Neural networks

Fundamentals Of Neural Networks Architectures Algorithms And Applications

The underwater path planning problem deals with finding an optimal or sub-optimal route between an origin point and a termination point in marine environments. The underwater environment is still considered as a great challenge for the path planning of autonomous underwater vehicles (AUVs) because of its hostile and dynamic nature. The major constraints for path planning are limited data transmission capability, power and sensing technology available for underwater operations. The sea environment is subjected to a large set of challenging factors classified as atmospheric, coastal and gravitational. Based on whether the impact of these factors can be approximated or not, the underwater environment can be characterized as predictable and unpredictable respectively. The classical path planning algorithms based on artificial intelligence assume that environmental conditions are known apriori to the path planner. But the current path planning algorithms involve continual interaction with the environment considering the environment as dynamic and its effect cannot be predicted. Path planning is necessary for many applications involving AUVs. These are based upon planning safety routes with minimum energy cost and computation overheads. This review is intended to summarize various path planning strategies for AUVs on the basis of characterization of underwater environments as predictable and unpredictable. The algorithms employed in path planning of single AUV and multiple AUVs are reviewed in the light of predictable and unpredictable environments.

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A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater Vehicles

Orthogonal frequency division multiplexing (OFDM) is a modulation technique which is now used in most new and emerging broadband wired and wireless communication systems because it is an effective solution to intersymbol interference caused by a dispersive channel. Very recently a number of researchers have shown that OFDM is also a promising technology for optical communications. This paper gives a tutorial overview of OFDM highlighting the aspects that are likely to be important in optical applications. To achieve good performance in optical systems OFDM must be adapted in various ways. The constraints imposed by single mode optical fiber, multimode optical fiber and optical wireless are discussed and the new forms of optical OFDM which have been developed are outlined. The main drawbacks of OFDM are its high peak to average power ratio and its sensitivity to phase noise and frequency offset. The impairments that these cause are described and their implications for optical systems discussed.

OFDM for Optical Communications

Internet of Things (IoT) expansion led the market to find alternative communication technologies since existing protocols are insufficient in terms of coverage, energy consumption to fit IoT needs. Low Power Wide Area Networks (LPWAN) emerged as an alternative cost-effective communication technology for the IoT market. LoRaWAN is an open LPWAN standard developed by LoRa Alliance and has key features i.e., low energy consumption, long-range communication, builtin security, GPS-free positioning. In this paper, we will introduce LoRaWAN technology, the state of art studies in the literature and provide open opportunities.

A Survey on LoRaWAN Architecture, Protocol and Technologies

The network functionaries incorporate and core networks aim to provide 99.999% reliability to their networks. The most preferred way to achieve this is to provide dynamic routing to the network. If the router gateway is disrupted by port failure, network administrator should manually configure the route in which packets are being forwarded. By using Hot Stand Routing Protocol (HSRP), it simultaneously adapts new route, which provides redundancy to the network with reduced packet loss. In this paper, our aim is to calculate the difference in number of packets lost when router with gateway is disrupted in the network by combining HSRP with Open Shortest Path First (OSPF) protocol. By using this combined technique, we can reduce the packet loss to maximum extent thereby increasing the reliability. The simulation results provide best route when HSRP is combined with OSPF than the existing technique without HSRP.

Performance Analysis of HSRP in Provisioning Layer-3 Gateway Redundancy for Corporate Networks

Design of near‐optimal local likelihood search‐based detection algorithm for coded large‐scale MU‐MIMO system

It is an arduous and indolent process to switch to IPv6 technology from the existing IPv4. This paper aims at providing a lucid performance analysis of key techniques used in IPv4 to IPv6 transition. Sustainable and real time topologies are built for each of the three robust techniques, namely, dual stack, tunneling, and network address translation. These implementations are done in an open source Network simulator GNS3 (1.3.13), a wide compatible and realistic simulator. All the topologies are analyzed for latency, efficiency and throughput using wire shark packet analyzer. Networks are built using different commercially used cisco 7200, 3600 and 3700 series routers and used serial and fast ethernet cables for connecting the nodes. All topologies are configured as private, to analyze each technique performance at their maximum potential. This analysis can be found useful in employing the right transition technique depending on the network scenario used as it weigh the advantage and limitation for each technique. The analysis depicts the competence of tunneling for its highest latency comparatively. Among the three methods, Dual Stack displays 100% efficiency in communicating within the network. Network address translation show 94% efficiency as it plays an important role when IPv4 only needs to communicate with IPv6 nodes. In most cases, IPv6 show better performance than IPv4, which lucidly explains the potential of IPv6. The analysis can further be extended to hardware implementation by constructing large topologies and with various other sophisticated routers produced by different vendors.

Performance Analysis of IPv4 to IPv6 Transition Methods

Massive Multi-user Multiple Input Multiple Output (MU‒MIMO) system is aimed to improve throughput and spectral efficiency in 5G communication networks. Interantenna Interference (IAI) and Multi-user Interference (MUI) are two major factors that influence the performance of MU– MIMO system. IAI arises due to closely spaced multiple antennas at each User Terminal (UT), whereas MUI is generated when one UT comes in the vicinity of another UT of the same cellular network. IAI can be mitigated by the use of a pre-coding scheme such as Singular Value Decomposition (SVD) and MUI can be cancelled through efficient Multi-user Detection (MUD) schemes. The highly complex and optimal Maximum Likelihood (ML) detector involves a large number of computations, especially when in massive structures. Therefore, the local search-based algorithm such as Likelihood Ascent Search (LAS) has been found to be a better alternative for mitigation of MUI, as it results in near optimal performance using lesser number of matrix computations. Most of the literature have been aimed at mitigating either IAI or MUI, whereas the proposed work presents SVD pre-coding and LAS MUD to mitigate both IAI and MUI. Simulation results indicate that the proposed scheme can attain near-optimal bit error rate (BER) performance with fewer computations. 

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Design of Massive Multiuser MIMO System to Mitigate Inter Antenna Interference and Multiuser Interference in 5G Wireless Networks

Localization or positioning of wireless sensor nodes is an essential task for a wide range of applications in wireless sensor networks-based fifth generation (5G) networks. Node localization using mobile aerial beacon nodes (MABNs) provides high localization accuracy and less deployment cost compared to the localization using fixed ground beacon nodes because MABN deployed in unmanned aerial vehicles sends signals to unknown nodes (UNs) through reliable air to ground (AG) channel link. The classical received signal strength indicator (RSSI)-based multilateration and optimization-based least square localization (OLSL) schemes result high localization error because of the nonlinear distortions induced in the wireless channel. So, the highly nonlinear artificial neural network (ANN) models such as multilayer perceptron (MLP) and radial basis function (RBF) are used effectively for nonlinear node localization problems. ANN-based localization techniques are also capable of localizing mobile UNs. Further, the RBF with Gaussian activation has a little edge over the MLP with sigmoid activation because the wireless channel usually modelled with a Gaussian random variable. The simulation results included in this article also justify the efficacy of the proposed RBF localization with performance gain of about (7–70) % over MLP, OLSL and RSSI localization techniques.

Kala Praveen Bagadi

Papers

Performance Analysis of HSRP in Provisioning Layer-3 Gateway Redundancy for Corporate Networks

Design of near‐optimal local likelihood search‐based detection algorithm for coded large‐scale MU‐MIMO system

Performance Analysis of IPv4 to IPv6 Transition Methods

Design of Massive Multiuser MIMO System to Mitigate Inter Antenna Interference and Multiuser Interference in 5G Wireless Networks

Radial basis function-based node localization for unmanned aerial vehicle-assisted 5G wireless sensor networks