Opportunistic Routing with Network Coding in Powerline Communications

Opportunistic Routing (OR) can be used as an alternative to the legacy routing (LR) protocols in networks with a broadcast lossy channel and possibility of overhearing the signal. The power line medium creates such an environment. OR can better exploit the channel than LR because it allows the cooperation of all nodes that receive any data. With LR, only a chain of nodes is selected for communication. Other nodes drop the received information. We investigate OR for the one-source one-destination scenario with one traffic flow. First, we evaluate the upper bound on the achievable data rate and advocate the decentralized algorithm for its calculation. This knowledge is used in the design of Basic Routing Rules (BRR). They use the link quality metric that equals the upper bound on the achievable data rate between the given node and the destination. We call it the node priority. It considers the possibility of multi-path communication and the packet loss correlation. BRR allows achieving the optimal data rate pertaining certain theoretical assumptions. The Extended BRR (BRR-E) are free of them. The major difference between BRR and BRR-E lies in the usage of Network Coding (NC) for prognosis of the feedback. In this way, the protocol overhead can be severely reduced. We also study Automatic Repeat-reQuest (ARQ) mechanism that is applicable with OR. It differs to ARQ with LR in that each sender has several sinks and none of the sinks except destination require the full recovery of the original message. Using BRR-E, ARQ and other services like network initialization and link state control, we design the Advanced Network Coding based Opportunistic Routing protocol (ANChOR). With the analytic and simulation results we demonstrate the near optimum performance of ANChOR. For the triangular topology, the achievable data rate is just 2% away from the theoretical maximum and it is up to 90% higher than it is possible to achieve with LR. Using the G.hn standard, we also show the full protocol stack simulation results (including IP/UDP and realistic channel model). In this simulation we revealed that the gain of OR to LR can be even more increased by reducing the head-of-the-line problem in ARQ. Even considering the ANChOR overhead through additional headers and feedbacks, it outperforms the original G.hn setup in data rate up to 40% and in latency up to 60%.:1 Introduction 2 1.1 Intra-flow Network Coding 6 1.2 Random Linear Network Coding (RLNC) 7 2 Performance Limits of Routing Protocols in PowerLine Communications (PLC) 13 2.1 System model 14 2.2 Channel model 14 2.3 Upper bound on the achievable data rate 16 2.4 Achieving the upper bound data rate 17 2.5 Potential gain of Opportunistic Routing Protocol (ORP) over Common Single-path Routing Protocol (CSPR) 19 2.6 Evaluation of ORP potential 19 3 Opportunistic Routing: Realizations and Challenges 24 3.1 Vertex priority and cooperation group 26 3.2 Transmission policy in idealized network 34 3.2.1 Basic Routing Rules (BRR) 36 3.3 Transmission policy in real network 40 3.3.1 Purpose of Network Coding (NC) in ORP 41 3.3.2 Extended Basic Routing Rules (BRR) (BRR-E) 43 3.4 Automatic ReQuest reply (ARQ) 50 3.4.1 Retransmission request message contents 51 3.4.2 Retransmission Request (RR) origination and forwarding 66 3.4.3 Retransmission response 67 3.5 Congestion control 68 3.5.1 Congestion control in our work 70 3.6 Network initialization 74 3.7 Formation of the cooperation groups (coalitions) 76 3.8 Advanced Network Coding based Opportunistic Routing protocol (ANChOR) header 77 3.9 Communication of protocol information 77 3.10 ANChOR simulation . .79 3.10.1 ANChOR information in real time .80 3.10.2 Selection of the coding rate 87 3.10.3 Routing Protocol Information (RPI) broadcasting frequency 89 3.10.4 RR contents 91 3.10.5 Selection of RR forwarder 92 3.10.6 ANChOR stability 92 3.11 Summary 95 4 ANChOR in the Gigabit Home Network (G.hn) Protocol 97 4.1 Compatibility with the PLC protocol stack 99 4.2 Channel and noise model 101 4.2.1 In-home scenario 102 4.2.2 Access network scenario 102 4.3 Physical layer (PHY) layer implementation 102 4.3.1 Bit Allocation Algorithm (BAA) 103 4.4 Multiple Access Control layer (MAC) layer 109 4.5 Logical Link Control layer (LLC) layer 111 4.5.1 Reference Automatic Repeat reQuest (ARQ) 111 4.5.2 Hybrid Automatic Repeat reQuest (HARQ) in ANChOR 114 4.5.3 Modeling Protocol Data Unit (PDU) erasures on LLC 116 4.6 Summary 117 5 Study of G.hn with ANChOR 119 5.1 ARQ analysis 119 5.2 Medium and PHY requirements for “good” cooperation 125 5.3 Access network scenario 128 5.4 In-home scenario 135 5.4.1 Modeling packet erasures 136 5.4.2 Linear Dependence Ratio (LDR) 139 5.4.3 Worst case scenario 143 5.4.4 Analysis of in-home topologies 145 6 Conclusions . . . . . . . . . . . . . . . 154 A Proof of the neccessity of the exclusion rule 160 B Gain of ORPs to CSRPs 163 C Broadcasting rule 165 D Proof of optimality of BRR for triangular topology 167 E Reducing the retransmission probability 168 F Calculation of Expected Average number of transmissions (EAX) for topologies with bi-directional links 170 G Feedback overhead of full coding matrices 174 H Block diagram of G.hn physical layer in ns-3 model 175 I PER to BER mapping 17

Amplitude quantization method for autonomous threshold estimation in self-reconfigurable cognitive radio systems

Self-adaptive threshold adjustment algorithms (SATAs) are required to reconfigure their parameters autonomously (i.e. to achieve self-parameter adjustment) at runtime and during online use for effective signal detection in cognitive radio (CR) applications. In this regard, a CR system embedded with the functionality of a SATA is termed a self-reconfigurable CR system. However, SATAs are challenging to develop owing to a lack of methods for self-parameter adjustment. Thus, a plausible approach towards realizing a functional SATA may involve developing effective non-parametric methods, which are often pliable to achieve self-parameter adjustment since they are distribution-free methods. In this article, we introduce such a method termed the non-parametric amplitude quantization method (NPAQM) designed to improve primary user signal detection in CR without requiring its parameters to be manually fine-tuned. The NPAQM works by quantizing the amplitude of an input signal and then evaluating each quantized value based on the principle of discriminant analysis. Then, the algorithm searches for an effective threshold value that maximally separates noise from signal elements in the input signal sample. Further, we propose a new heuristic, which is an algorithm designed based on a new corollary derived from the Otsu’s algorithm towards improving the NPAQM’s performance under noise-only regimes. We applied our method to the case of the energy detector and compared the NPAQM with other autonomous methods. We show that the NPAQM provides improved performance as against known methods, particularly in terms of maintaining a low probability of false alarm under different test conditions.http://www.elsevier.com/locate/phycomhj2022Electrical, Electronic and Computer Engineerin

A cuckoo search optimization-based forward consecutive mean excision model for threshold adaptation in cognitive radio

The forward consecutive mean excision (FCME) algorithm is one of the most effective adaptive threshold estimation algorithms presently deployed for threshold adaptation in cognitive radio (CR) systems. However, its effectiveness is often limited by the manual parameter tuning process and by the lack of prior knowledge pertaining to the actual noise distribution considered during the parameter modeling process of the algorithm. In this paper, we propose a new model that can automatically and accurately tune the parameters of the FCME algorithm based on a novel integration with the cuckoo search optimization (CSO) algorithm. Our model uses the between-class variance function of the Otsu’s algorithm as the objective function in the CSO algorithm in order to auto-tune the parameters of the FCME algorithm. We compared and selected the CSO algorithm based on its relatively better timing and accuracy performance compared to some other notable metaheuristics such as the particle swarm optimization, artificial bee colony (ABC), genetic algorithm, and the differential evolution (DE) algorithms. Following close performance values, our findings suggest that both the DE and ABC algorithms can be adopted as favorable substitutes for the CSO algorithm in our model. Further simulation results show that our model achieves reasonably lower probability of false alarm and higher probability of detection as compared to the baseline FCME algorithm under different noise-only and signal-plus-noise conditions. In addition, we compared our model with some other known autonomous methods with results demonstrating improved performance. Thus, based on our new model, users are relieved from the cumbersome process involved in manually tuning the parameters of the FCME algorithm; instead, this can be done accurately and automatically for the user by our model. Essentially, our model presents a fully blind signal detection system for use in CR and a generic platform deployable to convert other parameterized adaptive threshold algorithms into fully autonomous algorithms.http://link.springer.com/journal/5002020-11-03hj2020Electrical, Electronic and Computer Engineerin

PNT cyber resilience : a Lab2Live observer based approach, Report 1 : GNSS resilience and identified vulnerabilities. Technical Report 1

The use of global navigation satellite systems (GNSS) such as GPS and Galileo are vital sources of positioning, navigation and timing (PNT) information for vehicles. This information is of critical importance for connected autonomous vehicles (CAVs) due to their dependence on this information for localisation, route planning and situational awareness. A downside to solely relying on GNSS for PNT is that the signal strength arriving from navigation satellites in space is weak and currently there is no authentication included in the civilian GNSS adopted in the automotive industry. This means that cyber-attacks against the GNSS signal via jamming or spoofing are attractive to adversaries due to the potentially high impact they can achieve. This report reviews the vulnerabilities of GNSS services for CAVs (a summary is shown in Figure 1), as well as detection and mitigating techniques, summarises the opinions on PNT cyber testing sourced from a select group of experts, and finishes with a description of the associated lab-based and real-world feasibility study and proposed research methodology