Inter-satellite links (ISLs), the essential part of global navigation satellite systems (GNSS), enhance the autonomy and flexibility of the constellation under the minimal distribution of reference monitoring stations. ISL is generally designed to cater to ranging, communication and autonav requirements for medium earth orbit (MEO) navigation satellites. ISL assists the communication need by transferring primary navigation parameters and ranging parameters across the satellite constellation at faster rates. The code division multiple access (CDMA) based ranging assists precise orbit de-termination and time-transfer requirements for autonav operation. We propose the radio frequency (RF) ISL system for navigation satellites constellation considering the low data rate requirements and ranging accuracy for orbit determination & autonav requirements. We present the onboard system design of RF ISL with Ka-band active phased array antenna. Inter-plane RF ISLs, which connect satellites from different orbital planes, are greatly dynamic and are considerably affected by the higher Doppler shift. We also present link design for various ISL distances, the required transmit/receive antenna requirements & power amplifier rating, Doppler shift, and the number of ISLs for a given MEO satellite constellation. The proposed RF-ISL provides the ranging accuracy of approximately 13.6 cm for MEO navigation satellite constellation system.

Summary The enormous growth of mobile broadband traffic is a catalyst for expanding terrestrial communication systems and their integration with satellite communication systems. This results in sharing frequencies allocated to satellite communication systems with terrestrial systems. As this can lead to interference between the incumbent and the upcoming service, coexistence studies are conducted. In the case of sharing satellite uplink frequencies with terrestrial communication systems, interference from base stations (BSs) is dominant. While there are methods to estimate the number of BSs that may be deployed, it is unclear where the BSs will be located. The BS locations play a pivotal role in interference calculation, as the values of link budget parameters are highly dependent on the longitude and latitude of interfering transmitters. This article presents an intelligent method which balances network capacity and coverage for simulating base stations (BSs) in coexistence studies. A realistic BS distribution is generated using weighted K‐means clustering (WKMC) algorithm and incorporating population density along with Haversine distance. The paper provides a case study of co‐frequency, co‐coverage interference in the satellite uplink in the C‐band to demonstrate the impact of BS distribution on the results of coexistence studies. This paper will find applications in upcoming frequency sharing and coexistence studies and the design of integrated satellite‐terrestrial communication networks.

In this paper, we revisit the max-product signal-to-interference-plus-noise ratio (SINR) power allocation policy in a cell-free multiple-input multiple-output (MIMO) system that was previously approached using the model and data-driven based methods. We develop a reinforcement learning (RL) algorithm to be employed by all access points to compute their best power allocation profile in real-time. Model-free temporal difference RL algorithms are designed for the max-product SINR power optimization strategy inspired by state-action-reward-state-action (SARSA), Q -learning, and expected SARSA. The proposed algorithms find suboptimal scalable power allocation solutions for cell-free systems with less dependency on the underlying system model and less computational complexity.

Millimeter wave (mmWave) with two way relaying (TWR) is an emerging paradigm towards cellular fifth/sixth generation (5G/6G) technology that can support various data hungry applications with improve coverage, network throughput, and reliability. The foreseen potential of mmWave TWR system can be further alleviated by using large-scale multiple input multiple output (MIMO) architecture. However, high power consumption, hardware complexity and cost of fully digital large-scale MIMO architecture restricts its application. As a countermeasure, hybrid precoding structures with reduced RF chains are utilized. Therefore, the amalgamation of TWR MIMO mmWave system with hybrid precoding structure demands an accurate channel state information (CSI) to avail the maximum gain of two way MIMO communications. Furthermore, the inherent self-interference in TWR systems in collusion with sparse mmWave channels imposes severe challenges in acquiring accurate CSI. The challenge is further aggravated in case of frequency-selective mmWave channel. To solve this problem, we propose a novel iterative variational Bayesian inference (IVBI)-based channel estimation (CE) scheme in the time domain for TWR system with reduced RF chain. In the proposed method, we follow the alternative minimization method involving variational Bayesian inference (VBI) to estimate all the channels of mmWave TWR system. The performance of the proposed algorithm are evaluated over both flat fading and frequency-selective channel. Extensive simulation results for symmetric and non-symmetric MIMO structure validate the proposed algorithm. The Bayesian Cramer-Rao bound (BCRB) of the proposed estimator is also derived. This novel scheme converges fast and achieves significant improvement in terms of normalized mean square error (NMSE) and bit error rate (BER) as compared to state-of-art.

Precoding is an interference cancellation technique which enables aggressive frequency reuse in multibeam satellites thereby increasing the overall system throughput. This paper presents system level trade-off analysis for multibeam high throughput satellites (HTS) which use on-board precoding (OBP). The throughput performance is analysed for a 16-beam Ku band HTS, with and without precoding under different frequency reuse schemes. The payload mass and DC power requirements are also estimated to understand the penalties associated with its on-board implementation as compared to a conventional non-processing HTS.

An in vitro study was carried out to examine the impact of UV exposure on metal-dissolved humic material (M-DHM) complexes in aqueous systems at different pH. Complexation reactions of dissolved M (Cu, Ni, and Cd) with DHM increased with the increasing pH of the solution. Kinetically inert M-DHM complexes dominated at higher pH in the test solutions. Exposure to UV radiation did affect the chemical speciation of M-DHM complexes at different pH of the systems. The overall observation suggests that exposure to increasing UV radiation increased the lability, mobility, and bioavailability of M-DHM complexes in aquatic environments. The dissociation rate constant of Cu-DHM was found to be slower than Ni-DHM and Cd-DHM complexes (both before and after UV exposure). At a higher pH range, Cd-DHM complexes dissociated after exposure to UV radiation and a part of this dissociated Cd precipitated out from the system. No change in the lability of the produced Cu-DHM and Ni-DHM complexes after UV radiation exposure was observed. They did not appear to form new kinetically inert complexes even after 12 h of exposure. The outcome of this research has important global implications. The results of this study helped to understand DHM leachability from soil and its effect on dissolved metal concentrations in the Northern Hemisphere water bodies. The results of this study also facilitated to comprehend the fate of M-DHM complexes at photic depths (where pH changes are accompanied by high UV radiation exposure) in tropical marine/freshwater systems during summer.

The perinatal period is very critical as the embryo or the new born is more susceptible to Cd toxicity. This study was done to measure Cd levels in brain tissue of F1 and F2 generation mice whose mothers were exposed to Cd during lactation or during the entire period of gestation and lactation and also to investigate whether quercetin could modulate this effect. Dams were exposed to cadmium during lactation and during the entire perinatal period. F1 and F2 generations were reared till 100 days of age. After being sacrificed, their brains were extracted, and cadmium levels were estimated using Atomic absorption spectrophotometer. It was found that Cd levels in brain tissue were significantly higher in the F1 generation when animals were exposed in lactation. There was slight increase in Cd in brain tissue of animals exposed during gestation as well as lactation, but the change was not statistically significant. Quercetin reduced the Cd levels significantly in a dose dependent manner in lactation group. In the other two groups it reduced the Cd levels even lower than the controls. This study shows that Cd is passed on to the next generation more efficiently when exposed during lactation. Lesser transmission is seen when exposure is during gestation followed by lactation. Quercetin effectively reduces Cd levels in brain tissue irrespective of the type of exposure.

This is the first study to comprehend copper (Cu)-dynamics in a monsoon fed Indian estuarine system (the Mandovi estuary from the central west coast of India). Distribution and speciation of Cu in estuarine sediment, pore water, suspended particulate matter (SPM) and water column was used to understand geochemical cycling of Cu in the estuary. Geochemical fractionation study reveals that sedimentary organic carbon (Corg) was the major hosting phase for non-residual Cu in the sediments. Experimental analysis and chemical speciation modelling suggests that leaching of sedimentary Cu2+, CuCO3 and a fraction of Cu-Corg complexes increased Cu-concentrations in the pore water towards the downstream of the estuary. Dissolved Cu concentration in overlying water column was observed to increase with increasing Cu concentrations in the pore water. This study suggests that chemical speciation of sedimentary Cu play key role in controlling its distribution and dynamics in the tropical estuarine system during dry period.

Cell-free Massive MIMO systems consist of a large number of geographically distributed access points (APs) that serve the users by coherent joint transmission.The spectral efficiency (SE) achieved by each user depends on the power allocation: which APs that transmit to which users and with what power.In this article, we revisit the max-min and sum-SE power allocation policies, which have previously been approached using high-complexity general-purpose solvers.We develop and compare several different high-performance low-complexity power allocation algorithms that are appropriate for use in large systems.We propose two new algorithms for sum-SE power optimization inspired by weighted minimum mean square error (WMMSE) minimization and fractional programming (FP).Further, one new FP-based algorithm is proposed for max-min fair power allocation.The alternating direction method of multipliers (ADMM) is used to solve specific convex subproblems in the proposed algorithms.Our ADMM reformulations lead to multiple small-sized subproblems with closed-form solutions.The proposed algorithms find global or local optimal power allocation solutions for large-scale systems but with reduced computational time compared to previous work.

India is industrializing rapidly and with this there comes higher releases of contaminants into the environment. Change in Pb deposition over the last century on the eastern (off Andhra Pradesh) and western (off Karnataka) shelves of India was investigated based on the data extracted from two sediment cores covering the past ~114 and ~145 yrs. The variations of the total Pb content, its enrichment factor, and concentrations of non-residual Pb in both the sediment cores document that there was a gradual increase in anthropogenic Pb input into the coastal sediments of India over the last century. Sediment leachates were used to monitor the increase in anthropogenic Pb input and its Pb isotope composition. The anthropogenic end member composition of the western shelf sediment location (206Pb/207Pb: 1.105; 206Pb/208Pb: 2.149) was significantly less radiogenic than the eastern shelf isotopic composition (206Pb/207Pb: 1.145; 206Pb/208Pb:2.120). A binary mixing model suggests that Pb emitted from the heavy industries (e.g., ore mining, Pb processing and smelting plants) of India has been the major source of anthropogenic Pb to the sediments of western continental shelf. In contrast, the isotopic signatures suggest that coal combustion is responsible for elevated anthropogenic Pb levels in the sediments from the eastern shelf of India.

The corona virus-2019 (COVID-19) is ravaging the whole world. Scientists have been trying to acquire more knowledge on different aspects of COVID-19. This study attempts to determine the effects of COVID-19, on a large population, which has already been persistently exposed to various atmospheric pollutants in different parts of India. Atmospheric pollutants and COVID-19 data, obtained from online resources, were used in this study. This study has shown strong positive correlation between the concentration of atmospheric nitrogen dioxide (NO 2 ) and both the absolute number of COVID-19 deaths (r = 0.79, p < 0.05) and case fatality rate (r = 0.74, p < 0.05) in India. Statistical analysis of the amount of annual fossil fuels consumption in transportation, and the annual average concentration of the atmospheric PM 2.5 , PM 10 , NO 2 , in the different states of India, suggest that one of the main sources of atmospheric NO 2 is from fossil fuels combustion in transportation. It is suggested that homeless, poverty-stricken Indians, hawkers, roadside vendors, and many others who are regularly exposed to vehicular exhaust, may be at a higher risk in the COVID-19 pandemic.

This study provides the first, preliminary data on geochemical distribution and fractionation of Pb (a toxic heavy metal) in continental shelf sediments around India and identifies the factors that control geochemical fractionation processes of Pb in convoluted coastal marine sediments. For the sake of clarity, the long coastline (similar to 7,000km) of India was divided into 6 coastal regions in this study. The total concentration of sedimentary Pb showed regional variation along the coast. The highest median concentration of Pb was found in the sediments collected from the north-east region (26.5 mg/kg) followed by the north-west (21.4mg/kg)>central-east (20.6 mg/kg) > south-west (13.7mg/kg)>south-east (13.3mg/kg)>central-west (12.5mg/kg) regions. Geochemical fractionation study suggested that the concentration of sedimentary Fe-Mn in oxyhydroxide form and the nature of sedimentary organic matters determined the geochemical distribution and fractionation of Pb in the shelf sediments. The major Pb hosting phases in the shelf sediments were the Fe-Mn oxyhydroxide phase followed by the sedimentary organic matter binding phases. The concentration of nonresidual Pb complexes in the shelf sediment was found to depend on the total sedimentary Pb loading. This study suggests that increase of anthropogenic Pb input and expansion of reduced oxygen levels in the coastal marine environment may have detrimental effects on the increasing mobility and bioavailability of Pb in the coastal areas around India.

The increased exposure to cadmium (Cd) through environmental pollutants, food and cigarette smoke is a concern worldwide. The association of Cd with impaired learning disabilities led us to hypothesise that cadmium levels in brain tissue could be dose-dependently related to the extent of memory impairment and oxidative stress. In this study, we proposed to study whether cadmium exposure to dams could alter the brain Cd levels, memory parameters, antioxidant enzymes in brain and their gene expression in the F1-F2 generation mice and whether quercetin could modulate this effect. Animals were administered Cd alone and in combination with quercetin for 7 days during their gestation period. Their newborn pups (F1 and F2 mice) were reared until adulthood and were tested for memory using Morris water maze and step-down latency test. The brain tissue of F1 mice was collected. Cd levels were estimated using the atomic absorption spectrophotometer. G-S-transferase (GST) and catalase (CAT) activity were measured and fold increase in their respective gene expression was observed using the RT-PCR method. Cd levels were significantly increased in the brain tissue of animals exposed to Cd but cotreatment with quercetin showed decreased levels in both generations. Memory impairment was observed in animals of F1 generation exposed to Cd and cotreatment with quercetin (100 mg/kg) reversed this effect. Cd exposure significantly enhanced both activity and expression of GST and CAT in the brain tissue of F1 generation mice and quercetin attenuated this effect. In F2 generation, results were variable. GST activity and expression increased with Cd and decreased with quercetin cotreatment. However, CAT activity showed no significant change despite a decrease in gene expression. Quercetin cotreatment enhanced activity as well gene expression in F2 generation. Our study insinuates that Cd levels could act as a predictor of memory impairment and altered enzyme activity and gene expression in brain tissue. Quercetin helped to reduce Cd levels in brain tissue of F1 and F2 generation and modulated the antioxidant system of the cell by affecting expression of antioxidant enzymes at the transcription level.

Cell-free Massive MIMO systems consist of a large number of geographically distributed access points (APs) that serve users by coherent joint transmission. Downlink power allocation is important in these systems, to determine which APs should transmit to which users and with what power. If the system is implemented correctly, it can deliver a more uniform user performance than conventional cellular networks. To this end, previous works have shown how to perform system-wide max-min fairness power allocation when using maximum ratio precoding. In this paper, we first generalize this method to arbitrary precoding, and then train a neural network to perform approximately the same power allocation but with reduced computational complexity. Finally, we train one neural network per AP to mimic system-wide max-min fairness power allocation, but using only local information. By learning the structure of the local propagation environment, this method outperforms the state-of-the-art distributed power allocation method from the Cell-free Massive MIMO literature.

Full-duplex two-way relay (FD-TWR) system has potential to increase the spectral efficiency in the future 5G wireless system. Full-duplex transceiver suffers from inevitable self-interference (SI) which can be alleviated by active self-interference cancellation (SIC) method. However, the mitigation capability of SIC mechanism is limited specifically due to inherent non-linearities of transmitter and receiver front end. As a consequence, residual self-interference (RSI) will degrade the system's signal-to-noise ratio (SNR) and throughput. Non-linearity in RF power amplifier in collusion with time-variant channel results is a great challenge in efficient signal detection and successful SI suppression. In contrast to classical schemes, which consider non-linear distortion at the transmitter, we present a semi-blind data detection and non-linear channel estimation in the presence of RSI at the receiver. Attributed to non-linearity, the target posterior probability density function is mathematically intractable. In this paper, a sequential importance sampling based particle filtering is used for joint data detection and estimation. Intractable distribution is approximated by using weighted random measures. A Taylor's series expansion is used to locally linearize the non-analytic form of distribution. Numerical results validate the joint detection and channel estimation scheme. The robustness of the scheme is verified in presence of RSI under high mobility.

Two-way relay network based on full-duplex technique has the potential to enhance the spectral efficiency significantly, and increase capacity in future 5G mobile communication systems. However, the self-interference of full-duplex communication severely limits the performance of a two-way relay network. The cancellation of self-interference for multi-relay full-duplex two-way relay systems in highly mobile environment is very challenging due to time-frequency doubly selective channel on the one hand and multiple carrier frequency offsets on the other hand. In this paper, we propose a novel semi-blind estimator to jointly estimate multiple carrier frequency offsets and doubly selective self-interference channels in highly mobile two-way relay systems with orthogonal frequency-division multiplexing modulation in the presence of residual self-interference. We use discrete prolate spheroidal basis expansion model to capture rapid time variations of the channel. The proposed iterative space-alternating generalized expectation maximization-based semi-blind algorithm uses received data symbols along with received pilot symbols to obtain improved frequency offsets and channel estimate with significantly less number of pilot overhead. The proposed estimator converges in almost two iterations and achieves significant improvement over the pilot-based method. The Cramer-Rao lower bounds of the semi-blind joint estimation are also derived.

Impact of pH variation of overlying water column on transport and transformation of Cu-sediment complexes in the bottom mangrove sediments was investigated by using different metal extraction studies. The total Cu concentration in the studied sediments varied from similar to 64 +/- 1 to 78 +/- 2 mg.kg(-1). The sequential extraction study showed that a major part of the sedimentary Cu (85-90% of the total sedimentary Cu) was present within the structure of the sediments with minimum mobility and bioavailability. The redistribution of non-residual Cu among the different binding phases of the sediments was observed at different pH. It was found that Cu shifted from the different non-residual binding phases to the organic binding phase of the sediments at higher pH. Partial leaching of sedimentary Cu-SOM complexes (with increasing stability as determined by kinetic extraction study) was observed at higher pH. This study infers that increase in pH of overlying water column may release Cu-SOM complexes and increase the mobility of Cu-complexes in mangrove systems.

Millimeter wave (mm-Wave) is an emerging paradigm towards 5G technology that can support high data rate. The foreseen potential of mm-Wave is limited by huge path loss incurred due to the high frequency operation which can be alleviated by high emission power at the transmitter. This in concurrence with the enormous bandwidth of mmWave and high frequency design limitations of the integrated circuits enforce the power amplifier (PA) into non-linear region. Further, the non-linear distortion in collusion with frequency selective channel and carrier frequency offset (CFO) degrade the signal detection performance. To solve this problem, we propose a semi-blind joint estimation of CFO and frequency selective channel gains followed by data detection in the presence of PA non-linearity. The presence of non-linearity results in the posterior probability distribution of complex data symbol to be non-Gaussian and hence, analytically intractable. Therefore, sequential importance resampling based particle filter (PF) is suggested for approximating the intractable posterior distribution of interest by the weighted random probability samples (particles) to detect the data symbols. The detected symbols are then used to jointly update the channel gains and CFO using a novel sequential maximum likelihood (ML) estimation. Extensive simulation results validate the proposed algorithm. This novel scheme enhances the non-linear signal detection performance in presence of CFO and frequency selective channel at the receiver.

This study suggests that varying concentration of dissolved oxygen of overlying bottom water influences geochemical fractionation, speciation, and oxidation state of sedimentary Cr in a marine system. The nature of sedimentary organic matter (labile or nonlabile) and Fe speciation also controls the geochemical fractionation and oxidation state of Cr in the sediment from the continental margin across the oxygen minimum zone of the Arabian Sea. Increasing concentration of sedimentary organic matter (under hypoxic conditions) increased association of Cr with sedimentary organic binding phases. The association of Cr with Fe‐Mn‐oxyhydroxide phase gradually decreased with decreasing dissolved oxygen concentration due to the reduction and dissolution of Fe (III). The sedimentary organic matter was found to be the major hosting phase for Cr (VI) in the shelf sediments. The decrease in sedimentary Fe (III) concentration under hypoxic conditions also prevented Cr (VI) reduction. This study suggests that the type of sedimentary organic matter and Fe (III) concentration may influence benthic exchange fluxes of Cr under variable redox conditions in many coastal/margin systems.

Distributed multiple-input multiple-output (DMIMO) system with orthogonal frequency division multiplexing (OFDM) modulation is an emerging paradigm for high data rate and cell coverage extension. In order to make the paradigm shift from conventional network to intelligent DMIMO-OFDM systems, one must address the fundamental bottleneck in synchronization and channel estimation for coherent reception. The involvement of multiple cooperative nodes increases the number of corresponding channels and synchronization impairments to be estimated in comparison with collocated multiple input multiple output (MIMO) systems. As a consequence, the traditional pilot-based estimator requires a large pilot overhead to effectively estimate multiple impairments. This paper presents semi-blind space alternating generalized expectation maximization (SB-SAGE) algorithm for jointly estimating the multiple carrier frequency offsets (MCFOs) and frequency-selective channel gains in DMIMO-OFDM systems. SB-SAGE estimator uses soft information of partially received data symbols along with pilot symbols to obtain improved MCFOs and channel estimates with significantly reduced length of pilot overhead. It also increases spectral efficiency of the systems. The proposed estimator converges in almost two iterations and achieves significant improvement over pilot-based methods.