A Collection of Constraint Programming Models for the Three-Dimensional Stable Matching Problem with Cyclic Preferences

We introduce five constraint models for the 3-dimensional stable matching problem with cyclic preferences and study their relative performances under diverse configurations. While several constraint models have been proposed for variants of the two-dimensional stable matching problem, we are the first to present constraint models for a higher number of dimensions. We show for all five models how to capture two different stability notions, namely weak and strong stability. Additionally, we translate some well-known fairness notions (i.e. sex-equal, minimum regret, egalitarian) into 3-dimensional matchings, and present how to capture them in each model. Our tests cover dozens of problem sizes and four different instance generation methods. We explore two levels of commitment in our models: one where we have an individual variable for each agent (individual commitment), and another one where the determination of a variable involves pairing the three agents at once (group commitment). Our experiments show that the suitability of the commitment depends on the type of stability we are dealing with. Our experiments not only led us to discover dependencies between the type of stability and the instance generation method, but also brought light to the role that learning and restarts can play in solving this kind of problems

Matching Theory Framework for 5G Wireless Communications

The prevalence of high-performance mobile devices such as smartphones and tablets has brought fundamental changes to the existing wireless networks. The growth of multimedia and location-based mobile services has exponentially increased the network congestion and the demands for more wireless resources. The extremely high computational complexity and communication overhead resulting from the conventional centralized resource management methods are no longer suitable to capture the scale of tomorrow’s wireless networks. As a result, the resource management in next-generation networks is shifting from the centralized optimization to the self-organizing solutions. The goal of this thesis is to demonstrate the effectiveness of matching theory, a powerful operational research framework, for solving the wireless resource allocation problems in a distributed manner. Matching theory, as a Nobel-prize winning framework, has already been widely used in many economic fields. More recently, matching theory has been shown to have a promising potential for modeling and analyzing wireless resource allocation problems due to three reasons: (1) it offers suitable models that can inherently capture various wireless communication features; (2) the ability to use notions, such as preference relations, that can interpret complex system requirements; (3) it provides low-complexity and near-optimal matching algorithms while guaranteeing the system stability. This dissertation provides a theoretical research of implementing the matching theory into the wireless communication fields. The main contributions of this dissertation are summarized as follows. An overview of the basic concepts, classifications, and models of the matching theory is provided. Furthermore, comparisons with existing mathematical solutions for the resource allocation problems in the wireless networks are conducted. Applications of matching theory in the wireless communications are studied. Especially, the stable marriage model, the student project allocation model and so on are introduced and applied to solve the resource allocation problems, such as the device-to-device (D2D) communication, LTE-Unlicensed, and so on. Both theoretical and numerical analysis are provided to show that matching theory can model complex system requirements, and also provide semi-distributive matching algorithms to achieve stable and close-optimal results. The potential and challenges of the matching theory for designing resource allocation mechanisms in the future wireless networks are discussed.Electrical and Computer Engineering, Department o

Constrainedness in stable matching

In constraint satisfaction problems, constrainedness provides a way to predict the number of solutions: for instances of a same size, the number of constraints is inversely correlated with the number of solutions. However, there is no obvious equivalent metric for stable matching problems. We introduce the contrarian score, a simple metric that is to matching problems what constrainedness is to constraint satisfaction problems. In addition to comparing the contrarian score against other potential tightness metrics, we test it for different instance sizes as well as extremely distinct versions of the stable matching problem. In all cases, we find that the correlation between contrarian score and number of solutions is very strong

Detection of OFDM Signals Using Pilot Tones and Applications to Spectrum Sensing for Cognitive Radio Systems

Nowadays there are an increasing number of wireless devices which support wireless networking and the need for higher data rate communication is increasing rabidly. As more and more systems go wireless, approaching technologies will face spectral crowding and existence of wireless devices will be an important issue. Because of the limited bandwidth availability, accepting the request for higher capacity and data rates is a challenging task, demanding advanced technologies that can offers new methods of using the available radio spectrum. Cognitive radio introduces a key solution to the spectral increasing issue by presenting the opportunistic usage of spectrum that is not heavily occupied by licensed users. It is a latest idea in wireless communications systems which objective to have more adaptive and aware communication devices which can make better use of available natural resources. Cognitive radio appears to be an attractive solution to the spectral congestion problem by introducing the notion of opportunistic spectrum use. Cognitive radios can operate as a secondary systems on top of existence system which are called primary (or licensed) systems. In this case, secondary (cognitive) users need to detect the unused spectrum in order to be able to access it. Because of its many advantages, orthogonal frequency division multiplexing (OFDM) has been successfully used in numerous wireless standards and technologies. It\u27s shown that OFDM will play an important role in realizing the cognitive radio concept as well by providing a proven, scalable, and adaptive technology for air interface. Researches show that OFDM technique is considered as a candidate for cognitive radio systems. The objective of this dissertation is to explore detecting of OFDM modulated signals using pilot tones information. Specifically we applying Time-Domain Symbol Cross-Correlation (TDSC) method in the confect of actual 4G wireless standards such as WIMAX and LTE. This detection is only based upon the knowledge of pilot structures without knowledge of received signal so that, it can be performed on every portion of the received signal. The approach induces Cross-Correlation between pilots subcarriers and exploits the deterministic and periodic characteristics of pilot mapping in the time frequency domain

On Dependable Wireless Communications through Multi-Connectivity

The realization of wireless ultra-reliable low-latency communications (URLLC) is one of the key challenges of the fifth generation (5G) of mobile communications systems and beyond. Ensuring ultra-high reliability together with a latency in the (sub-)millisecond range is expected to enable self-driving cars, wireless factory automation, and the Tactile Internet. In wireless communications, reliability is usually only considered as percentage of successful packet delivery, aiming for 1 − 10⁻⁵ up to 1 − 10⁻⁹ in URLLC