second one to be used in multichannel scenarios. Analytical models for the network goodput, packet service time and individual transmission probability are derived and used to compute the performance of both protocols. Simulation results assess the accuracy of the analytical models as well as the benefits of the proposed CR MAC schemes

Generalised Radio Resource Sharing Framework for Heterogeneous Radio Networks

Recent years have seen a significant interest in quantitative measurements of licensed and unlicensed spectrum use. Several research groups, companies and regulatory bodies have conducted studies of varying times and locations with the aim to capture the over- all utilisation rate of spectrum. The studies have shown that large amount of allocated spectrum are under-utilised, and create the so called \spectrum holes", resulting in a waste of valuable frequency resources. In order to satisfy the requirements of increased demands of spectrum resources and to improve spectrum utilisation, dynamic spectrum sharing (DSS) is proposed in the literature along with cognitive radio networks (CRNs). DSS and CRNs have been studied from many perspectives, for example spectrum sensing to identify the idle channels has been under the microscope to improve detection proba- bility. As well as spectrum sensing, the DSS performance analysis remains an important topic moving towards better spectrum utilisation to meet the exponential growth of traffi�c demand. In this dissertation we have studied both techniques to achieve different objectives such as enhancing the probability of detection and spectrum utilisation. In order to improve spectrum sensing decisions we have proposed a cooperative spec- trum sensing scheme which takes the propagation conditions into consideration. The proposed location aware scheme shows an improved performance over conventional hard combination scheme, highlighting the requirements of location awareness in cognitive radio networks (CRNs). Due to the exponentially growing wireless applications and services, traffi�c demand is increasing rapidly. To cope with such growth wireless network operators seek radio resource cooperation strategies for their users with the highest possible grade of service (GoS). However, it is diffi�cult to fathom the potential benefits of such cooperation, thus we propose a set of analytical models for DSS to analyse the blocking probability gain and degradation for operators. The thesis focuses on examining the performance gains that DSS can entail, in different scenarios. A number of dynamic spectrum sharing scenarios are proposed. The proposed models focus on measuring the blocking probability of secondary network operators as a trade-o� with a marginal increase of the blocking probability of a primary network in return of monetary rewards. We derived the global balance equation and an explicit expression of the blocking probability for each model. The robustness of the proposed analytical models is evaluated under different scenarios by considering varying tra�c intensities, different network sizes and adding reserved resources (or pooled capacity). The results show that the blocking probabilities can be reduced significantly with the proposed analytical DSS models in comparison to the existing local spectrum access schemes. In addition to the sharing models, we further assume that the secondary operator aims to borrow spectrum bandwidths from primary operators when more spectrum resources available for borrowing than the actual demand considering a merchant mode. Two optimisation models are proposed using stochastic optimisation models in which the secondary operator (i) spends the minimum amount of money to achieve the target GoS assuming an unrestricted budget or (ii) gains the maximum amount of pro�t to achieve the target GoS assuming restricted budget. Results obtained from each model are then compared with results derived from algorithms in which spectrum borrowings were random. Comparisons showed that the gain in the results obtained from our pro- posed stochastic optimisation model is significantly higher than heuristic counterparts. A post-optimisation performance analysis of the operators in the form of analysis of blocking probability in various scenarios is investigated to determine the probable per- formance gain and degradation of the secondary and primary operators respectively. We mathematically model the sharing agreement scenario and derive the closed form solution of blocking probabilities for each operator. Results show how the secondary and primary operators perform in terms of blocking probability under various offered loads and sharing capacity. The simulation results demonstrate that at most trading windows, the proposed opti- mal algorithms outperforms their heuristic counterparts. When we consider 80 cells, the proposed pro�t maximisation algorithm results in 33.3% gain in net pro�t to the secondary operators as well as facilitating 2.35% more resources than the heuristic ap- proach. In addition, the cost minimisation algorithm results in 46.34% gain over the heuristic algorithm when considering the same number of cells (80)