Research On Energy Efficiency Optimization Algorithms In Heterogeneous Cellular Networks Under Parametric Uncertainties

With the rapid development of wireless communication technology,traditional homogeneous cellular networks have gradually evolved to heterogeneous cellular networks in order to meet the increasing demand for communication service quality.At the same time,the explosive growth in the number of wireless devices and the large-scale deployment of various types of base stations have made the optimization of energy efficiency a common goal for academics and industry.Existing heterogeneous network energy efficiency optimization algorithms are assumed to be able to obtain perfect channel state information.However,due to the inherent randomness of the wireless channel environment and unavoidable channel estimation errors,the above-mentioned traditional algorithm will cause communication interruption in actual wireless systems.Therefore,this thesis studies robust energy efficiency optimization algorithms for heterogeneous cellular networks based on parameter uncertainties.The main work of this thesis is as follows:(1)In order to reduce the impact of spectrum sensing on network transmission efficiency,a robust resource allocation and transmission duration optimization algorithm based on cognitive heterogeneous cellular networks is studied.Firstly,based on the multi-user cognitive heterogeneous network,a robust resource allocation model for maximizing the total energy efficiency of users in cognitive femtocell networks is established.Then,a sub-optimal subcarrier allocation scheme based on channel gain is proposed to achieve user-subcarrier pairing,and then Taylor series expansion method is used to approximate and optimize the optimal transmission time.Then,the Bernstein approximation method is used to convert the cross-layer interference power constraint based on the outage probability into a convex constraint.Finally,the Dinkelbach method and Lagrangian dual function method are used to obtain the optimal transmission power,and a robust resource allocation algorithm based on Bernstein approximation is proposed.(2)In order to extend the operating life of mobile terminals while ensuring the robustness of the system,a robust resource allocation algorithm for heterogeneous cellular networks based on simulataneous wireless information and power transfer(SWIPT)is studied.SWIPT was introduced to femtocell users,and a multivariable coupled non-convex energy efficiency optimization robust resource allocation model was established.Then,without knowing the statistical distribution model of the position parameters,the minimax probability machine(MPM)method and the Dinkelbach method are used to transform the outage probability constraint and the fractional objective function into convex form,respectively.Finally,based on the Lagrange dual function method and the sub-gradient update method,the optimal power split coefficient and transmit power are obtained,and a robust resource allocation algorithm based on the MPM method is proposed.(3)In order to improve spectrum utilization and the number of users accessing the network,a robust resource allocation algorithm for heterogeneous cellular networks based on a hybrid access model of non-orthogonal multiple access(NOMA)and orthogonal frequency division multiple access(OFDMA)is studied.In order to excavate spectrum efficiency and improve the communication experience of users at the cell edge,based on the NOMA/OFDMA hybrid access mode,the resource allocation problem of multiple femtocell networks to maximize minimum fair energy efficiency was established.Then,the worst-case principal is used to convert the transmission rate expression and the channel uncertainty in cross-layer interference power into convex form,and the variable relaxation method is used to convert the original mixed integer variable problem into a convex problem.Finally,based on the convex optimization theory and the sub-gradient update method,the optimal transmit power and subcarrier allocation strategies are obtained,and a robust resource allocation algorithm based on the variable relaxation method is proposed.