Performance Evaluation of Downlink Coordinated Multipoint Joint Transmission under Heavy IoT Traffic Load

Emerging 5G network cellular promotes key empowering techniques for pervasive IoT. Evolving 5G-IoT scenarios and basic services like reality augmented, high dense streaming of videos, unmanned vehicles, e-health, and intelligent environments services have a pervasive existence now. These services generate heavy loads and need high capacity, bandwidth, data rate, throughput, and low latency. Taking all these requirements into consideration, internet of things (IoT) networks have provided global transformation in the context of big data innovation and bring many problematic issues in terms of uplink and downlink (DL) connectivity and traffic load. These comprise coordinated multipoint processing (CoMP), carriers’ aggregation (CA), joint transmissions (JTs), massive multi-inputs multi-outputs (MIMO), machine-type communications, centralized radios access networks (CRAN), and many others. CoMP is one of the most significant technical enhancements added to release 11 that can be implemented in heterogonous networks implementation approaches and the homogenous networks’ topologies. However, in a massive 5G-IoT device scenario with heavy traffic load, most cell edge IoT users are severely suffering from intercell interference (ICI), where the users have poor signal, lower data rates, and limited QoS. This work is aimed at addressing this problematic issue by proposing two types of DL-JT-CoMP techniques in 5G-IoT that are compliant with release 18. Downlink JT-CoMP with two homogeneous network CoMP deployment scenarios is considered and evaluated. The scenarios used are IoT intrasite and intersite CoMP, which performance evaluated using downlink system-level simulator for long-term evolution-advanced (LTE-A) and 5G. Numerical simulation scenarios were results under high dense scenario—with IoT heavy traffic load which shows that intersite CoMP has better empirical cumulative distribution function (ECDF) of average UE throughput than intrasite CoMP approximately 4%, inter-site CoMP has better ECDF of average user entity (UE) spectral efficiency than intrasite CoMP almost 10%, and intersite CoMP has approximately same ECDF of average signal interference noise ratio (SINR) as intrasite CoMP and intersite CoMP has better fairness index than intrasite CoMP by 5%. The fairness index decreases when the users’ number increase since the competition among users is higher.

Efficient Load Balancing Algorithm in Long Term Evolution (LTE) Heterogeneous Network Based on Dynamic Cell Range Expansion Bias

The traditional scheme for load balancing in a homogeneous Long Term Evolution (LTE) Network where User Equipment (UEs) associate to a node with the strongest received signal strength is not practical for LTE Heterogeneous Network (LTE HetNet) due to power disparity between the nodes. Therefore, dynamic Cell Range Expansion (CRE) based load-balancing schemes were employed by several scholars to address the challenges in the LTE HetNet. However, the fairness index in achieving the desired average user throughput and UE offloading effect is relatively low. In this work, an efficient load-balancing algorithm for LTE HetNet based on dynamic Cell Range Expansion (CRE) was developed to improve the fairness of the network for the desired throughput and UE offloading effect. The simulation results achieve a throughput gain improvement of up to 11%, while the fairness index improves by 6% compared to the existing algorithm. Further, the UEs offloading effect shows a significant improvement of 3% relative to the existing algorithm. Keywords: Fairness Index; Cell Range Expansion; Load Balancing; LTE Heterogeneous Network; Throughput

Alokasi Daya Kirim pada Visible Light Communication menggunakan Algoritma Waterfilling

ABSTRAKPeningkatan terhadap kebutuhan akses data membuat Visible Light Communication (VLC) menjadi alternatif media transmisi nirkabel yang efisien. Namun berdasarkan performansinya, VLC memiliki permasalahan data rate yang tidak merata diterima oleh User Equipment (UE). Dalam mengatasi permasalahan tersebut, penelitian ini menerapkan alokasi daya kirim dengan algoritma waterfilling yang mampu memberikan keadilan data rate setiap UE berdasarkan nilai kanal. Penelitian ini menggunakan kanal Line Of Sight (LOS) dengan 3 skenario berbeda. Kami menggunakan parameter validasi untuk mengukur setiap kinerja dengan nilai Signal Noise Ratio (SNR), data rate, fairness index dan efisiensi energi. Dari hasil simulasi menggunakan algoritma waterfilling, kami memperoleh nilai fairness index untuk data rate sebesar 100% namun tidak memiliki efisiensi daya. Dengan memodifikasi algorima waterfilling, terjadi penurunan fairness index, SNR serta data rate, tapi memberikan efisiensi energi LED hingga 9%. Dengan demikan, daya yang dipancarkan oleh LED memiliki lifetime yang lebih panjang dengan modified waterfilling.Kata kunci: VLC, Power Allocation, Waterfilling, Fairness. ABSTRACTThe increase in the need for data access makes Visible Light Communication (VLC) an alternative wireless transmission medium that is efficient. However, based on its performance, VLC has a data rate problem that is not evenly accepted by User Equipment (UE). In overcoming this problem, this study applies power allocation with waterfilling algorithm that is able to provide fair data rate for each UE based on channel value. This study uses the Line Of Sight (LOS) channel with 3 different scenarios. We use validation parameters to measure each performance using the Signal Noise Ratio (SNR) value, data rate, fairness index and energy efficiency. From the results of simulation using the waterfilling algorithm, we obtain a fairness index value for the data rate of 100% but does not have a power efficiency. By modifying the waterfilling algorithm, there is a decrease in the fairness index, SNR and data rate, but provide LED energy efficiency of up to 9%. Thus, the power emitted by the LED has a longer lifetime with modified waterfilling algorithm.Keywords: VLC, Power Allocation, Waterfilling, Fairness.

Improving Fairness in IEEE 802.11 EDCA Ad Hoc Networks Based on Fuzzy Logic

Wireless ad hoc network is a self-configurable and dynamically distributed network in which stations can move freely. In the ad hoc network, some flows have difficulty in accessing the channel due to contention at both the medium-access control (MAC) and link layers. The IEEE 802.11 protocol is currently the de facto standard for wireless networks. It uses enhanced distributed channel access (EDCA) method to access the transmission environment of each type of data flow. The size of the contention window (CW) in EDCA is related to the probability of accessing the channel of each flow. In our approach, useful information is obtained from the physical, MAC, and link layers. A fuzzy logic system is then used to adjust the size of CW to rely on such value, thereby improving the fairness index of data flows (voice, video, best effort) in IEEE 802.11 EDCA. The simulation results show that the proposed method can improve the throughput and fairness index of data flows.

A Discrimination Index Based on Jain's Fairness Index to Differentiate Researchers with Identical H-index Values

PurposeThis paper proposes a discrimination index method based on the Jain's fairness index to distinguish researchers with the same H-index.Design/methodology/approachA validity test is used to measure the correlation of D-offset with the parameters, i.e. H-index, the number of cited papers, the total number of citations, the number of indexed papers, and the number of uncited papers. The correlation test is based on the Saphiro-Wilk method and Pearson's product-moment correlation.FindingsThe result from the discrimination index calculation is a two-digit decimal value called the discrimination-offset (D-offset), with a range of D-offset from 0.00 to 0.99. The result of the correlation value between the D-offset and the number of uncited papers is 0.35, D-offset with the number of indexed papers is 0.24, and the number of cited papers is 0.27. The test provides the result that it is very unlikely that there exists no relationship between the parameters.Practical implicationsFor this reason, D-offset is proposed as an additional parameter for H-index to differentiate researchers with the same H-index. The H-index for researchers can be written with the format of “H-index: D-offset”.Originality/valueD-offset is worthy to be considered as a complement value to add the H-index value. If the D-offset is added in the H-index value, the H-index will have more discrimination power to differentiate the rank of the researchers who have the same H-index.

Exhaustive Appraisal of Adaptive Hybrid LTE-A Downlink Scheduling Algorithm

Long Term Evolution- Advanced (LTE-A) networks have been introduced in Third Generation Partnership Project (3GPP) release – 10 specifications, with an objective of obtaining a high data rate for the cell edge users, higher spectral efficiency and high Quality of service for multimedia services at the cell edge/Indoor areas. A Heterogeneous network (HetNet) in a LTE-A is a network consisting of high power macro-nodes and low power micro-nodes of different cell coverage capabilities. Due to this, non-desired signals acting as interference exist between the micro and macro nodes and their users. Interference is broadly classified as cross-tier and co-tier interference. The cross tier interference can be reduced by controlling the base station transmit power while the co-tier interference can be reduced by proper resource allocation among the users. Scheduling is the process of optimal allocation of resources to the users. For proper resource allocation, scheduling is done at the Main Base station (enodeB). Some LTE-A downlink scheduling algorithms are based on transmission channel quality feedback given by user equipment in uplink transmission. Various scheduling algorithms are being developed and evaluated using a network simulator. This paper presents the performance evaluation of the Adaptive Hybrid LTE-A Downlink scheduling algorithm. The evaluation is done in terms of parameters like user’s throughput (Peak, Average, and Edge), Average User’s spectral efficiency and Fairness Index. The evaluated results of the proposed algorithm is compared with the existing downlink scheduling algorithms such as Round Robin, Proportional Fair, Best Channel Quality Indicator (CQI) using a network simulator. The comparison results show the effectiveness of the proposed adaptive Hybrid Algorithm in improving the cell Edge user’s throughput as well the Fairness Index.

Performance Evaluation and Comparison of Scheduling Algorithms on 5G Networks using Network Simulator

In this research, we compared the Round Robin (RR) and the Proportional Fair (PF) algorithms for different user equipment density scenarios using voice and video traffic, to evaluate the key impact on performance of 5G mmwave network. This research simulated on NS3.27 with an integrated mmwave module. Based on the result, we found that the RR is a good choice for voice traffic. It has a throughput of 3.65% better than PF with similar fairness index. On the other hand, we found that the PF is the right choice for video traffic due to has better result for throughput. It has a throughput of 1.24% better than RR. For fairness index round robin has better result for voice and video traffic.

Improving Fairness of H-index: RA-index

<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p><span>H-index has been widely used as one of the bibliometric measurement methods for researchers’ performance. </span><span>On the other hand, H-index has been unfair for figuring authors that have high number of citations but fewer number </span><span>of papers (perfectionist researcher) and researchers that have many papers but fewer citations (productive researcher). The main objective of this article is to improve H-index for accommodating and calculating perfectionist and productive researchers’ impact based on Jain’s Fairness Index algorithm and Lotka’s Law. For improving H-index by RA-index is proposed. To prove the proposed a method, 1,710 citation data sets of top cited researchers from Scopus based on author names list from Webometrics site are used. Fairness index of the RA-index has the average of 91 per cent, which is higher than the fairness of H-Index 80 per cent has been found. </span></p></div></div></div>