## 4 Results and Discussion  
The MATLAB based Vienna LTE System level simulator is used to measure the performance of the proposed model [27]. The downlink channel model with microscopic path loss and shadow fading for an urban area is considered in the simulation process. The WINNER II channel model is implemented in the MATLAB based simulator [28]. Users are equally distributed and scattered randomly in the urban area. There are a different number of users in each cell, which varies from 10 to 60. The users are  
Figure 2: Step-by-step procedure of the proposed method. not static and their average speed is 5 kmph. A 900 MHz frequency band with 20 MHz bandwidth is used and simulation time is 1000 TTI. A number of simulations have been conducted to evaluate the cell-edge throughput, average user throughput, spectral efficiency and fairness index of the proposed EMLWDF method, and the results are compared with PF and basic MLDWF schedulers. Three types of data are considered in the simulation namely Video, Voice over Internet Protocol (VoIP), and HyperText Transfer Protocol (HTTP). The resource type of VoIP is considered as guaranteed bit rate (GBR), whereas Video and HTTP are considered as non-guaranteed bit rate (NGBR) for all user. In order to provide QoS guaranteed VoIP performance, an RTP (Real-time Transport Protocol) AMR (Adaptive Multi-Rate) 12.2 codec with a 12.2 kbps bitrate is used [29]. Videos are encoded by an H.264/AVC (Advanced Video Coding) encoder with a constant bitrate of 242 kbps, while this paper considers the bitrate of 250 kbps for HTTP packets [9]. The basic parameters of the simulation are stated in Table 3.  
The cell-edge throughput of the user is calculated for different data types and algorithms with a various number of users. These cell-edge users are located in the outer region of the cell and their distances from the eNB are higher than the value of \(\Omega\). Figures 3-5 show the comparison of PF, basic MLWDF and EMLWDF algorithms for video, VoIP and HTTP, respectively. As predicted, when the number of users is increasing, the cell-edge user throughput is decreasing for all algorithms. The proposed EMLWDF has higher cell-edge throughput than the other two algorithms for all types of user data. The reasons for this better performance are (a) EMLWDF considers the distance between the user and eNB, received SINR of the user along with HOL delay and previous throughput. Therefore, the users located in a cell-edge area with bad channel condition can get priority from the scheduler and receive a comparatively higher number of RBs. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Values** \\ \hline System bandwidth & 20 MHz \\ Operating frequency & 900 MHz \\ Scenario & Random deployment (Urban) \\ Number of users & 10, 20, 30, 40, 50, 60 \\ User speed & 5 kmph \\ eNB power transmission & 46 dBm \\ MSC index & 29 available MSCs as in 3 GPP [30] \\ Traffic model & Video, VoIP, HTTP \\ Scheduler & PF, MLWDF, EMLWDF \\ Simulation time & 1000 TTI \\ \hline \hline \end{tabular} MSC: Modulation Coding Scheme; 3 GPP: Third Generation Partnership Project; VoIP: Voice over Internet Protocol; PF: Proportional fairness; MLWDF: Modified Largest Weighted Delay First; EMLWDF: Extended MLWDF.  
\end{table} 
Table 3: Simulation parameters with corresponding values. Figure 3: Cell-edge user throughput for Video. On the other hand, basic MLWDF does not consider any other parameter rather than HOL delay and previous throughput. As a result, the cell-edge users do not get the required RB, whereas cell-edge user throughput of the PF algorithm is the lowest, as it only considers the previous throughput of the user. Furthermore, (b) EMLWDF measures the probability of packet loss by considering the error probability of data packet and probability from failure state to success state. Therefore, the cell-edge users with higher error rates are getting higher priority from the scheduler to get more RB.