Research On Radio Resource Allocation In LTE-Advanced Systems

With the rapid development of wireless communication technology and the continuous increase of user requirements for high rate data services, the mobile communication system has undergone many times of innovations and evolutions evolving from the analog system to the fourth generation (4G) system. As the further evolution of the Quasi 4G system-LTE, LTE-Advanced systems introduce a variety of key technologies, such as Coordinated Multiple Point (CoMP) transmission and Device-to-Device (D2D) Communication, to achieve the goals that improving the spectral efficiency, enhancing the network coverage and reducing the cell load. On the other hand, with the sharp growth of multimedia services and unceasing expansion of network size in LTE-Advanced systems, the problems of energy shortage and environment pollution are becoming increasingly severe. In the future wireless communication systems, the enhancement of spectrum efficiency is no longer the only criterion for network performance. The energy efficiency in non-regeneration energy supplied system and the network sustainability in green energy powered system is becoming a crucial designing evaluation for the next generation mobile communication networks.However, due to the scarcity of radio resource and the instability of wireless channel in mobile communications systems, how to reasonably allocate the limited resource in order to satisfy people’s needs of services and various indicators of network performance has become the core issue that need to be studied in LTE-Advanced systems. In this thesis, the technologies of radio resource allocation in LTE-Advanced systems are studied in depth. By means of various technologies such as swarm intelligent optimization, convex optimization, fractional programming and queuing theory, optimal allocation strategies on energy, time-frequency and space resources are proposed for CoMP networks and D2D communication underlaying cellular networks. The evolution of performance indicators is considered as the clue through the whole thesis. This thesis launches studying according to the order that from spectrum efficiency to energy efficiency to network sustainability, and presents the following research contents and innovations:1. For CoMP JT networks, the spectrum allocation schemes based on optimal capacity are studied from both heuristic and optimal point of view. For the heuristic spectrum allocation strategy, a semi-dynamic cooperation set selection method is proposed first, which has solved the conflict between performance and complexity overhead. And then on this basis, a spectrum allocation algorithm is designed for the coordination among overlapping cooperation sets by inheriting the idea of fair treatment for cell center users (CCUs) and cell edge users (CEUs) to use resources. The proposed semi-dynamic coordinated method increases the average throughput of cellular users significantly as well as ensures the users’ fairness. Next, the spectrum allocation scheme based on improved particle swarm optimization (PSO) is presented from the perspective of optimization. The relation between the performance of cell edge and overall system is emphatically analyzed and the CEU weighting factor is introduced to control the proportion of CEUs’throughput in the objective function. The limited nonlinear 0-1 programming model is established for spectrum allocation in CoMP JT and the improvement on binary variables optimization, constraint handling and convergence acceleration is put forward based on the established model. The binary constrained PSO algorithm is further proposed which is appropriate for the spectrum allocation in CoMP JT scenario. The proposed algorithm balances the performance of CEUs and overall system by adjusting the weighting factor with a flexible implementation; the CEU throughput and entire system throughput are both improved significantly compared with other existing algorithms when the weighting factor is set properly.2. For cellular and D2D communication hybrid networks, the spectrum and power allocation strategy based on optimal capacity is proposed. By analyzing the interference scene in which D2D users reuse the cellular uplink resources, the global optimization model of resource allocation for both cellular and D2D users is built with the objective of maximizing the system capacity. In this model, the number of D2D users on the same resource block and resources reused by D2D user are no longer restricted, which offers a higher freedom of resource reusing for D2D users. In order to decrease the solving complexity, the capacity optimization problem is divided into two sub-problems and a two-step resource allocation scheme is further designed. Based on the ideas of increment greed, an improved greedy spectrum allocation algorithm is proposed, in which the exchanging and excluding operations are brought in to avoid falling into the local optimum. After the spectrum allocation policy has been determined, the power optimization problem is solved in its dual domain by using Lagrangian duality theory and the optimum power allocation algorithm based on two-layer iteration is proposed. The above resource allocation scheme dynamically adjusts the RBs used for cellular and D2D users and the transmit power on each RB according to the collected channel state information, which makes an effective improvement in transmission rate of D2D users and capacity of whole system while still retains the rate of cellular users.3. For the downlink multiple-antenna scenario with CoMP CS/CB, the coordinated user scheduling, beamforming and power allocation schemes based on energy efficiency maximization and energy efficiency-spectrum efficiency tradeoff are proposed respectively. At first, in order to effectively measure the energy efficiency of network, the energy consumption on data transmission, signal processing and backhauling link losses are considered together and the total power consumption for multi-cell cooperative system is mathematically abstracted. Combining with the analysis of system total capacity, the optimization goal about energy efficiency is further obtained. For the first kind of energy efficiency maximization problem, the fractional programming model about the beamforming vectors and user scheduling policies is established based on the above optimization goal. After that, the original problem is converted into an equivalent parametric non-fractional form based on the Dinkelbach property and the Newton-iterative searching algorithm is adopted for solving the optimal energy efficiency. For the sub-problems nested in the proposed Newton-iterative algorithm, the iterative beamforming vector optimization algorithm base on the first order optimal condition and the improved greedy user scheduling algorithm are designed respectively. The proposed algorithm has a rapid speed of iteration convergence and achieves significant performance gain in system energy efficiency. For the second kind of radio resource optimization problem on energy efficiency-spectrum efficiency tradeoff, the constraint for minimum rate is introduced to effectively guarantee the quality of transmission for each user. At the solving stage, by integrating the advantages of Newton-iterative algorithm and Bisection method, an improved bisection resource allocation algorithm is used to optimize the energy efficiency. Subsequently, the sub-problem solving method based on first-order convex approximation and the rate constraint optimization algorithm based on bit loading are further put forward. Numerical results indicate that the proposed algorithm realizes the effective balance between user rate and energy efficiency by adjusting the minimum rate restriction.4. For CoMP networks and cellular and D2D communication hybrid networks which are powered by renewable energy sources, radio resource allocation schemes based on energy sustainability are designed respectively. Due to the highly dynamic time-varying characteristic of renewable energy supply, the energy evolution process of base station (BS) is a stochastic process. First of all, the statistical properties of energy evolution process are analyzed via queueing theory and the above process is modeled as a G/G/1 queue. The expressions for the conditional probability density function and the mean of energy sustainable duration (ESD) are further derived. Next, the radio resource allocation problem of the CoMP networks powered by renewable energy is abstracted and modeled. During the modeling process, maximizing the minimal energy sustainable duration (MESD) is applied as the optimization objective with the synthetical consideration of requirements for users’quality of service (QoS), so that the unremitting communication of whole network is guaranteed while the maximum fairness of energy sustainability among BSs is also achieved. To solve the constructed problem, two equivalent constraints on transmit power of BS are obtained based on the statistical analysis of ESD. Furthermore, an iterative resource allocation algorithm with low complexity and semi-distributed implementation is proposed, which improves the overall sustainability of CoMP networks while also maintains users’transmission performance. Finally, the power allocation issue for renewable energy supplied D2D communication networks is studied. The non-convex characteristic of original problem is overcome through variable substitution and the closed-form solutions for global optimal power are obtained. Furthermore, an iterative power allocation algorithm based on Lagrangian duality theory is put forward. The proposed algorithm takes the total transmission rate of D2D users as the optimization criterion and takes into account the constraint conditions such as network sustainability, QoS requirements of cellular users and transmit power limitation of BS and users. The simulation results show that the proposed algorithm can ensure the normal energy supply of BS while effectively increase the performance gain brought from D2D communication.