Hybrid precoding techniques are lately involved a lot of interest for millimeter-wave (mmWave) massive MIMO systems is due to the cost and power consumption advantages they provide. However, existing hybrid precoding based on the singular value decomposition (SVD) necessitates a difficult bit allocation to fit the varying signal-to-noise ratios (SNRs) of altered sub-channels. In this paper, we propose a generalized triangular decomposition (GTD)-based hybrid precoding to avoid the complicated bit allocation. The development of analog and digital precoders is the reason for the high level of design complexity in analog precoder architecture, which is based on the OMP algorithm, is very non-convex, and so has a high level of complexity. As a result, we suggest using the GTD method to construct hybrid precoding for mmWave mMIMO systems. Simulated studies as various system configurations are used to examine the proposed design. In addition, the archived findings are compared to a hybrid precoding approach in the classic OMP algorithm. The proposed Matrix Decomposition’s simulation results of signal-to-noise ratio vs spectral efficiencies.

Queuing regime is one outstanding approach in improving channel aggregation. If well designed and incorporated with carefully selected parameters, it enhances the smooth rollout of fifth/next generation wireless networks. While channel aggregation is the merging of scattered TV white space (spectrum holes) into one usable chunk for secondary users (SU). The queuing regime ensures that these unlicensed users (SUs) traffic/ services are not interrupted permanently (blocked/dropped or forced to terminate) in the event of the licensed users (primary user) arrival. However, SUs are not identical in terms of traffic class and bandwidth consumption hence, they are classified as real time and non-real time SU respectively. Several of these strategies have been studied considering queuing regime with a single feedback queuing discipline. In furtherance to previous proposed work with single feedback queuing regime, this paper proposes, develops and compares channel aggregation policies with two feedback queuing regimes for the different classes of SUs. The investigation aims at identifying the impacts of the twofeedback queuing regime on the performance of the secondary network such that any SU that has not completed its ongoing service are queued in their respective buffers. The performance is evaluated through a simulation framework. The results validate that with a well-designed queuing regime, capacity, access and other indices are improved with significant decrease in blocking and forced termination probabilities respectively.

Retinitis pigmentosa is a genetic disorder that results in nyctalopia and its progression leads to complete loss of vision. The analysis and the study of retinal images are necessary, so as to help ophthalmologist in early detection of the retinitis pigmentosa. In this paper fundus images and Optical Coherence Tomography images are comprehensively analyzed, so as to obtain the various morphological features that characterize the retinitis pigmentosa. Pigment deposits, important trait of RP is investigated. Degree of darkness and entropy are the features used for analysis of PD. The darkness and entropy of the PD is compared with the different regions of the fundus image which is used to detect the pigments in the retinal image. Also the performance of the proposed algorithm is evaluated by using various performance metrics. The performance metrics are calculated for all 120 images of RIPS dataset. The performance metrics such as sensitivity, sensibility, specificity, accuracy, F-score, equal error rate, conformity coefficient, Jaccard’s coefficient, dice coefficient, universal quality index were calculated as 0.72, 0.96, 0.97, 0.62, 0.12, 0.09, 0.59, 0.45 and 0.62, respectively.