Comparison between scheduling techniques in long term evolution

Long-Term Evolution (LTE) is a recently evolving technology characterized by very high speed data rate that allows users to access internet through their mobile as well as through other electronic devices. Such technology is intended to support variety of IP-based heterogeneous traffic types. Traffic scheduling plays an important role in LTE technology by assigning the shared resources among users in the most efficient manner. This paper discusses the performance of three types of scheduling algorithms namely: Round Robin, best Channel Quality Indicator (CQI) and Proportional Fair (PF) schedulers representing the extreme cases in scheduling. The scheduling algorithms performances on the downlink were measured in terms of throughput and block error rate using a MATLAB-based system level simulation. Results indicate that the best CQI algorithm outperforms other algorithms in terms of throughput levels but on the expense of fairness to other users suffering from bad channel conditions

Comparison between Scheduling Techniques in Long Term Evolution

Long-Term Evolution (LTE) is a recently evolving technology characterized by very high speed data rate that allows users to access internet through their mobile as well as through other electronic devices.  Such technology is intended to support variety of IP-based heterogeneous traffic types. Traffic scheduling plays an important role in LTE technology by assigning the shared resources among users in the most efficient manner. This paper discusses the performance of three types of scheduling algorithms namely: Round Robin, best Channel Quality Indicator (CQI) and Proportional Fair (PF) schedulers representing the extreme cases in scheduling. The scheduling algorithms performances on the downlink were measured in terms of throughput and block error rate using a MATLAB-based system level simulation. Results indicate that the best CQI algorithm outperforms other algorithms in terms of throughput levels but on the expense of fairness to other users suffering from bad channel conditions. ABSTRAK: Teknologi baru Evolusi Jangka Panjang (LTE) sentiasa berubah dan ia bercirikan kelajuan kadar data sangat tinggi yang membolehkan pengguna mengakses internet melalui telefon bimbit dan peranti elektronik lain. Teknologi seperti ini bertujuan menyokong pelbagai jenis trafik heterogen berasaskan IP. Penjadualan trafik memainkan peranan penting dalam teknologi LTE bagi mengagihkan sumber perkongsian secara paling berkesan di kalangan pengguna. Kertas ini membincangkan prestasi tiga jenis algoritma penjadualan iaitu: pusingan Robin, penunjuk kualiti saluran (CQI) terbaik dan  penjadualan berkadar adil (PF) yang merupakan kes ekstrem dalam penjadualan. Prestasi penjadualan Algoritma di pautan turun diukur dari segi daya pemprosesan dan kadar ralat blok melalui simulasi  sistem menggunakan MATLAB. Hasil kajian menunjukkan algoritma CQI adalah yang terbaik berbanding hasil algoritma lain dari segi tahap daya pemprosesan tetapi algoritma ini menyebabkan pengguna lain mengalami keadaan saluran buruk. KEYWORDS: LTE; round robin; best CQI; proportional fair; scheduling; resource block

Identification of genetic risk loci and causal insights associated with Parkinson\u27s disease in African and African admixed populations: a genome-wide association study

\ua9 2023 Elsevier LtdBackground: An understanding of the genetic mechanisms underlying diseases in ancestrally diverse populations is an important step towards development of targeted treatments. Research in African and African admixed populations can enable mapping of complex traits, because of their genetic diversity, extensive population substructure, and distinct linkage disequilibrium patterns. We aimed to do a comprehensive genome-wide assessment in African and African admixed individuals to better understand the genetic architecture of Parkinson\u27s disease in these underserved populations. Methods: We performed a genome-wide association study (GWAS) in people of African and African admixed ancestry with and without Parkinson\u27s disease. Individuals were included from several cohorts that were available as a part of the Global Parkinson\u27s Genetics Program, the International Parkinson\u27s Disease Genomics Consortium Africa, and 23andMe. A diagnosis of Parkinson\u27s disease was confirmed clinically by a movement disorder specialist for every individual in each cohort, except for 23andMe, in which it was self-reported based on clinical diagnosis. We characterised ancestry-specific risk, differential haplotype structure and admixture, coding and structural genetic variation, and enzymatic activity. Findings: We included 197 918 individuals (1488 cases and 196 430 controls) in our genome-wide analysis. We identified a novel common risk factor for Parkinson\u27s disease (overall meta-analysis odds ratio for risk of Parkinson\u27s disease 1\ub758 [95% CI 1\ub737–1\ub780], p=2\ub7397 7 10−14) and age at onset at the GBA1 locus, rs3115534-G (age at onset β=–2\ub700 [SE=0\ub757], p=0\ub70005, for African ancestry; and β=–4\ub715 [0\ub758], p=0\ub7015, for African admixed ancestry), which was rare in non-African or non-African admixed populations. Downstream short-read and long-read whole-genome sequencing analyses did not reveal any coding or structural variant underlying the GWAS signal. The identified signal seems to be associated with decreased glucocerebrosidase activity. Interpretation: Our study identified a novel genetic risk factor in GBA1 in people of African ancestry, which has not been seen in European populations, and it could be a major mechanistic basis of Parkinson\u27s disease in African populations. This population-specific variant exerts substantial risk on Parkinson\u27s disease as compared with common variation identified through GWAS and it was found to be present in 39% of the cases assessed in this study. This finding highlights the importance of understanding ancestry-specific genetic risk in complex diseases, a particularly crucial point as the Parkinson\u27s disease field moves towards targeted treatments in clinical trials. The distinctive genetics of African populations highlights the need for equitable inclusion of ancestrally diverse groups in future trials, which will be a valuable step towards gaining insights into novel genetic determinants underlying the causes of Parkinson\u27s disease. This finding opens new avenues towards RNA-based and other therapeutic strategies aimed at reducing lifetime risk of Parkinson\u27s disease. Funding: The Global Parkinson\u27s Genetics Program, which is funded by the Aligning Science Across Parkinson\u27s initiative, and The Michael J Fox Foundation for Parkinson\u27s Research