D5.2 - Evaluation of Selected Measurement-based Techniques

Deliverable D5.2 del projecte FARAMIRPreprin

A survey of machine learning techniques applied to self organizing cellular networks

In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future

Distributed spectrum leasing via cooperation

“Cognitive radio” networks enable the coexistence of primary (licensed) and secondary (unlicensed) terminals. Conventional frameworks, namely commons and property-rights models, while being promising in certain aspects, appear to have significant drawbacks for implementation of large-scale distributed cognitive radio networks, due to the technological and theoretical limits on the ability of secondary activity to perform effective spectrum sensing and on the stringent constraints on protocols and architectures. To address the problems highlighted above, the framework of distributed spectrum leasing via cross-layer cooperation (DiSC) has been recently proposed as a basic mechanism to guide the design of decentralized cognitive radio networks. According to this framework, each primary terminal can ”lease” a transmission opportunity to a local secondary terminal in exchange for cooperation (relaying) as long as secondary quality-of-service (QoS) requirements are satisfied. The dissertation starts by investigating the performance bounds from an information-theoretical standpoint by focusing on the scenario of a single primary user and multiple secondary users with private messages. Achievable rate regions are derived for discrete memoryless and Gaussian models by considering Decode-and-Forward (DF), with both standard and parity-forwarding techniques, and Compress-and-Forward (CF), along with superposition coding at the secondary nodes. Then a framework is proposed that extends the analysis to multiple primary users and multiple secondary users by leveraging the concept of Generalized Nash Equilibrium. Accordingly, multiple primary users, each owning its own spectral resource, compete for the cooperation of the available secondary users under a shared constraint on all spectrum leasing decisions set by the secondary QoS requirements. A general formulation of the problem is given and solutions are proposed with different signaling requirements among the primary users. The novel idea of interference forwarding as a mechanism to enable DiSC is proposed, whereby primary users lease part of their spectrum to the secondary users if the latter assist by forwarding information about the interference to enable interference mitigation at the primary receivers. Finally, an application of DiSC in multi-tier wireless networks such as femtocells overlaid by macrocells whereby the femtocell base station acts as a relay for the macrocell users is presented. The performance advantages of the proposed application are evaluated by studying the transmission reliability of macro and femto users for a quasi-static fading channel in terms of outage probability and diversity-multiplexing trade-off for uplink and, more briefly, for downlink