Research On Energy Issue In Heterogeneous Cellular Networks

Wireless date traffic now is growing dramatically. However, as a scarce natural resource, radio spectrum is very crowded in the band of mobile communications, which is becoming a bottleneck to develop diverse wireless applications. A promising way to deal with the increasing demand of date requirement is to shrinking cell sizes serves as the overriding scheme. However, more base station (BSs) will be established in this way, which also increase the energy consumption. Heterogeneous is seemed as an efficient technology to meet the traffic requirements as well as the satisfy the green communication demand. Because of the short range between the low power BSs and the users, heterogeneous cellular network can improve the system capacity and indoor coverage. Furthermore, the low power BSs in the heterogeneous network can not only offload the traffic of the macro BS, but also reduce the total power consumption of the cellular system due to the short distance between the low power BSs and users, which shows great potential in the field of energy saving in wireless communication. Consequently, heterogenous network will contribute to improve the system throughput and reduce the energy consumption. In this thesis, we study the energy efficiency problem for heterogeneous cellular networks. We summarize the main contribution of this work as follows.1. We develop a general modes to illustrate the heterogeneous cellular network-s, in which the properties of different kinds of BSs are taken into consideration, e.g. transmit power, range of coverage and backhauls. Besides, the mutual interference be-tween BSs are also considered, which is the main challenge for the resource allocation problem. Hence, our model is practical for heterogeneous cellular networks.2. We develop a general network to maximize the overall EE of the relaying cognitive radio system, under the constraints of transmit power, traffic demands, as well as the interference constraints of the primary users. However, our problem formulation leads to a nonconvex optimization task. We first convert the formulated problem into a convex optimization problem via its hypograph form, which can be solved by the barrier method. Then we further speed up the computation of Newton step during the barrier method, significantly reducing the complexity of the algorithm by exploiting its special structure.3. We formulate the minimum power consumption problem for heterogeneous cellular networks while satisfying all users’rate requirements, as well as considering the inter-cell interference. A two-stage method is developed to deal with the subchan-nel assignment and power allocation separately. En efficient subchannel allocation scheme is performed by considering different kinds of losses and interference. In the second step, we derive a concave lower bound of user’s achievable rate for a given power allocation, based on which an efficient iterative algorithm is developed to solve the formulated problem. Numerical results show that the energy consumption is re-duced dramatically. Moreover, our proposed algorithm converges quickly and stably, showing great potential for applications.In summary, our proposed algorithms perform well with lower complexity than the other methods in literature and our research results throw some lights in the field of green communication for the resource allocation problem in heterogeneous cellular networks.