Achieving Max-Min Throughput in LoRa Networks

With growing popularity, LoRa networks are pivotally enabling Long Range connectivity to low-cost and power-constrained user equipments (UEs). Due to its wide coverage area, a critical issue is to effectively allocate wireless resources to support potentially massive UEs in the cell while resolving the prominent near-far fairness problem for cell-edge UEs, which is challenging to address due to the lack of tractable analytical model for the LoRa network and its practical requirement for low-complexity and low-overhead design. To achieve massive connectivity with fairness, we investigate the problem of maximizing the minimum throughput of all UEs in the LoRa network, by jointly designing high-level policies of spreading factor (SF) allocation, power control, and duty cycle adjustment based only on average channel statistics and spatial UE distribution. By leveraging on the Poisson rain model along with tailored modifications to our considered LoRa network, we are able to account for channel fading, aggregate interference and accurate packet overlapping, and still obtain a tractable and yet accurate closed-form formula for the packet success probability and hence throughput. We further propose an iterative balancing (IB) method to allocate the SFs in the cell such that the overall max-min throughput can be achieved within the considered time period and cell area. Numerical results show that the proposed scheme with optimized design greatly alleviates the near-far fairness issue, and significantly improves the cell-edge throughput.Comment: 6 pages, 4 figures, published in Proc. International Conference on Computing, Networking and Communications (ICNC), 2020. This paper proposes stochastic-geometry based analytical framework for a single-cell LoRa network, with joint optimization to achieve max-min throughput for the users. Extended journal version for large-scale multi-cell LoRa network: arXiv:2008.0743

Intelligent Control of a Distributed Energy Generation System Based on Renewable Sources

The control of low power systems, which include renewable energy sources, a local network, an electrochemical storage subsystem and a grid connection, is inherently hierarchical. The lower level consists of the wind energy sources (power limitation at rated value in full load regime and energy optimization in partial load regime) and photovoltaic (energy conversion optimization) control systems. The present paper deals with control problem at the higher level and aims at generating the control solution for the energetic transfer between the system components, given that the powers of the renewable energy sources and the power in the local network have random characteristics. For the higher level, the paper proposes a mixed performance criterion, which includes an energy sub-criterion concerning the costs of electricity supplied to local consumers, and a sub-criterion related to the lifetime of the battery. Three variants were defined for the control algorithm implemented by using fuzzy logic techniques, in order to control the energy transfer in the system. Particular attention was given to developing the models used for the simulation of the distributed energy system components and to the whole control system, given that the objective is not the real-time optimization of the criterion, but to establish by numerical simulation in the design stage the "proper" parameters of the control system. This is done by taking into account the multi-criteria performance objective when the power of renewable energy sources and the load have random characteristics

Study on the optimized control strategy of the DAB converter

Due to the rapid development of DC power generation and transmission technology, it has become the central link of high voltage AC transmission and low voltage DC distribution network, and the medium and low voltage DC distribution network has attracted more attention. In the medium and low voltage DC distribution network, the high-frequency isolation bidirectional DCDC-driven converter is required as an interconnection equipment for electrical isolation, current conversion and bidirectional power flow. To reduce the voltage stress of the switching element of the dual active bridge (DAB) autoconverter used in the medium voltage environment, the three-level topology is incorporated into the autoconverter of the audio broadcast. The three-input-output level (3L) DAB converter has the advantages of both input-output level automatic converter and DAB converter, which is more convenient to operate and has great application and development prospects. For the 3L-DAB converter and its optimal management, taking the double-free-phase-shift controller as an example, it first constructs the segmented time-domain map mode of the automatic converter, and analyzes its operation characteristics, which provides a basis for the subsequent research. The power switching transistors of the two-channel free phase-shift timing converter meet the soft switching requirements, and we deduce the influence of the nonlinear influence on the soft switching range. Then, the reliability optimization strategy is given in view of the non-matching conditions, and then the equivalent conditions of the two optimization methods are derived. Finally, we analyze that the segmented time domain mapping method is not suitable for the model changes, construct the multi-degree of freedom universal phase shift controller mode, and derive the fundamental wave optimization game

Energy Efficient, Cooperative Communication in Low-Power Wireless Networks

The increased interest in massive deployment of wireless sensors and network densification requires more innovation in low-latency communication across multi-hop networks. Moreover, the resource constrained nature of sensor nodes calls for more energy efficient transmission protocols, in order to increase the battery life of said devices. Therefore, it is important to investigate possible technologies that would aid in improving energy efficiency and decreasing latency in wireless sensor networks (WSN) while focusing on application specific requirements. To this end, and based on state of the art Glossy, a low-power WSN flooding protocol, this dissertation introduces two energy efficient, cooperative transmission schemes for low-power communication in WSNs, with the aim of achieving performance gains in energy efficiency, latency and power consumption. These approaches apply several cooperative transmission technologies such as physical layer network coding and transmit beamforming. Moreover, mathematical tools such as convex optimization and game theory are used in order to analytically construct the proposed schemes. Then, system level simulations are performed, where the proposed schemes are evaluated based on different criteria. First, in order to improve over all latency in the network as well as energy efficiency, MF-Glossy is proposed; a communication scheme that enables the simultaneous flooding of different packets from multiple sources to all nodes in the network. Using a communication-theoretic analysis, upper bounds on the performance of Glossy and MF-Glossy are determined. Further, simulation results show that MF-Glossy has the potential to achieve several-fold improvements in goodput and latency across a wide spectrum of network configurations at lower energy costs and comparable packet reception rates. Hardware implementation challenges are discussed as a step towards harnessing the potential of MF-Glossy in real networks, while focusing on key challenges and possible solutions. Second, under the assumption of available channel state information (CSI) at all nodes, centralized and distributed beamforming and power control algorithms are proposed and their performance is evaluated. They are compared in terms of energy efficiency to standard Glossy. Numerical simulations demonstrate that a centralized power control scheme can achieve several-fold improvements in energy efficiency over Glossy across a wide spectrum of network configurations at comparable packet reception rates. Furthermore, the more realistic scenario where CSI is not available at transmitting nodes is considered. To battle CSI unavailability, cooperation is introduced on two stages. First, cooperation between receiving and transmitting nodes is proposed for the process of CSI acquisition, where the receivers provide the transmitters with quantized (e.g. imperfect) CSI. Then, cooperation within transmitting nodes is proposed for the process of multi-cast transmit beamforming. In addition to an analytical formulation of the robust multi-cast beamforming problem with imperfect CSI, its performance is evaluated, in terms of energy efficiency, through numerical simulations. It is shown that the level of cooperation, represented by the number of limited feedback bits from receivers to transmitters, greatly impacts energy efficiency. To this end, the optimization problem of finding the optimal number of feedback bits B is formulated, as a programming problem, under QoS constraints of 5% maximum outage. Numerical simulations show that there exists an optimal number of feedback bits that maximizes energy efficiency. Finally, the effect of choosing cooperating transmitters on energy efficiency is studied, where it is shown that an optimum group of cooperating transmit nodes, also known as a transmit coalition, can be formed in order to maximize energy efficiency. The investigated techniques including optimum feedback bits and transmit coalition formation can achieve a 100% increase in energy efficiency when compared to state of the art Glossy under same operation requirements in very dense networks. In summary, the two main contributions in this dissertation provide insights on the possible performance gains that can be achieved when cooperative technologies are used in low-power wireless networks

Analyzing Energy-efficiency and Route-selection of Multi-level Hierarchal Routing Protocols in WSNs

The advent and development in the field of Wireless Sensor Networks (WSNs) in recent years has seen the growth of extremely small and low-cost sensors that possess sensing, signal processing and wireless communication capabilities. These sensors can be expended at a much lower cost and are capable of detecting conditions such as temperature, sound, security or any other system. A good protocol design should be able to scale well both in energy heterogeneous and homogeneous environment, meet the demands of different application scenarios and guarantee reliability. On this basis, we have compared six different protocols of different scenarios which are presenting their own schemes of energy minimizing, clustering and route selection in order to have more effective communication. This research is motivated to have an insight that which of the under consideration protocols suit well in which application and can be a guide-line for the design of a more robust and efficient protocol. MATLAB simulations are performed to analyze and compare the performance of LEACH, multi-level hierarchal LEACH and multihop LEACH.Comment: NGWMN with 7th IEEE Inter- national Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA 2012), Victoria, Canada, 201

Electric Power System Operations with a Variable Series Reactor

Series FACTS devices, such as a Variable Series Reactor (VSR), have the ability to continuously regulate the transmission line reactance so as to control power ow. This research work evaluates the benefits brought by VSRs in different aspects of power system and develops efficient planning models and algorithms to provide optimal investment plan for the VSRs. First, an optimization approach capable of finding both optimal locations and settings of VSRs under a specific operating condition is developed. The tool implements a full ac model as well as detailed models for different power system components. Second, an optimization tool which can optimally allocate VSRs to improve the load margin in a transmission network considering a multi-scenario framework including base case and some critical contingencies is proposed. Starting from a mixed integer nonlinear programming (MINLP) model, a reformulation technique is leveraged to transform the MINLP model into a mixed integer linear programming (MILP) model so that it is computationally tractable for large scale power systems. Detailed numerical simulations on the practical Northwest US power network demonstrate the proposed technique and the capability of VSRs. Third, the VSR is introduced in the Transmission Expansion Planning (TEP) problem. A security constrained multi-stage TEP with the VSR is formulated as an MILP model. To reduce the computational burden for a practical large scale system, a decomposition approach is proposed. Simulation results demonstrate the effectiveness of the proposed approach and show that the appropriately allocated VSRs allow reduced planning costs. Fourth, in order to investigate the economic benefits brought by VSR in contingencies, a planning model to allocate VSR considering different operating conditions and the N - 1 contingencies is formulated. We consider a single target year planning. Three distinct load patterns which represent peak, normal and low load level are selected to accommodate the yearly load profile. The transmission contingencies can occur in any of the three load conditions. A two phase Benders decomposition is proposed to solved the large scale MILP model. Simulation results on the IEEE-118 bus system and the practical Polish system establish the efficient performance of the proposed algorithm