Statistical analysis and channel modeling in next generation wireless communication systems

In this thesis, statistical analysis and channel modeling in next generation wireless communication systems is presented in detail. The primary focus of this thesis is on the statistical modeling of interference temperature (IT) in cognitive radio systems, and empirical study of wireless channel characterization of unmanned aerial vehicle (UAV)-assisted communications at ultra-wideband (UWB) and at millimeter wave (mmWave) frequencies.Firstly, in the cognitive radio system, a novel idea to statistically model the dynamic interference threshold (IT) from user traffic demand is presented in detail. It is shown that the cognitive radio system with dynamic IT will have high capacity performance with less outage probability over a system that does not utilize dynamic IT. The detailed theoretical analysis with expressions for mean capacity and outage probability in general operation region, and in high power region are derived and subsequently, validated with the simulations results. In addition, the effect of secondary user interference on primary user is also examined in this part.In the second part, wireless channel characterisation for unmanned aerial vehicle-to-wearables (UAV2W) at UWB frequency is analysed, and studied empirically in an indoor warehouse environment. The frequency and distance dependent path gain analysis at different bandwidths for a corresponding carrier frequency with time dispersion characteristics is presented in detail. Furthermore, from statistical modeling, it was shown that the Log-normal distribution is the best fit distribution model to characterize fading in these UAV2W systems.Finally, a novel emulation method for UAV motion by a robotic arm is presented to study the mmWave channel characteristics (Doppler spreading and path loss) at 28 GHz. In addition to that, empirical study is carried out to analyze the propeller modulation effect caused by the propellers in UAVs with an actual UAV setup. These important statistical analysis, and channel modeling discussed in this thesis are very critical in designing, analysing, and in implementation of fifth generation (5G) and beyond 5G (B5G) communication for the future. This thesis is a stepping stone in that direction

Unmanned aerial vehicle-to-wearables (UAV2W) indoor radio propagation channel measurements and modeling

In this paper, off-body ultra-wide band (UWB) channel characterization and modeling are presented between an unmanned aerial vehicle (UAV) and a human subject. The wearable antenna was patched at nine different body locations on a human subject during the experiment campaign. The prime objective of this work was to study and evaluate the distance and frequency dependent path loss factors for different bandwidths corresponding to various carrier frequencies, and also look into the time dispersion properties of such unmanned aerial vehicle-to-wearables (UAV2W) system. The environment under consideration was an indoor warehouse with highly conductive metallic walls and roof. Best fit statistical analysis using Akaike Information Criteria revealed that the Log-normal distribution is the best fit distribution to model the UWB fading statistics. The study in this paper will set up a road map for future UAV2W studies to develop enhanced retail and remote health-care monitoring/diagnostic systems

Extended reduced-rank joint estimation of direction of arrival with mutual coupling for coherent signals

This paper proposes an extended method for direction-of-arrival (DOA) estimation with unknown mutual coupling for coherent signals. The proposed method employs the forward/backward spatial smoothing to decorrelate the coherent signals in the process of rank reduction with the joint iterative subspace optimization approach. Then, the autocalibration of mutual coupling is performed based on the Capon's minimum variance criterion. Performance of the proposed method is compared with the state of the art algorithms in terms of DOA root-mean-square error and in terms of probability of successful estimation, where successful estimation is the case when the average of absolute DOA estimation error is within 2.5°. It is shown that the proposed method has a similar performance as the state of the art autocalibration methods while offering a lower computational complexity

Optimization of lte radio resource block allocation for maritime channels

In this study, we describe the behavior of LTE over the sea and investigate the problem of radio resource block allocation in such SINR limited maritime channels. For simulations of such sea environment, we considered a network scenario of Bosphorus Strait in Istanbul, Turkey with different number of ships ferrying between two ports at a given time. After exploiting the network characteristics, we formulated and solved the radio resource allocation problem by max-min integer linear programming method. The radio resource allocation fairness in terms of Jain's fairness index was computed and it was compared with round robin and opportunistic methods. Results show that the max-min optimization method performs better than the opportunistic and round robin methods. This result in turn reflects that the max-min optimization method gives us the high minimum best throughput as compared to other two methods considering different ship density scenarios in the sea. Also, it was observed that as the number of ships begin to increase in the sea, the max-min method performs significantly better with good fairness as compared to the other two methods

Reduced-rank joint estimation of DOA with mutual coupling

In this paper, an extended reduced-rank direction-of-arrival (DOA) estimation with unknown mutual coupling in uniform linear array (ULA) structure is presented. The proposed method is based on the joint iterative subspace optimization (JIO) and the auto-calibration of mutual coupling. Given an initial coupling vector, reduced-rank correlation matrix is estimated with the JIO approach, followed by iterative joint estimation of DOA and coupling with an auto-calibration algorithm. Simulation results show that both the proposed method and the existing auto-calibration method have similar performance in terms of DOA root mean square error, while the complexity of the proposed method is much lower than that of the auto-calibration approach due to the reduced rank

Interference Spreading through Random Subcarrier Allocation Technique and Its Error Rate Performance in Cognitive Radio Networks

In this letter, we investigate the idea of interference spreading and its effect on bit error rate (BER) performance in a cognitive radio network (CRN). The interference spreading phenomenon is caused because of the random allocation of subcarriers in an orthogonal frequency division multiplexing (OFDM)-based CRN without any spectrum-sensing mechanism. The CRN assumed in this work is of underlay configuration, where the frequency bands are accessed concurrently by both primary users (PUs) and secondary users (SUs). With random allocation, subcarrier collisions occur among the carriers of primary users (PUs) and secondary users (SUs), leading to interference among subcarriers. This interference caused by subcarrier collisions spreads out across multiple subcarriers of PUs rather than on an individual PU, therefore avoiding high BER for an individual PU. Theoretical and simulated signal to interference and noise ratio (SINR) for collision and no-collision cases are validated for M-quadrature amplitude modulation (M-QAM) techniques. Similarly, theoretical BER performance expressions are found and compared for M-QAM modulation orders under Rayleigh fading channel conditions. The BER for different modulation orders of M-QAM are compared and the relationship of average BER with interference temperature is also explored further

Diagnostic accuracy of xpert test in tuberculosis detection: A systematic review and meta-analysis

Background: World Health Organization (WHO) recommends the use of Xpert MTB/RIF assay for rapid diagnosis of tuberculosis (TB) and detection of rifampicin resistance. This systematic review was done to know about the diagnostic accuracy and cost-effectiveness of the Xpert MTB/RIF assay. Methods: A systematic literature search was conducted in following databases: Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Reviews, MEDLINE, PUBMED, Scopus, Science Direct and Google Scholar for relevant studies for studies published between 2010 and December 2014. Studies given in the systematic reviews were accessed separately and used for analysis. Selection of studies, data extraction and assessment of quality of included studies was performed independently by two reviewers. Studies evaluating the diagnostic accuracy of Xpert MTB/RIF assay among adult or predominantly adult patients (≥14 years), presumed to have pulmonary TB with or without HIV infection were included in the review. Also, studies that had assessed the diagnostic accuracy of Xpert MTB/RIF assay using sputum and other respiratory specimens were included. Results: The included studies had a low risk of any form of bias, showing that findings are of high scientific validity and credibility. Quantitative analysis of 37 included studies shows that Xpert MTB/RIF is an accurate diagnostic test for TB and detection of rifampicin resistance. Conclusion: Xpert MTB/RIF assay is a robust, sensitive and specific test for accurate diagnosis of tuberculosis as compared to conventional tests like culture and microscopic examination