# Optimal Meshing Degree Performance Analysis in a mmWave FWA 5G Network Deployment
## 5 Experimental Simulation and Results  
In this section, we analyse the risk-return trade-off that exists between increasing the number of links to provide multiple paths to the nearest POP and the performance of the network. Specifically, we consider the following parameters: (1) gross return, which is a popular metric that measures the return (i.e., gain) attributed to a particular change [47] (in this paper, we consider gross return to be the gain in terms of a set of metrics described below that we achieve when we change the topology from Topology 1 to either Topology 2 or Topology 3), and (2) risk of investment, which is defined as the chance that an investment's actual gain will differ from its expected gain [48]. To this end, each topology was modelled in MATLAB and simulated over 20,000 time steps. At every step, each node randomly decides whether it will generate data packets (based on either an interactive HD-video (1920 \(\times\) 1080 at 24 fps)-streaming session or reported sensor data (an upload of a few KB)), which are sent to the closest POP. There was no further sophistication added at this stage to represent ongoing sessions or other types of traffic in order to maintain the fairness of the tests. The topologies were then compared in terms of the following metrics:  
* Average Latency--This is defined as the average time from when the packet transmission departs from the source node to when the data packet is successfully received by the POP. Latency is set to 1 ms per hop. This value is specified based on real-life measurements. * Packet Error Rate (PER)--This is defined as the ratio between the erroneous data packets received at the POP to the total transmitted data packets. * Packet Delivery Fraction (PDF)--This is defined as the ratio of the number of data packets correctly received by the POP to the total number of data packets generated by the source. * Throughput--This is defined as the total amount of information received at the POP divided by the total session time in bits per second (bps). * Data Rate--This is defined as the total amount of received information at the POP, which is also represented in bps. Note that these metrics were chosen because they are commonly used by researchers to evaluate network performance and are well understood in the context of network modelling [49]. In terms of gross return, throughputs, data rate, and PDF are considered positive gains from an investment, whereas latency and PER are considered negative gains. Furthermore, the computation of the data rate was based on the link capacity represented by the maximum Modulation and Coding Scheme (MCS) index achieved at the receiver's end, which summarizes the modulation type and the coding rate. Importantly, the higher the MCS index, the higher the available data rate at the receiver. All the details on the connection between the MCS indexes and the corresponding available data rates can be found in [21]. Finally, the computation of the MCS index was based on the Shannon-Hartley theorem that considers the bandwidth assigned at the receiver node and the received power, which takes into account the transmission power, the attenuation of the signal due to path loss, and antenna gain. Therefore, the results pertaining to the data rate also provide an insight in terms of link budget, which represents the received power, accounting for the radio environment conditions and transmitter/receiver nodes, and can be evaluated through the corresponding available data rate at the receiver node [50]. The risk of investment in this context is measured using the Coefficient of Variation (\(CV\)) [51]. The \(CV\) represents the variation per unit of median, which was computed using Equation (1) below and is generally expressed as a percentage. In this context, a low \(CV\) is better because it means the volatility (i.e., risk) of measurements is low relative to the median.