The Design And Optimization Of Small Cell Network In Future Wireless Communication Systems

With the rapid development of the new generation of wireless communication system,the explosive growth in mobile data traffic and the number of mobile devices brings a heavy burden to the wireless network.To tackle this problem,researchers are searching for new solutions to boost the capacity and coverage of the wireless network,so as to provide the users with higher quality of service(QoS).Small cell network(SCN)has became a potential wireless network structure for future wireless communication,due to its low power,low cost,high capacity and high coverage.However,despite these advantages,the traditional SCN still suffers from its high energy consumption,severe inter-cell interference(ICI)and poor mobility.To address the above problems,the network design and optimization of traditional SCN are carried out in this dissertation from three aspects,namely,improving energy efficiency(EE),eliminating the ICI of the SCN,and exploring more flexible form of the small cell base station.Firstly,a novel energy harvesting(EH)system is designed and optimized for SCN.Based on this structure,a classic three-node relay communication system with EH relay is considered.By taking the energy for receiving data into consideration,an adaptive power scheduling algorithm is proposed to effectively maximize the system throughput in the third chapter.Considering that the SCN has existing electric power supply devices,a hybrid energy communication system based EH and traditional power grid(PG)is also proposed in the third chapter.Then,a novel technique,namely,energy borrowing(EB),is proposed to established a cooperation relationship between the EH-based SCN and PG.Specifically,the EH-based SCN could borrow energy from the PG,requested to return the borrowed energy back with additional energy as interest.Joint optimizations of both EB policy and power scheduling for maximizing the system throughput is formulated.Simulation results show that the proposed EB-based SCN provides considerable throughput gain compared with conventional EH systems,while achieving extra energy interest for the PG.In the fourth chapter,a novel wireless communication system based on spatial modulation(SM)is designed,aiming at alleviating the ICI.Then,for the sake of obtaining the transmit diversity gain,a machine learning(ML)-based base selection algorithm is also proposed,which reduces the computational complexity effectively,while approaching the optimal bit error rate(BER)performance.Furthmore,a tree search based base antenna selection(TSAS)algorithm is proposed for large scale SCN,which works by iteratively spilling the Euclidean distance matrix into submatrices with smaller dimensions.TSAS achieves the optimal BER performance,while reducing the computational complexity.A decremental base antenna selection(DAS)is also proposed for further computational complexity reduction.In the fifth chapter,an unmaned aerial vehicle(UAV)based SCN is proposed to charge ground users via the wireless power transfer(WPT)technique.Based on the UAV-based SCN,the UAV trajectory design algorithms are proposed for both singleuser and two-user models.In the single user case,a two-UAV trajectory design problem is theoretically solved and extended to the multi-UAV case.For the two-user case,the 2D UAV trajectory design is analyzed,which is then extended to higher dimensional UAV trajectory design problem.An adaptive trajectory design algorithm based on the calculus method is presented.Simulation results show that the proposed trajectory design algorithms improve the total receive energy of the ground users effectively.