HARD HANDOVER OPTIMIZATION USING TIME WINDOW BASED HANDOVER ALGORITHM

ABSTRACT This paper shows and solves a handover problem occurring with current power control mechanisms in cochannel Wideband Code Division Multiple Access (WCDMA) heterogeneous networks. The problem is the mismatch between the required uplink transmits power when a user is communicating to a small cell and an underlying microcellular base-station. This paper introduces Time Window Handover (TWHO) algorithm to adapt the transmit power of the small cell users during the handover regime to prevent such Signal to Interference plus Noise Ratio (SINR) drops

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

Resource Allocation for Coordinated Multipoint Joint Transmission System and Received Signal Strength Based Positioning in Long Term Evolution Network

The Long-Term Evolution Advanced (LTE-A) system are expected to provide high speed and high quality services, which are supported by emerging technologies such as Coordinated Multipoint (CoMP) transmission and reception. Dynamic resource allocation plays a vital role in LTE-A design and planning, which is investigated in this thesis. In addition, Received Signal Strength (RSS) based positioning is also investigated in orthogonal frequency division multiplexing (OFDM) based wireless networks, which is based on an industry project. In the first contribution, a physical resource blocks (PRB) allocation scheme with fuzzy logic based user selection is proposed. This work considers three parameters and exploit a fuzzy logic (FL) based criterion to categorize users. As a result, it enhances accuracy of user classification. This work improves system capacity by a ranking based PRBs allocation schemes. Simulation results show that proposed fuzzy logic based user selection scheme improves performance for CoMP users. Proposed ranking based greedy allocation algorithm cut complexity in half but maintain same performance. In the second contribution, a two-layer proportional-fair (PF) user scheduling scheme is proposed. This work focused on fairness between CoMP and Non-CoMP users instead of balancing fairness in each user categories. Proposed scheme jointly optimizes fairness and system capacity over both CoMP and Non-CoMP users. Simulation results show that proposed algorithm significantly improves fairness between CoMP and Non-CoMP users. In the last contribution, RSS measurement method in LTE system is analyzed and a realizable RSS measurement method is proposed to fight against multipath effect. Simulation results shows that proposed method significantly reduced measurement error caused by multipath. In RSS based positioning area, this is the first work that consider exploiting LTE’s own signal strength measurement mechanism to enhance accuracy of positioning. Furthermore, the proposed method can be deployed in modern LTE system with limited cost

HANDOVER PARAMETER OPTIMIZATION IN WCDMA USING FUZZY CONTROLLING

The increasing traffic and the demand for high data rate services in WCDMA networks prompt the need for an automatic network optimization. Current state–of–the–art optimization methods adapt physical parameters, such as the antennas ’ tilt or azimuth. As agreed in the community, a further capacity increase can be achieved by an optimization of Radio Resource Management (RRM) parameters. While theoretical approaches of RRM parameter optimization have already been introduced in the literature, practical solutions optimizing cell individual parameters have rarely been treated so far. Consequently, this paper copes with the optimization of the cell individual offset (CIO) in the soft handover algorithm with the goal to reduce the network’s outage probabiliy. We design and apply a fuzzy logic controller, whose output are CIO changes matching the current traffic and load conditions. Verifications using a dynamic system simulator prove the powerfulness of our method and promise significant outage reductions in a fully loaded network scenario leading to capacity improvements of up to 9%