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A surface plasmon resonance (SPR) based photonic crystal fiber (PCF) sensor having a milled microchannel, and an open D-channel has been proposed in this paper. The sensor shows good functionality in the wide sensing range of 1.14-1.36 Refractive Index Units (RIU) of the analyte, having the capability to detect low refractive index (RI). The Finite Element Method (FEM) based numerical investigations dictate that the proposed sensor has been able to gain a maximum wavelength sensitivity of 53,800 nm/RIU according to the wavelength interrogation technique. The amplitude interrogations show that the sensor has the highest amplitude sensitivity of 328 RIU-1. The highest FOM (Figure of Merit) has been found to be 105 RIU-1. The sensor evinces a minimum wavelength resolution of $1.86\times 10 ^{-6}$ RIU, which secures high detection accuracy. A circular perfectly matched layer (PML) is implemented in the sensor's outermost layer as a boundary condition to absorb surface radiations. Gold is the plasmonic metal, while TiO2 acts as the adhesive layer for gold attachment on silica. Due to the high sensitivity with a broad range of analyte detection, the sensor is well suited for practical biochemical detection purposes.

In this paper,a polarization-maintaining single-mode rectangular-shaped hollow-core waveguide with four segmented air cladding in the terahertz (THz) regime is presented for detecting various toxic industrial chemicals. A new type of injection moldable cyclic olefin copolymer, commercially named as TOPAS is used as the base fiber material for its high optical transmission and high resistance to other chemicals. The finite element method with a perfectly matched layer as the boundary condition is employed for numerical explorations. The proposed sensor exhibits ultra-high relative sensitivity of 99.73% and ultra-low effective material loss of 0.007 cm−1 at 1.6 THz frequency for Toluene in y polarization. This sensor also evinces a high birefringence of $4.16\times 10^{-3}$ at 1.6 THz frequency. A maximum V parameter of 2.224 has been found at 2.2 THz which ensures the single-mode propagation of light. The sensor shows a very low confinement loss of $3.2\times 10^{-11}$ dB/m and a high numerical aperture of 0.3574 at 1.6 THz frequency for Hydrogen Sulfide. This paper also concentrates on other important design parameters such as bending loss, mode field radius, beam divergence and effective area for serviceability of the sensor in the THz region. This sensor can be a very good candidate for various chemical detection as well as other applications in the terahertz regime.

Increasing concerns regarding wireless systems’ security are leading researchers to exploit the physical properties of a medium while designing any secured wireless network. The secrecy performance of a mixed radio frequency-free space optical (RF-FSO) system with a variable gain relaying scheme is investigated in this paper under the attempt of wiretapping by an eavesdropper. We assume that the eavesdropper can intrude the target data from the RF link only. Both the RF links (main and eavesdropper) undergo the $\alpha -\mu $ fading statistics and the FSO link experiences the exponentiated Weibull fading statistics. Exploiting the amplify-and-forward (AF) relaying scheme while considering two detection techniques (i.e. heterodyne detection and intensity modulation/direct detection) with pointing error impairments, the mathematical formulations of the unified probability density function and cumulative distribution function are performed for the equivalent signal-to-noise ratio of the considered dual-hop RF-FSO link. Closed-form analytical expressions for average secrecy capacity, secrecy outage probability, and the probability of non-zero secrecy capacity are derived in terms of Meijer’s $G$ and Fox’s $H$ functions to quantify the system performance. Capitalizing on these expressions, the secrecy performance is further analyzed for various channel parameters of RF links, aperture sizes of the receiver, pointing errors, and atmospheric turbulence severity. The results reveal that aperture averaging can improve the secrecy performance remarkably by suppressing the effects of turbulence. Monte Carlo simulations are provided to justify the accuracy of the proposed model.

In Radio Frequency (RF)-Free Space Optical (FSO) mixed links, secrecy capacity (SC) can be improved by exploiting spatial diversity (i.e., antenna diversity) in the RF path. In addition to atmospheric turbulence and point error of the FSO link, antenna correlation in the RF link can significantly deteriorate the secrecy performance. In this paper, a secrecy rate of wiretap channels with a single source, relay, destination, and eavesdropper is analyzed under practical environments with the aforementioned impairments. The RF hop (source-to-relay) and the FSO hop (relay-to-destination) are modeled utilizing arbitrarily correlated Nakagami-$m$ and Málaga ($\mathcal {M}$) distributions, respectively. The correlated signal branches of the RF hop are combined at the relay exploiting equal gain combining reception technique. We assume that the eavesdropper is capable of wiretapping via RF and FSO links separately. We derive novel closed-form expressions for secrecy outage probability (SOP) and strictly positive secrecy capacity (SPSC) considering heterodyne detection (HD) and intensity modulation with direct detection (IM/DD) techniques in order to examine the impact of atmospheric scintillation, pointing error, fading, and correlation on the system's secrecy performance. It is shown that the HD technique exhibits a better performance than an IM/DD technique. In addition, similar to the pointing error and turbulent fading, the correlation imposes a detrimental impact on SC. Finally, Monte-Carlo simulation results are provided for validation of the derived expressions.

This work deals with the secrecy performance analysis of a dual-hop RF-FSO DF relaying network composed of a source, a relay, a destination, and an eavesdropper. We assume the eavesdropper is located close to the destination and overhears the relay’s transmitted optical signal. The RF and FSO links undergo ( $\alpha -\kappa -\mu $ )-shadowed fading and unified Málaga turbulence with pointing error. The secrecy performance of the mixed system is studied by deriving closed-form analytical expressions of secure outage probability (SOP), strictly positive secrecy capacity (SPSC), and intercept probability (IP). Besides, we also derive the asymptotic SOP, SPSC, and IP upon utilizing the unfolding of Meijer’s $G$ function where the electrical SNR of the FSO link tends to infinity. Finally, the Monte-Carlo simulation is performed to corroborate the analytical expressions. Our results illustrate that fading, shadowing, detection techniques (i.e. heterodyne detection (HD) and intensity modulation and direct detection (IM/DD)), atmospheric turbulence, and pointing error significantly affect the secrecy performance. In addition, better performance is obtained exploiting the HD technique at the destination relative to IM/DD technique.

Brain is the controlling center of our body. With the advent of time, newer and newer brain diseases are being discovered. Thus, because of the variability of brain diseases, existing diagnosis or detection systems are becoming challenging and are still an open problem for research. Detection of brain diseases at an early stage can make a huge difference in attempting to cure them. In recent years, the use of artificial intelligence (AI) is surging through all spheres of science, and no doubt, it is revolutionizing the field of neurology. Application of AI in medical science has made brain disease prediction and detection more accurate and precise. In this study, we present a review on recent machine learning and deep learning approaches in detecting four brain diseases such as Alzheimer’s disease (AD), brain tumor, epilepsy, and Parkinson’s disease. 147 recent articles on four brain diseases are reviewed considering diverse machine learning and deep learning approaches, modalities, datasets etc. Twenty-two datasets are discussed which are used most frequently in the reviewed articles as a primary source of brain disease data. Moreover, a brief overview of different feature extraction techniques that are used in diagnosing brain diseases is provided. Finally, key findings from the reviewed articles are summarized and a number of major issues related to machine learning/deep learning-based brain disease diagnostic approaches are discussed. Through this study, we aim at finding the most accurate technique for detecting different brain diseases which can be employed for future betterment.

We study the secrecy transmission of uplink non-orthogonal multiple access (NOMA) with single antenna and multi-antenna users in presence of an eavesdropper. Two phases are required for communications during each time frame between the users and the base station in cellular networks. We study the case where an eavesdropper overhears the relay and direct links from the users to the base stations. In terms of the secure performance analysis, we focus on two main metrics including secrecy outage probability (SOP) and strictly positive secrecy capacity (SPSC) with the assumption that the eavesdropper is able to detect the signals. Analytical closed-form expressions for the SOP and SPSC are derived to evaluate the system secure performance achieved by the proposed schemes. Furthermore, the asymptotic analysis is presented to gain further insights. The analytical and numerical results indicate that the proposed schemes can realize better secrecy performance once we improve the channel condition and signal-to-noise ratio (SNR) at the base station. Our results confirms that the secrecy performance gaps exist among the two users since different power allocation factors are assigned to these users.

With the rapid evolution of communication technologies, high-speed optical wireless applications under the water surface as a replacement or complementary to the conventional radio frequency (RF) and acoustic technologies are attracting significant attention from the researchers. Since underwater turbulence (UWT) is an inevitable impediment for a long distance underwater optical wireless communication (UOWC) link, mixed RF-UOWC is being considered as a more feasible solution by the research community. This article deals with the secrecy performance of a variable gain relay-based mixed dual-hop RF-UOWC framework under the intercepting attempt of a potential eavesdropper. The RF link undergoes Generalized Gamma (GG) fading distribution, whereas the UOWC link is subjected to mixture Exponential Generalized Gamma (mEGG) distribution. The eavesdropper is capable of wiretapping via a RF link that also experiences the GG fading. The secrecy analysis incorporates the derivations of closed-form expressions for strictly positive secrecy capacity, average secrecy capacity, and exact as well as lower bound of secrecy outage probability in terms of univariate and bivariate Meijer’s $G$ and Fox’s $H$ functions. Based on these expressions, impacts of heterodyne and intensity modulation/direct detection techniques along with weak, moderate, and severe UWT conditions due to air bubbles, temperature, and salinity gradients are quantified. To the best of authors’ knowledge, the proposed model is the first of its kind that addresses the secrecy analysis of a temperature gradient RF-UOWC system along with air bubbles, as opposed to the existing models that considered thermally uniform scenarios only. Finally, the derived expressions are verified via Monte-Carlo simulations.

The emergence of an array of new wireless networks has led researchers to evaluate the prospect of utilizing the physical properties of the wireless medium in order to design secure systems. In this paper, the physical layer secrecy performance of a mixed radio frequency-free space optical (RF-FSO) system with variable gain relaying scheme is investigated in the presence of an eavesdropper. We assume that the eavesdropper can wiretap the transmitted confidential data from the RF link only. It is further assumed that the main and eavesdropper RF links are modeled as generalized Gamma (GG) fading channel, and the free space optical (FSO) link experiences Málaga turbulence with pointing error impairment. Our primary concern is to protect this confidential information from being wiretapped. Besides pointing error, the atmospheric turbulence and two types of detection techniques (i.e. heterodyne detection and intensity modulation with direct detection) are also taken into consideration. Utilizing amplify-and-forward (AF) scheme, the novel mathematical closed-form expressions for average secrecy capacity, lower bound of secrecy outage probability, and strictly positive secrecy capacity are derived. As both the links (RF and FSO) undergo generalized fading channels, the derived expressions are also general. We present a unification of some existing works utilizing the proposed model to better clarify the novelty of this work. Finally, all the derived expressions are justified via Monte-Carlo simulations.

Precision Medicine (PM) is an emerging approach that appears with the impression of changing the existing paradigm of medical practice. Recent advances in technological innovations and genetics, and the growing availability of health data have set a new pace of the research and imposes a set of new requirements on different stakeholders. To date, some studies are available that discuss about different aspects of PM. Nevertheless, a holistic representation of those aspects deemed to confer the technological perspective, in relation to applications and challenges, is mostly ignored. In this context, this paper surveys advances in PM from informatics viewpoint and reviews the enabling tools and techniques in a categorized manner. In addition, the study discusses how other technological paradigms including big data, artificial intelligence, and internet of things can be exploited to advance the potentials of PM. Furthermore, the paper provides some guidelines for future research for seamless implementation and wide-scale deployment of PM based on identified open issues and associated challenges. To this end, the paper proposes an integrated holistic framework for PM motivating informatics researchers to design their relevant research works in an appropriate context., 22 pages, 8 figures, 5 tables, journal paper

Vehicular networks aim to support cooperative warning applications that involve the dissemination of warning messages to reach vehicles in a target area. Due to the high mobility of vehicles, imperative technologies such as software-defined network (SDN) and edge computing (EC) have been proposed for the next-generation vehicular networks. The SDN separates the control plane from data plane entities and executes the control plane software on general purpose hardware. On the other hand, EC aims to reduce the network latency and packet loss rate by pushing the computations to the edge of the network. Nevertheless, the current solutions that integrate SDN and EC could not satisfy the latency requirements for data dissemination of vehicle-to-everything (V2X) services. To bridge the gap between the two technologies, the conventional EC is enhanced to multi-access edge computing (MEC) by collocating the edge computing servers with the radio access networks. In order to improve the latency for V2X services, we propose in this paper, an SDN-based multi-access edge computing framework for the vehicular networks (SDMEV). In the proposed solution, two main algorithms are implemented. First, a fuzzy logic-based algorithm is used to select the head vehicle for each evolved node B (eNB) collocated with road-side unit (RSU) for the purpose of grouping vehicles based on their communication interfaces. Afterward, an OpenFlow algorithm is deployed to update flow tables of forwarding devices at forwarding layers. In addition, a case study is presented and evaluated using the object-oriented modular discrete event network (OMNeT++) simulation framework which includes the INET framework-based SDN. Simulation results depict that the data dissemination based-SDN supported by multi-access edge computing over SDMEV can improve the latency requirements for V2X services.

Cloud computing has become popular in various application domains based on infrastructure, platform, and software as a service model. Rapid deployment, high scalability, on-demand, and (theoretically) infinite resources have driven the industry towards the wide adoption of cloud computing services. However, the difficulty of cross-provider resource allocation and seamless resource transition is a major concern for such services. Therefore, the segregated cloud market forces its clients to use provider-specific and pre-configured options for their required resources and services. Thus, the overall market, even with the presence of multiple cloud service providers, operates as a direct service from the providers to the clients, and with non-negotiable pricing strategies for the cloud services. In this article, we propose Bepari, a cost-driven model for opaque service platforms for cloud computing. Bepari acts as a negotiation-based approach to deliver composite cross-provider cloud-based services to the end-users. Bepari provides a detailed service-oriented architecture for multiple cloud service providers to provide cross-platform and composite services. Furthermore, Bepari delivers a detailed cost model and comparison between establishing a cloud service vs. an opaque cloud service. Our empirical framework allows a Bepari service provider to analyze the profit model and create a market niche accordingly. Simulation results are provided, which validate the efficiency of a negotiated pricing strategy in terms of maximized resource utilization and profits for cloud service providers and cost reduction for the cloud users.

The ubiquitous nature of IoT devices has brought new and exciting applications in computing and communication paradigms. Due to its ability to enable auto-configurable communication between IoT devices, pervasive applications, and remote clients, the use of the Universal Plug and Play (UPnP) protocol is widespread. However, the advertisement and discovery mechanism of UPnP incurs significant overhead on resource-constrained IoT devices. In this paper, we propose a delegation-based approach that extends the UPnP protocol by offloading the service advertisement and discovery-related overhead from resource-limited IoT devices to the resource-rich neighbours of a UPnP-enabled IoT network. Our experimental evaluations demonstrate that the proposed scheme shows significant improvement over the basic UPnP, reducing energy consumption and network overhead.

The emergence of an array of new wireless networks has led researchers to evaluate the prospect of utilizing the physical properties of the wireless medium in order to design secure systems. In this paper, the physical layer secrecy performance of a mixed radio frequency-free space optical (RF-FSO) system with variable gain relaying scheme is investigated in the presence of an eavesdropper. We assume that the eavesdropper can wiretap the transmitted confidential data from the RF link only. It is further assumed that the main and eavesdropper RF links are modeled as generalized Gamma (GG) fading channel, and the free space optical (FSO) link experiences Malaga turbulence with pointing error impairment. Our primary concern is to protect this confidential information from being wiretapped. Besides pointing error, the atmospheric turbulence and two types of detection techniques (i.e. heterodyne detection and intensity modulation with direct detection) are also taken into consideration. Utilizing amplify-and-forward (AF) scheme, the novel mathematical closed-form expressions for average secrecy capacity, lower bound of secrecy outage probability, and strictly positive secrecy capacity are derived. As both the links (RF and FSO) undergo generalized fading channels, the derived expressions are also general. We present a unification of some existing works utilizing the proposed model to better clarify the novelty of this work. Finally, all the derived expressions are justified via Monte-Carlo simulations.

Compared to orthogonal multiple access (OMA), non-orthogonal multiple access (NOMA) can achieve higher spectral efficiency by exploiting the power domain multiplexing. In this paper, we investigate the performance of NOMA in a two-tier heterogeneous network (HetNet) with non-uniform small cell deployment, where critical performance metrics like coverage probability and achievable rate are analyzed. First, a NOMA-based HetNet model is established, where users are paired based on the proposed user pairing scheme. Then the distribution of the order statistics for the distances between different NOMA users and the serving base station (BS) is presented considering the channel qualities from the NOMA users to the BSs. On this basis, we analytically demonstrate the impact of various network parameters on the coverage probability and achievable rate of NOMA users, such as signal-to-interference-plus-noise ratio threshold and BS density. Furthermore, an analysis is presented to provide insight into the energy efficiency of the considered system. Finally, extensive simulation and comparisons are conducted, which validate the advantages of NOMA over OMA in the considered HetNet environment.

Internet of Things comprises nodes with different functionalities, storage capacity, battery life, and computing capabilities. Spatially dispersed and dedicated low powered wireless sensor devices tremendously contribute to enabling Internet of things. However, direct access to data sensed by these sensor devices are restricted to users of foreign networks due to security threats. In this paper, we propose a ticket-based authentication between a low powered sensor node and a mobile device that belong to the foreign network. Considering the capacity limitations of sensor nodes, the key derivation and distribution load are moved to authentication server existing in its administrative domain. The security analysis is also presented to confirm solidity of the presented technique.

In this paper, we propose a hybrid nano communication (HNC) system that integrates three possible modes of nano communications: terahertz communication (TC), molecular communication (MC), and neural communication (NC). The paper provides some insights into how the required four key building blocks, namely, terahertz to molecular (T2M) relay interface, molecular to terahertz (M2T) interface, molecular to neural (M2N) relay, and neural to molecular (N2M) interface can be designed to implement the HNC system. In addition, the capacity analysis for the hybrid channel is provided. Sub-channels’ capacities are also calculated. Finally, numerical results are presented to comprehend the data transmission capacity of the proposed HNC system.

Physical layer (PHY) security that is based on information-theoretic secrecy has recently emerged as an alternative option for traditional cryptographic techniques to secure wireless networks. In this paper, we study the problems related to routing scheme along with PHY security for a multihop wireless network so that full diversity can be achieved at each hop. We propose a hop-by-hop best relay selection for the multihop ad-hoc wireless network consisting several relays at each hop in presence of an eavesdropper such that a secure routing scheme to transmit a confidential message from transmitter to legitimate receiver is achieved. The selection is performed considering the instantaneous channel conditions of relay as well as eavesdropper at each hop. We derive a closed form expressions for the probability of non-zero secrecy capacity along with end to end probability of secrecy outage at a normalized secrecy rate. Moreover, we provide an asymptotic expression to gain insights on the diversity gain.

The high demand for memory devices by decreasing power consumption is significant. SRAM has been under its renewal phase by enduring the ever-increasing delay along with supporting low power applications. A New 10 transistor (lOT) SRAM cell architecture has been proposed as explanations for the limitations of conventional SRAM models, in this paper. The proposed cell excels, in particular, three aspects: 1) data overwriting, 2) low power consumption, and 3) Improved area. The second value makes it particularly appropriate for a SRAM is stability. We have simulated and validated its performance by using 45nm predictive technology model (PTM).

Dynamic CMOS circuits are frequently used in low power and high-performance VLSI systems. Limitations of noise margin, leakage current are main challenging element of dynamic circuit design. In this work, a new model keeper circuit is proposed that optimizes the noise tolerance and power dissipation. Expansive simulation analysis by employing LTSpice tools using 32nm PTM technology establish the validity and robustness of the proposed work.

Dynamic logic is highly in demand for designing low power VLSI circuits. It need less number of transistor though but the performance of the dynamic logic is not so promising due to prolonged contention time and higher leakage power. Present research proposes a new nMOS based resistive circuit in order to reduce the contention time for minimum leakage power. Simulation results using LTspice tools demonstrate that the proposed model significantly reduces the contention time as well as the leakage power.

This research proposed a new type of memory cell designed by using only nMOS transistors of 16nm, 22nm and 45nm (Arizona State University Predictive Technologies Model) PTM models and memristors. The memory cell consumes less power and also occupies minimum amount of silicon area. The stability of the data during successive read operation and noise margin are in the promising range. Extensive simulation results demonstrate the validity and competency of the proposed model in the sector of time delay, static noise margin and power consumption.

This research proposed a new design of memory cell of 7T SRAM using 16nm and 45nm (Arizona State University Predictive Technologies Model) PTM models. The memory cell provides larger static noise margin in hold state and a better read operation by controlling drain induces barrier lowering (DIBL) effect. With utilization of a single transistor, proposed cell provides stability of the data not only during successive read operation but also overwriting new data. Extensive simulation results using LTspice demonstrate the time delay, static noise margin and power consumption of the proposed cell.

Dynamic logic is most area effective technique for designing VLSI circuit. However, due to lower noise margin of dynamic logic performance is not auspicious. This research proposes a N-FinFET based resistive keeper circuit using 45nm PTM FinFET model which reduces the contention between pull down network and keeper device using the special feature of four terminal FinFET (capacitance merging among both gates of four terminal FinFET). Proposed resistive gate voltage can control the strength of keeper device which reduces the leakage power and time delay. Extensive simulation results using LTSpice tools demonstrate the validity and superiority of the introduced circuit.

This research proposed a new type of memory cell designed by using only nMOS transistors. The memory cell consumes less power and also occupies minimum amount of silicon area. The stability of the data during successive read operation and noise margin are in the promising range. Extensive simulation results demonstrate the validity and competency of the proposed cell.

Designing VLSI circuit using dynamic logic is one of the most area efficient techniques. However, the performance of the dynamic logic is not so promising due to longer time delay and higher leakage power. This research proposes a new model of dynamic logic by incorporating nMOS based resistive gate circuit. The proposed circuit reduces the contention time delay and the leakage power. Extensive simulation results using LTSpice tools demonstrate the validity and superiority of the proposed circuit.

In the new era of smart grid in power system, demand side management (DSM) plays a vital role which helps the customers to make the right decision regarding their power consumption thus minimize the peak load demand and provide the best load profile. Due to DSM carbon emission level and financial cost has been deduced. This paper represents a strategy on load shifting technique for demand side management for commercial customers of future smart grids. A complete methodology for implementing a DSM program has also been outlined. Case study has been carried out taking Ahsanullah University of Science and Technology (AUST), Dhaka as a commercial customer. Results prove that implementation of proposed methodology would provide substantial economic benefit to customer and distributors.

Automatic Number Plate Recognition (ANPR) is a kind of image processing technology for recognizing the vehicle number plate. This system also offers users to place, mark out and monitor moving vehicles automatically by extracting their number plates. It also plays an important role in intelligent traffic control system. This research presents a prosperous method to identify vehicle number plates. The proposed technique is built on morphological operations based on different structuring elements in order to maximally exclude non-interested region and improve object area. This system has been experienced using a database of number plates and simulated results demonstrate major improvements as compared to other conventional systems. The success rate of the proposed method is about 92% with varying light conditions.

Development of an accurate three dimensional (3D) model of human skull showing the shape and relative position of a tumor inside the cancerous brain is crucial for taking pre-surgical or pre-therapy measures. This paper presents a new method for automatic segmentation of volumetric image which is a collection of series of spatially distributed slice images of a cancerous brain. The proposed method provides a 3D visualization in order to identify the position, shape, and size of a tumor inside the brain of a skull. Each of the images of the series is segmented using a level-based segmentation method using the histogram of image intensities. Such a segmentation of single image in the series results in spurious regions which may cause misleading 3D shapes of tumors. In order to obtain an accurate 3D model of the tumor inside the brain, both the intra- and inter-slice area-based thresholds are exploited for removing the spurious regions from the initially segmented images. The proposed segmentation scheme not only removes the false regions regarding the segmentation of tumor, but also effectively maintains the size and shape of the original tumor. Extensive experimentations on a number of volumetric images reveal that the proposed method can provide minimum volumetric noise in the extraction process of a tumor as compared to the recently introduced vector flow method.

High-speed, flexible and reliable detection schemes are the demands for today's communication systems while keeping in mind the complexity issues. In this comparative study; different detection schemes in UWB-MIMO systems have been analyzed. The V-BLAST algorithms with OSIC are briefly discussed and simulated to differentiate their performance by considering the multipath environment. In particular, the ZF-OSIC-RAKE and MMSE-OSIC-RAKE were used to evaluate the performance of UWB-MIMO system and then it was compared with the ML algorithm. The performance comparison results are based on the number of paths of the signal and number of antennas.

Interference reduces the performance of a correct data signal detection and decoding. This problem becomes severe when interferences exist during the period of channel estimation. This will destroy the accuracy of channel estimation and, will eventually result severe degradation in the performance of signal detection and decoding in the entire data packet/frame. In this article, we propose an improved channel estimation technique for multiband orthogonal frequency division multiplexing (MB-OFDM) ultra-wideband (UWB) system in presence of interferences. In particular, we work towards a preamble-based channel estimation technique in multi-access and narrowband interfering environments. We construct two preamble symbols with opposite, both in amplitude and phase, sequences in frequency-domain. Time-domain redundancy is introduced into these preamble symbols before transmission. Based on this time-domain redundancy property, we eliminate multi-access interference (MAI) through an adaptive select and replace (ASR) scheme. We show that the use of opposite sequences in preambles leads a simple addition, subtraction and compare (ASC) scheme to cancel narrowband interference (NBI). In addition, we apply a frequency-domain filter, driven by channel's power delay profile (PDP), to get a further enhancement in the estimation accuracy. Simulation results urge that our proposed technique outperforms the conventional channel estimation methods.

The field of speech compression has advanced rapidly due to cost-effective digital technology and diverse commercial applications. In voice communication a real-time system should be considered. It is not still possible to compress signals without facing any loss in real-time system. This paper presents a theory of loss-less digital compression for saving high quality speech signals. Emphasis is given on the quality of speech signal. In hearing music high quality music is always needed, consuming smaller memory space. In this compression 8-bit PCM/PCM speech signal is compressed. When values of samples are varying they are kept same. When they are not varying the number of samples containing same value is saved. After compression the signal is also an 8-bit PCM/PCM but expansion is needed before hearing it. This technique may also be used in real-time systems.

New channel estimation technique is proposed for multiband orthogonal frequecny division multiplexing (MB-OFDM) ultra-wideband (UWB) systems. Several steps have been carried out to achieve this purpose. In first step, refined least square (LS) channel estimation is found out by using subspace-based narrowband interference (NBI) estimation method with prilimonary LS channel. In second step, low rank least square minimum mean squared error (LMMSE) channel estimation is performed using this refined LS channel estimation. Finally, Blackman windowing is applied on low rank LMMSE channel to reduce the spectral leakage and hence to increase the channel estimation accuracy. Before starting the actual channel estimation, an ICI mitigation filter is used to minimize the reduction of signal-to-interference ratio (SIR) due to imperfect frequency synchronization. Link level simulation (LLS) urges that our proposed technique has improved performance.