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

In this paper, we propose a new algorithm called Lenstra Lenstra Lovasz (LLL) assisted Likelihood Ascent Search (LAS) algorithm for signal detection in Massive MIMO which attains a near to optimum performance. This algorithm is developed by collaborating two existing algorithms to satisfy the tradeoff between performance and complexity in Massive Multiple Input Multiple Output (MIMO) systems. The Linear Detection and Lattice Reduction (LR) are some of the prominent suboptimal algorithms whose performance is far from optimal. In the proposed LLL-LAS Algorithm, the LLL algorithm is an LR based detection which serves as the initial solution to the LAS algorithm. The Simulation results substantiate the decrement in the Bit Error Rate which makes it better than the other classical detection techniques

Lenstra Lenstra Lovász (LLL) Assisted Likelihood Ascent Search (LAS) Algorithm for Signal Detection in Massive MIMO

The large scale multiuser multiple input multiple output (MU-MIMO) is one of the promising communication technology for 5G wireless networks as it offers reliability, high spectral efficiency and high throughput. The lattice reduction (LR) precoding based user level local likelihood ascent search (ULAS) detection scheme is proposed in this paper for efficient signal detection in large scale MU-MIMO system. The initial solution of ULAS algorithm is obtained from the LR precoding assisted zero forcing detector. The LR precoding transforms the non-orthogonal channel matrix into nearly orthogonal channel, which helps to mitigate inter antenna interference (IAI) exists at each user. The remaining multiuser interference (MUI) imposed to each user from undesired users is cancelled by the proposed ULAS multiuser detection scheme. Thus, the proposed LR precoding assisted ULAS mitigates both IAI and MUI unlike the classical detector, those try to moderate either IAI or MUI. By contrast, the proposed ULAS detector provides performance close to optimal maximum likelihood detector with just a fraction of its complexity.

Design of Large Scale MU-MIMO System with Joint Precoding and Detection Schemes for Beyond 5G Wireless Networks

Multi carrier–code division multiple access (MC–CDMA) system is a promising wireless communication technology with high spectral efficiency and system performance. Though the multiple access techniques provide high spectral efficiency, these techniques were prone to multiple access interference (MAI). So, this paper mainly aims at the design of the MC–CDMA receiver to mitigate MAI. The classical receivers like maximal ratio combining (MRC), equal gain combining (EGC), and minimum mean square error (MMSE) fails to cancel MAI when the MC– CDMA is subjected to non-linearistic degradations. By contrast, being highly non-linear classifiers, the neural network (NN) receivers could be better alternative under such a case. The feasibility, efficiency and effectiveness of the proposed multilayer perceptron (MLP) NN based receiver are studied in detail for the MC–CDMA with nonlinearistic degradations.

Receiver Design Using Artificial Neural Network for Signal Detection in Multi Carrier – Code Division Multiple Access System

Now a days in Service Provider’s core network we do not use IP forwarding rather we go for MPLS because it gives more efficient switching of packets. MPLS is the combination of layer-3 routing and layer-2 switching because every network prefix is assigned a particular Label. In this paper I am going to do testing and implement scalability over MPLS L3 VPN. This testing and implementation are to proof the scalability is the one important thing when design MPLS L3 VPN technology. This Topology of MPLS L3 VPN also provides the secure tunnel between two customer sites. By this implementation we show that there is a transparent tunneling over SP network. We are also avoiding the BGP implementation In SP core. So we call it as BGP free core. This implementation also saves the routing table space on provider routers. We have used the concept of Route Reflector (RR) to avoid more BGP sessions and to make it more scalable.

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Architecture for MPLS L3 VPN Deployment in Service Provider Network

OFDM is a form of multicarrier modulation technique with high spectral efficiency, robustness to channel fading, immunity to impulse interference, uniform average spectral density capacity of handling very strong echoes and non-linear distortion. Despite of its many advantages, one major disadvantage of OFDM is that the time domain OFDM signal which is a sum of several sinusoids leads to high peak to average power ratio (PAPR). The peak to average power ratio of the time domain envelope is an important parameter at the physical layer of the communication system using OFDM signaling. The signals must maintain a specified average energy level in the channel to obtain the desired Bit-error-rate. Pulse shaping techniques are very effective and mitigate problems associated with PAPR. In this paper conventional pulse shapes like Raised Cosine (RC), and sinc Power (SP) pulses are modified as Modified Raised Cosine Pulse (MRC) and Improved sinc Power pulse (ISP) introducing design parameter ‘d’ and amplitude parameter ‘a’ etc . The proposed method has fast decaying rate by decreasing the lobes of sinc function and its implementation complexity is also less. In this paper OFDM system performance measures like Complementary Cumulative Distribution Function (CCDF) of PAPR and bit error rate (BER) are analyzed through MATLAB simulation which proves the efficacy of the proposed pulse shaping scheme. It was observed from the performance curves using ISP pulse shaping filter at the OFDM transmitter’s end outperforms others.

Kala Praveen Bagadi

Papers

Lenstra Lenstra Lovász (LLL) Assisted Likelihood Ascent Search (LAS) Algorithm for Signal Detection in Massive MIMO

Design of Large Scale MU-MIMO System with Joint Precoding and Detection Schemes for Beyond 5G Wireless Networks

Receiver Design Using Artificial Neural Network for Signal Detection in Multi Carrier – Code Division Multiple Access System

Architecture for MPLS L3 VPN Deployment in Service Provider Network

Performance improvement of ofdm system by peak to average power reduction through pulse shaping technique