A Review of MAC Scheduling Algorithms in LTE System

The recent wireless communication networks rely on the new technology named Long Term Evolution (LTE) to offer high data rate real-time (RT) traffic with better Quality of Service (QoS) for the increasing demand of customer requirement. LTE provide low latency for real-time services with high throughput, with the help of two-level packet retransmission. Hybrid Automatic Repeat Request (HARQ) retransmission at the Medium Access Control (MAC) layer of LTE networks achieves error-free data transmission. The performance of the LTE networks mainly depends on how effectively this HARQ adopted in the latest communication standard, Universal Mobile Telecommunication System (UMTS). The major challenge in LTE is to balance QoS and fairness among the users. Hence, it is very essential to design a down link scheduling scheme to get the expected service quality to the customers and to utilize the system resources efficiently. This paper provides a comprehensive literature review of LTE MAC layer and six types of QoS/Channel-aware downlink scheduling algorithms designed for this purpose. The contributions of this paper are to identify the gap of knowledge in the downlink scheduling procedure and to point out the future research direction. Based on the comparative study of algorithms taken for the review, this paper is concluded that the EXP Rule scheduler is most suited for LTE networks due to its characteristics of less Packet Loss Ratio (PLR), less Packet Delay (PD), high throughput, fairness and spectral efficiency

Hybrid Micro Genetic Algorithm Assisted Optimum Detector for Multi-Carrier Systems

A low-complexity detection scheme, which consists of a Hybrid Micro Genetic Algorithm (Hybrid- µGA), is proposed for Orthogonal Frequency Division Multiplexing (OFDM) systems. In the absence of orthogonality, intercarrier-interference (ICI) occurs because a signal from one subcarrier causes interference to others. In several environment, the OFDM signal reflections from a far obstacle generate inter-block-interference (IBI) due to long time delays. To avoid these unpleasant effects of IBI and ICI in OFDM system, a Hybrid-µGA detection algorithm is proposed. The proposed detector combines the conventional one-Tap equalizer and the Micro Genetic Algorithm (µGA) search engine. The output of one-Tap equalizer is considered as the input to µGA search engine. Therefore, the µGA starts with some knowledge rather than blindly to speed up the search. Theoretical analysis and simulation results show that the proposed detection Hybrid- µGA scheme substantially improves the performance of OFDM systems. Moreover, its complexity is 10 times lower than the conventional GA

Procedures to view aberrations-A travel from protein to gene: Literature review

The diagnosis of any pathology is fundamentally based on the microscopic structure of cells and tissues and this remains as the standard by which all other diagnostic tests are measured. In this era, the pathologists are relying on the examination of tissue section stained by histochemical means and it is supported by the advanced immunological, biochemical and molecular techniques. This review will provide the information about one of the way that can be followed to unravel the molecular mechanism in spotting the disease process. Technologies used to study the cellular process are same for the normal and the abnormal cell. Experimental strategy briefed here is also applicable for both. The cellular process can be studied either from protein to gene or from gene to protein. Earlier days biochemical analysis (isolation of protein, protein sequencing) was separate and genetic analysis (genomic mapping) was separate. But now with advent of recombinant DNA technology it is possible to have a link between the biochemical and genetic analysis. Intermediary step of development of oligonucleotide synthesis, complementary DNA probe and cloning has revolutionized the research process. Identified gene can be compared with the normal gene by comparative genomics or expressed proteins by expression proteomics