Predicting Performance of Channel Assignments in Wireless Mesh Networks through Statistical Interference Estimation

Wireless Mesh Network (WMN) deployments are poised to reduce the reliance on wired infrastructure especially with the advent of the multi-radio multi-channel (MRMC) WMN architecture. But the benefits that MRMC WMNs offer viz., augmented network capacity, uninterrupted connectivity and reduced latency, are depreciated by the detrimental effect of prevalent interference. Interference mitigation is thus a prime objective in WMN deployments. It is often accomplished through prudent channel allocation (CA) schemes which minimize the adverse impact of interference and enhance the network performance. However, a multitude of CA schemes have been proposed in research literature and absence of a CA performance prediction metric, which could aid in the selection of an efficient CA scheme for a given WMN, is often felt. In this work, we offer a fresh characterization of the interference endemic in wireless networks. We then propose a reliable CA performance prediction metric, which employs a statistical interference estimation approach. We carry out a rigorous quantitative assessment of the proposed metric by validating its CA performance predictions with experimental results, recorded from extensive simulations run on an ns-3 802.11g environment

A Novel Beamformed Control Channel Design for LTE with Full Dimension-MIMO

The Full Dimension-MIMO (FD-MIMO) technology is capable of achieving huge improvements in network throughput with simultaneous connectivity of a large number of mobile wireless devices, unmanned aerial vehicles, and the Internet of Things (IoT). In FD-MIMO, with a large number of antennae at the base station and the ability to perform beamforming, the capacity of the physical downlink shared channel (PDSCH) has increased a lot. However, the current specifications of the 3rd Generation Partnership Project (3GPP) does not allow the base station to perform beamforming techniques for the physical downlink control channel (PDCCH), and hence, PDCCH has neither the capacity nor the coverage of PDSCH. Therefore, PDCCH capacity will still limit the performance of a network as it dictates the number of users that can be scheduled at a given time instant. In Release 11, 3GPP introduced enhanced PDCCH (EPDCCH) to increase the PDCCH capacity at the cost of sacrificing the PDSCH resources. The problem of enhancing the PDCCH capacity within the available control channel resources has not been addressed yet in the literature. Hence, in this paper, we propose a novel beamformed PDCCH (BF-PDCCH) design which is aligned to the 3GPP specifications and requires simple software changes at the base station. We rely on the sounding reference signals transmitted in the uplink to decide the best beam for a user and ingeniously schedule the users in PDCCH. We perform system level simulations to evaluate the performance of the proposed design and show that the proposed BF-PDCCH achieves larger network throughput when compared with the current state of art algorithms, PDCCH and EPDCCH schemes

User Pairing and Power Allocation for IRS-Assisted NOMA Systems with Imperfect Phase Compensation

In this letter, we analyze the performance of the intelligent reflecting surface (IRS) assisted downlink non-orthogonal multiple access (NOMA) systems in the presence of imperfect phase compensation. We derive an upper bound on the imperfect phase compensation to achieve minimum required data rates for each user. Using this bound, we propose an adaptive user pairing algorithm to maximize the network throughput. We then derive bounds on the power allocation factors and propose power allocation algorithms for the paired users to achieve the maximum sum rate or ensure fairness. Through extensive simulations, we show that the proposed algorithms significantly outperform the state-of-the-art algorithms

Stabilization of Black cotton soil with Tyre Waste

Black cotton soil which covers the major portion of Indian sub continent poses challenging problems to infrastructural development in the region. The soil is generally weak and has less stability against the application of load. These soils are used in sub grade of pavement and also in construction of structures. The swelling and shrinkage property of black cotton soil makes it difficult for construction. Soil stabilization is one such method which will be adopted to improve the properties of soils. Many additives such as fly ash, mine waste, cement, lime have been used inthe past to stabilize the soils. In this study an attempt is made to stabilize the soil using tyre waste. Results of the study reveal that the engineering properties of soil can be improved by the addition of tyre waste and also solves the problem of disposal of waste

TBX3 regulates splicing in vivo: a novel molecular mechanism for Ulnar-Mammary Syndrome

pre-printTBX3 is a member of the T-box family of transcription factors with critical roles in development, oncogenesis, cell fate, and tissue homeostasis. TBX3 mutations in humans cause complex congenital malformations and Ulnar-mammary syndrome. Previous investigations into TBX3 function focused on its activity as a transcriptional repressor. We used an unbiased proteomic approach to identify TBX3 interacting proteins in vivo and discovered that TBX3 interacts with multiple mRNA splicing factors and RNA metabolic proteins. We discovered that TBX3 regulates alternative splicing in vivo and can promote or inhibit splicing depending on context and transcript. TBX3 associates with alternatively spliced mRNAs and binds RNA directly. TBX3 binds RNAs containing TBX binding motifs, and these motifs are required for regulation of splicing. Our study reveals that TBX3 mutations seen in humans with UMS disrupt its splicing regulatory function. The pleiotropic effects of TBX3 mutations in humans and mice likely result from disrupting at least two molecular functions of this protein: transcriptional regulation and pre-mRNA splicing

Modeling, Analysis and Design of Synchronous Buck Converter Using State Space Averaging Technique for PV Energy System

If we start forecasting in the view of electrical energy generation, in the upcoming decade all the fossil fuels are going to be extinct or the worst they are going to be unaffordable to a person living in typical circumstances, so renewable power energy generation systems are going to make a big deal out of that. It is extremely important to generate and convert the renewable energy with maximum efficiency. In this project, first we study the characteristics of low power PV array under different values of irradiance and temperature. And then we present the exquisite design of Synchronous Buck Converter with the application of State Space Modeling to implement precise control design for the converter by the help of MATLAB/Simulink. The Synchronous Buck Converter thus designed is used for portable appliances such as mobiles, laptops, iPod’s etc. But in this project our main intention is to interface the PV array with the Synchronous Buck Converter we designed, and we will depict that our converter is more efficient than the conventional buck converter in terms of maintaining constant output voltage, overall converter efficiency etc. And then we show that the output voltage is maintaining constant irrespective of fluctuations in load and source. And finally we see the performance of Synchronous Buck Converter, which is interfaced with PV array having the practical variations in temperature and irradiance will also maintain a constant output voltage throughout the response. All simulations are carried under MATLAB/Simulink environment. And at last experimental work is carried out for both conventional buck converter and also for synchronous buck converter, in which we observe the desired outputs obtained in simulations

Reliable Prediction of Channel Assignment Performance in Wireless Mesh Networks

The advancements in wireless mesh networks (WMN), and the surge in multi-radio multi-channel (MRMC) WMN deployments have spawned a multitude of network performance issues. These issues are intricately linked to the adverse impact of endemic interference. Thus, interference mitigation is a primary design objective in WMNs. Interference alleviation is often effected through efficient channel allocation (CA) schemes which fully utilize the potential of MRMC environment and also restrain the detrimental impact of interference. However, numerous CA schemes have been proposed in research literature and there is a lack of CA performance prediction techniques which could assist in choosing a suitable CA for a given WMN. In this work, we propose a reliable interference estimation and CA performance prediction approach. We demonstrate its efficacy by substantiating the CA performance predictions for a given WMN with experimental data obtained through rigorous simulations on an ns-3 802.11g environment.Comment: Accepted in ICACCI-201

Radio Co-location Aware Channel Assignments for Interference Mitigation in Wireless Mesh Networks

Designing high performance channel assignment schemes to harness the potential of multi-radio multi-channel deployments in wireless mesh networks (WMNs) is an active research domain. A pragmatic channel assignment approach strives to maximize network capacity by restraining the endemic interference and mitigating its adverse impact on network performance. Interference prevalent in WMNs is multi-faceted, radio co-location interference (RCI) being a crucial aspect that is seldom addressed in research endeavors. In this effort, we propose a set of intelligent channel assignment algorithms, which focus primarily on alleviating the RCI. These graph theoretic schemes are structurally inspired by the spatio-statistical characteristics of interference. We present the theoretical design foundations for each of the proposed algorithms, and demonstrate their potential to significantly enhance network capacity in comparison to some well-known existing schemes. We also demonstrate the adverse impact of radio co- location interference on the network, and the efficacy of the proposed schemes in successfully mitigating it. The experimental results to validate the proposed theoretical notions were obtained by running an exhaustive set of ns-3 simulations in IEEE 802.11g/n environments.Comment: Accepted @ ICACCI-201

Role of sentiment classification in sentiment analysis: a survey

Through a survey of literature, the role of sentiment classification in sentiment analysis has been reviewed. The review identifies the research challenges involved in tackling sentiment classification. A total of 68 articles during 2015 – 2017 have been reviewed on six dimensions viz., sentiment classification, feature extraction, cross-lingual sentiment classification, cross-domain sentiment classification, lexica and corpora creation and multi-label sentiment classification. This study discusses the prominence and effects of sentiment classification in sentiment evaluation and a lot of further research needs to be done for productive results