1. Abstract Cubesat project in Qatar University has been divided into sub-projects that involve designing the different subsystems. This sub-project tackles the communication subsystem, where the system design requirements and components were set, and the Low-Earth-Orbit channel model following the rician distribution was developed, as well as formulizing an energy optimization algorithm to achieve transmitting from the satellite with high data rates with minimal energy losses. The developed algorithms were tested by simulation since the hardware implementation that complies to cubesat requirements didn’t take place so far because of the shortage in equipment. USRP devices were used in terms of hardware as a proof of concept only.. Abstract Cubesat project in Qatar University has been divided into sub-projects that involve designing the different subsystems. This sub-project tackles the communication subsystem, where the system design requirements and components were set, and the Low-Earth-Orbit channel model following the rician distribution was developed, as well as formulizing an energy optimization algorithm to achieve transmitting from the satellite with high data rates with minimal energy losses. The developed algorithms were tested by simulation since the hardware implementation that complies to cubesat requirements didn’t take place so far because of the shortage in equipment. USRP devices were used in terms of hardware as a proof of concept only.. Objectives This phase of the project is focused on designing and modelling the onboard communication subsystem of Qubesat. This major objective can be subdivided into the following specific thrusts: 1) Achieving High data rate and low power communications system with the baseband design and prototyping. 2) Understanding and modelling the LEO wireless channel characteristics. Objectives This phase of the project is focused on designing and modelling the onboard communication subsystem of Qubesat. This major objective can be subdivided into the following specific thrusts: 1) Achieving High data rate and low power communications system with the baseband design and prototyping. 2) Understanding and modelling the LEO wireless channel characteristics. Conclusion The objectives of designing a communication subsystem for Qubesat were theoretically achieved. The developed energy minimization algorithm can be applied by the coming groups on the Rician channel model to simulate the real case. Moreover, a LEO channel model was developed, where the Rician model was adopted since it accounts for both Line-of-Sight and reflected components. For the hardware implementation part, the USRP platform was used to demonstrate transmitting on a 2.4-GHz channel using QPSK modulation, and a picture was successfully transmitted between the two devices, which corresponds to the real life application of the satellite. Conclusion The objectives of designing a communication subsystem for Qubesat were theoretically achieved. The developed energy minimization algorithm can be applied by the coming groups on the Rician channel model to simulate the real case. Moreover, a LEO channel model was developed, where the Rician model was adopted since it accounts for both Line-of-Sight and reflected components. For the hardware implementation part, the USRP platform was used to demonstrate transmitting on a 2.4-GHz channel using QPSK modulation, and a picture was successfully transmitted between the two devices, which corresponds to the real life application of the satellite. Design of an Energy Efficient Communication System for Qatar University Cubesat Abdulrahman Alassi, Ahmed Al-Mashhadani and Ahmed Khan Supervised by: Dr. Tamer Khattab and Dr. Ahmed Massoud Acknowledgments To our supervisors and the department’s technical engineers for their continuous support and guidance throughout the year. Acknowledgments To our supervisors and the department’s technical engineers for their continuous support and guidance throughout the year. Constellation diagrams for transmitter, unequalized and equalized received signals for the developed Rician Channel Simulink model. As well as the BER Vs. SNR curve for the model, showing the inverse proportionality between them Testing the effect on the received image for different SNR and resulting BER values. The picture to the left is received with 7% error, while the picture to the right is received with 0% error. Results Energy Minimization Algorithm For Transmission Scheduling and the developed Simulink model for testing it using an AWGN channel. The table shows the test results with the selected thresholds of T1 = 1 dB and T2 = 3 dB. It also shows the tradeoff between the BER and the number of received symbols for a set of SNR values. Es/No (dB)Reciever BER (Simulation)Received SymbolsRS Per 3 Rotations 0000 10.0506823039056911715 20.0235723039056911715 30.031361151990534559715 40.005261151990534559715 50.000571151990534559715 60.000051151990534559715 The experimental setup for testing the USRP devices. One of the laptops has the transmitting blocks whereas the other one has the receiving blocks Decoded data at the receiver side of the USRP devices network. It can be extended to include any kind of data Future Work For the communications subsystem, the coming groups have to continue working on the following: integrating the Rician channel model to the energy optimization Simulink file and getting the threshold values based on that, as well as trying to update the mathematical formulization of the problem. Also, in terms of hardware, they have to work on getting a functional board from a specialized manufacturer that complies with the cubesat standards. Eventually, the coming groups have to coordinate with their partners who will be working in other groups on developing and enhancing other subsystems to integrate the whole thing into one functional system. Future Work For the communications subsystem, the coming groups have to continue working on the following: integrating the Rician channel model to the energy optimization Simulink file and getting the threshold values based on that, as well as trying to update the mathematical formulization of the problem. Also, in terms of hardware, they have to work on getting a functional board from a specialized manufacturer that complies with the cubesat standards. Eventually, the coming groups have to coordinate with their partners who will be working in other groups on developing and enhancing other subsystems to integrate the whole thing into one functional system.