Beamformer Design with Smooth Constraint-Free Approximation in Downlink Cloud Radio Access Networks

It is known that data rates in standard cellular networks are limited due to inter-cell interference. An effective solution of this problem is to use the multi-cell cooperation idea. In Cloud Radio Access Network, which is a candidate solution in 5G and beyond, cooperation is applied by means of central processors (CPs) connected to simple remote radio heads with finite capacity fronthaul links. In this study, we consider a downlink scenario and aim to minimize total power spent by designing beamformers. We consider the case where perfect channel state information is not available in the CP. The original problem includes discontinuous terms with many constraints. We propose a novel method which transforms the problem into a smooth constraint-free form and a solution is found by the gradient descent approach. As a comparison, we consider the optimal method solving an extensive number of convex sub-problems, a known heuristic search algorithm and some sparse solution techniques. Heuristic search methods find a solution by solving a subset of all possible convex sub-problems. Sparse techniques apply some norm approximation ($\ell_0/\ell_1, \ell_0/\ell_2$) or convex approximation to make the objective function more tractable. We also derive a theoretical performance bound in order to observe how far the proposed method performs off the optimal method when running the optimal method is prohibitive due to computational complexity. Detailed simulations show that the performance of the proposed method is close to the optimal one, and it outperforms other methods analyzed.Comment: 18 pages, 12 figures, submitted to IEEE Access in Feb. 03, 2021. It is a revised version of the paper submitted to IEEE Access in Nov. 23, 2020. Revisions were made according to the reviewer comment

Designs for the Quality of Service Support in Low-Energy Wireless Sensor Network Protocols

A Wireless Sensor Network (WSN) consists of small, low cost, and low energy sensor nodes that cooperatively monitor physical quantities, control actuators, and perform data processing tasks. A network may consist of thousands of randomly deployed self-configurable nodes that operate autonomously to form a multihop topology. This Thesis focuses on Quality of Service (QoS) in low-energy WSNs that aim at several years operation time with small batteries. As a WSN may include both critical and non-critical control and monitoring applications, QoS is needed to make intelligent, content specific trade-offs between energy and network performance. The main research problem is defining and implementing QoS with constrained energy budget, processing power, communication bandwidth, and data and program memories. The problem is approached via protocol designs and algorithms. These are verified with simulations and with measurements in practical deployments. This Thesis defines QoS for WSNs with quantifiable metrics to allow measuring and managing the network performance. The definition is used as a basis for QoS routing protocol and Medium Access Control (MAC) schemes, comprising dynamic capacity allocation algorithm and QoS support layer. Dynamic capacity allocation is targeted at reservation based MACs, whereas the QoS support layer operates on contention based MACs. Instead of optimizing the protocols for a certain use case, the protocols allow configurable QoS based on application specific requirements. Finally, this Thesis designs sensor self-diagnostics and diagnostics analysis tool for verifying network performance. Compared to the related proposals on in-network sensor diagnostics, the diagnostics also detects performance problems and identifies reasons for the issues thus allowing the correction of problems. The results show that the developed protocols allow a clear trade-off between energy, latency, throughput, and reliability aspects of QoS while incurring a minimal overhead. The feasibility of results for extremely resource constrained WSNs is verified with the practical implementation with a prototype hardware platform having only few Million Instructions Per Second (MIPS) of processing power and less than a hundred kBs data and program memories. The results of this Thesis can be used in the WSN research, development, and implementation in general. The developed QoS definition, protocols, and diagnostics tools can be used separately or adapted to other applications and protocols

Enabling self organisation for future cellular networks.

The rapid growth in mobile communications due to the exponential demand for wireless access is causing the distribution and maintenance of cellular networks to become more complex, expensive and time consuming. Lately, extensive research and standardisation work has been focused on the novel paradigm of self-organising network (SON). SON is an automated technology that allows the planning, deployment, operation, optimisation and healing of the network to become faster and easier by reducing the human involvement in network operational tasks, while optimising the network coverage, capacity and quality of service. However, these SON autonomous features cannot be achieved with the current drive test coverage assessment approach due to its lack of automaticity which results in huge delays and cost. Minimization of drive test (MDT) has recently been standardized by 3GPP as a key self- organising network (SON) feature. MDT allows coverage to be estimated at the base station using user equipment (UE) measurement reports with the objective to eliminate the need for drive tests. However, most MDT based coverage estimation methods recently proposed in literature assume that UE position is known at the base station with 100% accuracy, an assumption that does not hold in reality. In this work, we develop a novel and accurate analytical model that allows the quantification of error in MDT based autonomous coverage estimation (ACE) as a function of error in UE as well as base station (user deployed cell) positioning. We first consider a circular cell with an omnidirectional antenna and then we use a three-sectored cell and see how the system is going to be affected by the UE and the base station (user deployed cell) geographical location information errors. Our model also allows characterization of error in ACE as function of standard deviation of shadowing in addition to the path-loss