This guide is based on the Python version of RF24 library for NRF24L01+ RF module

• Same from the link above ( not required for Raspbian )
• Numpy (for data recording)
• Matplotlib (optional)

• Raspberry Pi
• Nrf24l01+
• accessories

• send.py Main function for senders.
• recv.py Main function for the receiver.
• command.sh Include all functions for the master.
• ploter.py Plotting function for the master.
• lib_nrf24.py Library function for all nodes.
• conf.txt Number of each node (0~10)
• conf.txt Stands for:

Super frame = spd pack + delay + n*content pack

*spd pack: Decide speed of the following packages. It uses the lowest speed.([speed,node number, merge flag]) *delay:plz use code to calculate *content pack: a list with 32 bytes

• Name all Raspberry Pi as *node n¹ and set node 0 as the receiver, node 1~10 as the senders.

• Connect all nodes to the same Access Point (can be one Raspberry Pi) and obtain all IP address.
• Put all IP into hosts.txt so that the lowest IP stands for the receiver such as the one below.

192.168.88.116
192.168.88.117
192.168.88.118
################

• Create another file hosts2.txt and include all IP that you want to have the delay.

• Send conf.txt to the all to assign node number.

• Send send.py to all but the receiver (uncomment send in command.sh and call by./command.sh).

• Send recv.py to the receiver and change the name to send.py.

• Call main in command.sh.

• Obtain data from the senders.

• Use plot in command.sh to obtain thoughtput data from receiver.

s

• cd,spds,acks,wins,winsact(1~3) Data from the senders
• ts10to5_n.npy Throughput records
• Results: All 4000 success 1902 Accp rate 0.4755 [321, 342, 326, 359, 355, 51, 15, 16, 37, 80, 0, 0] fails 0 throu 6.33 (0.19/0.05 All 4000 success 1930 Accp rate 0.4825 [310, 346, 345, 343, 383, 62, 19, 26, 27, 69, 0, 0] fails 0 throu 6.493 Merge pos

• File: ts.npy
• Result: All 500 success 463 Accp rate 0.926 [463, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] fails 0 throu 12.830785002681203 (0.87)

• Results: All 2000 success 1272 Accp rate 0.636 [377, 482, 413, 0, 0, 0, 0, 0, 0, 0, 0, 0] fails 0 throu 8.638 (0.3 All 2000 success 1295 Accp rate 0.6475 [362, 523, 410, 0, 0, 0, 0, 0, 0, 0, 0, 0] fails 0 throu 8.565 (0.33

• ts10.npy
• Results" All 2000 success 617 Accp rate 0.3085 [75, 90, 95, 76, 97, 48, 18, 26, 7, 85, 0, 0] fails 0 throu 4.183 (0.08 All 2000 success 703 Accp rate 0.3515 [88, 103, 106, 86, 99, 61, 32, 23, 28, 77, 0, 0] fails 0 throu 4.604 (0.08

• Result: All 500 success 479 Accp rate 0.958 [479, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] fails 0 throu 12.064160309909484 (0.88 All 500 success 440 Accp rate 0.88 [440, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] fails 0 throu 10.63986680306113 (0.8 All 500 success 436 Accp rate 0.872 [436, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] fails 0 throu 10.182416244857752 9( 0.77

• Results: All 500 success 470 Accp rate 0.94 [470, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] fails 0 throu 15.132323312179262 (0.87 All 500 success 475 Accp rate 0.95 [475, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] fails 0 throu 15.753244993355121 (0.87 All 500 success 479 Accp rate 0.958 [479, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] fails 0 throu 15.446(0.88

• Results:All 500 success 472 Accp rate 0.944 [472, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] fails 0 throu 16.305350756311196 (0.88 All 500 success 459 Accp rate 0.918 [459, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] fails 0 throu 14.887 (0.88 All 500 success 460 Accp rate 0.92 [460, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] fails 0 throu 13.819 (0.81

• MATLAB simulation

• collision.m Call Bianchi_eqns.m to getn ideal data loss
• cd.m FFT analysis for carrier detection.
• CSMA.mMain function for simulation.