Paresh Saxena

• PhD
• Professor (Assistant) at Birla Institute of Technology and Science - Hyderabad Campus

In this paper, we propose a practical (low delay and low overhead) and simple (low complexity) network coding strategy for real time transmission over lossy line networks. We propose Systematic Random Coding (SRC) as outer code, which is performed at the transmitter node. The inner code is a combination of random coding and repetition coding (over...

In this paper, we investigate the use of systematic random network coding (SNC) for multicast and multi-unicast over satellite. In particular, the satellite coverage is over a large geographical area that consists of several users. These users may face different channel conditions and undergo different packet loss rates. In this work, we identify t...

In this letter, we investigate the benefits of systematic network coding (SNC) in Digital Video Broadcasting by Satellite-Second Generation (DVB-S2X) based satellite systems. We propose an architecture and encapsulation framework to use SNC at the link layer (LL) of DVB-S2X. Our proposal includes coding both at the source node and at one intermedia...

In this paper, we focus on the performance analysis of packetlevel Forward Error Correction (FEC) codes based on Systematic Random Linear Network Coding (SRNC) for multimedia transmission via erasure satellite channels. A performance comparison is presented against maximum distance separable (MDS) codes currently used in state-of-theart satellite t...

The paper introduces a Universal Serial Bus (USB)-based defense framework, USB-GATE, which leverages a Generative Adversarial Network (GAN) and transformer-based embeddings to enhance the detection of adversarial keystroke injection attacks. USB-GATE uses a Wasserstein GAN with Gradient Penalty (WGAN-GP) to augment benign data. The framework combin...

Intrusion detection systems (IDS) produce a vast number of alerts, many of which are false positives. Hence prioritizing these alerts for investigation is essential. It is also crucial to consider the different levels of knowledge of the defender (who prioritize alerts) about the system for developing effective defense strategies in the context of...

Fifth generation (5G) and beyond 5G networks support high-throughput ultra-high definition (UHD) video applications. This paper examines the use of dynamic adaptive streaming over HTTP (DASH) to deliver UHD videos from servers to 5G-capable devices. Due to the dynamic network conditions of wireless networks, it is particularly challenging to provid...

Due to its plug-and-play functionality and wide device support, the universal serial bus (USB) protocol has become one of the most widely used protocols. However, this widespread adoption has introduced a significant security concern: the implicit trust provided to USB devices, which has created a vast array of attack vectors. Malicious USB devices...

New Internet of Things (IoT) based applications with stricter key performance indicators (KPI) such as round-trip delay, network availability, energy efficiency, spectral efficiency, security, age of information, throughput, and jitter present unprecedented challenges in achieving next-generation ultra-reliable and low-latency communications (xURLL...

Providing a high Quality of Experience (QoE) for video streaming in 5G and beyond 5G (B5G) networks is challenging due to the dynamic nature of the underlying network conditions. Several Adaptive Bit Rate (ABR) algorithms have been developed to improve QoE, but most of them are designed based on fixed rules and unsuitable for a wide range of networ...

Adaptive bitrate (ABR) algorithms are used to adapt the video bitrate based on the network conditions to improve the overall video quality of experience (QoE). Recently, reinforcement learning (RL) and asynchronous advantage actor-critic (A3C) methods have been used to generate adaptive bit rate algorithms and they have been shown to improve the ov...

The fifth generation (5G) Wireless Communication systems development has brought out a paradigm shift using advanced technologies e.g., softwarization, virtualization, Massive MIMO, ultra-densification and introduction of new frequency bands. However, as the societal needs grow, and to satisfy UN's Sustainable Development Goals (SDGs), 6G and beyon...

Intrusion detection systems (IDS) generate a large number of false alerts which makes it difficult to inspect true positives. Hence, alert prioritization plays a crucial role in deciding which alerts to investigate from an enormous number of alerts that are generated by IDS. Recently, deep reinforcement learning (DRL) based deep deterministic polic...

The number of connected smart devices enabling multimedia applications has expanded tremendously in Internet-of-Things (IoT) environments. Specifically, the requirement for a high quality of experience (QoE) for video streaming services is a crucial prerequisite for a range of use cases, including smart surveillance, smart healthcare, smart agricul...

This paper proposes a computer vision based image classification approach to classify plastic wastes based on their resin identification code, to enable an efficient recycling of these wastes. While classification approaches to deal with waste plastic can be developed for known kinds of plastic, there is a need to also accommodate the challenges as...

During the last decade, research and development in the field of multi access edge computing (MEC) has rapidly risen to prominence. One of the factors propelling MEC’s evolution is the ability to deploy edge servers capable of providing both communication and computational services in close proximity to the mobile user terminal. MEC has been regard...

Adaptive bitrate (ABR) algorithms are used to adapt the video bitrate based on the network conditions to improve the overall video quality of experience (QoE). Further, with the rise of multi-access edge computing (MEC), a higher QoE can be guaranteed for video services by performing computations over the edge servers rather than the cloud servers....

This paper presents methods to identify the plastic waste based on its resin identification code to provide an efficient recycling of post-consumer plastic waste. We propose the design, training and testing of different machine learning techniques to (i) identify a plastic waste that belongs to the known categories of plastic waste when the system...

The problem of segregating recyclable waste is fairly daunting for many countries. This article presents an approach for image based classification of plastic waste using one-shot learning techniques. The proposed approach exploits discriminative features generated via the siamese and triplet loss convolutional neural networks to help differentiate...

This paper presents NANCY, a system that generates adaptive bit rates (ABR) for video and adaptive network coding rates (ANCR) using reinforcement learning (RL) for video distribution over wireless networks. NANCY trains a neural network model with rewards formulated as quality of experience (QoE) metrics. It performs joint optimization in order to...

Today, Unmanned Aerial Vehicles (UAVs) are widely used in many different scenarios including search, monitoring, inspection, and surveillance. To be able to transmit the sensor data from the UAVs to the destination reliably within tangible response times to the relevant content is crucial, especially for tactical use cases. In this paper, we propos...

Today, Unmanned Aerial Vehicles (UAVs) are widely used in many different scenarios including search, monitoring, inspection, and surveillance. To be able to transmit the sensor data from the UAVs to the destination reliably within tangible response times to the relevant content is crucial, especially for tactical use cases. In this paper, we propos...

In this paper, we present the practical design of systematic random network coding (SNC) for multicast over satellite. In particular, the satellite coverage is over a large geographical area that consists of several users. These users may face different channel conditions and undergo different packet loss rates. In this work, we show two regions of...

The concept of network coding has greatly evolved since its inception. Theoretical and achievable performance have been obtained for a wide variety of networking assumptions and performance objectives. Even if powerful, such a broad applicability poses a challenge to a unified design approach over different communication networks and systems. In th...

A novel cross-layer optimized video adaptation driven by perceptual semantics is presented. The design target is streamed live video to enhance situational awareness in challenging communications conditions. Conventional solutions for recreational applications are inadequate and novel quality of experience (QoE) framework is proposed which allows f...

In this paper, we present a Quality of Experience (QoE) based framework for point-to-point adaptive video in best effort band-limited satellite networks. We consider two time-varying factors degrading QoE in this scenario, namely: network unavailability due to bursty erasure events and the best effort shared channel dynamics. Our proposal is two-fo...

In this paper, we focus on the performance analysis of packet-level Forward Error Correction (FEC) codes based on Systematic Random Linear Network Coding (SRNC) for multimedia transmission via erasure satellite channels. A performance comparison is presented against maximum distance separable (MDS) codes currently used in state-of-the-art satellite...

For the two-user interference channel, the Han-Kobayashi (HK) scheme is known to achieve optimal rates within one bit of the capacity for Gaussian codebooks. In this paper, we propose its practical implementation based on finite M-QAM constellations. For the very strong interference regime, we derive the interference level conditions and its geomet...