On Resource Optimization In Distributed Antenna Systems

Heterogeneous networks and shrinking cells are the two most important trends of the evolution in wireless communication networks. With the development achieved in both the theory of multiple input multiple output (MIMO) and the technique of coordi-nated multipoint transmission (CoMP), distributed antenna system (DAS) has attracted much attention and been recognized as a new cellular architecture for future mobile communication systems. In a DAS, antenna units are geographically distributed with-in a cell and connected to a central unit (CU) via dedicated backhaul links, such as optical fiber or coaxial cable. DAS has the following advantages:improving the indoor and cell-edge coverage of cellular networks; increasing the system capacity by exploit-ing the spatial diversity gain; enhancing the system energy efficiency. This dissertation deals with resource optimization in DAS, including system capacity, joint user schedul-ing and power allocation with quality of service (QoS) guarantees, joint beamforming design for the robust transmission with time asynchronism and for the maximization of the energy efficiency. The main achievements and results of this dissertation are listed as follows:1. The system capacity of an uplink orthogonal frequency division multiple ac-cess (OFDMA) based DAS is studied. Assuming that the minimum mean square error successive interference cancellation (MMSE-SIC) receiver is applied at the CU, each subcarrier is allowed to be reused by several users simultaneously. We formulate a joint subcarrier and power allocation optimization problem to maximize the system ca-pacity. Since the problem is a mixed-integer program, we firstly propose a centralized greedy algorithm based on the multiuser iterative water-filling power allocation, which allocates the subcarrier-user pair that can achieve the maximum system rate gain at a time. Then, a heuristic algorithm that can be implemented in a distributed manner is proposed. Simulation results indicate that the heuristic algorithm achieves a near performance of the greedy one, and obtains a much higher system capacity than the traditional allocation algorithm.2. In a downlink single-cell DAS, assuming that the full channel state informa-tion (CSI) is available at the transmitter side, we study the joint user scheduling and power allocation algorithm with QoS guarantees. Given a user scheduling result, two power allocation algorithms are proposed based on "hard-removal" and "soft-removal", respectively. The former iteratively removes the unsatisfied users away from the sys-tem, while the latter gradually reduces the transmit power of those antenna units that support the unsatisfied users. Then, we define a priority parameter based on the qual-ity of experience and CSI of each user, which is used to determine the user scheduling order. Finally, a joint heuristic user scheduling and power allocation algorithm is pro-posed. Compared with the algorithms based on exhaustive search, simulation results show that our proposed algorithm achieves a near-optimal performance with a relative low complexity.3. Once only partial CSI is available at the transmitter side, the user QoS require-ment turns to the constraint that maintaining the signal to interference plus noise ratio (SINR) outage probability below a threshold. Thus, the close-form expression of the SINR outage probability is derived. Moreover, considering the random distribution of both the antenna units and users, an adaptive antenna selection method is proposed based on the received pilot signal strengths from different antenna units. Then, an op-timization problem is formulated to minimize the total transmit power, which is solved by applying the first order Taylor series approximation and semi-definite relaxation. Finally, a joint multiuser beamforming algorithm is proposed. Simulation results show that the proposed algorithm has a good property of convergence, and it can satisfy the rate requirements of users with partial CSI condition.4. Considering that signals received by the user terminal from different antenna units will experience different transmission delays, the robust transmit beamforming algorithm is studied. Since the time asynchronism results in serious co-channel inter-ference (CCI) and inter-symbol interference (ISI), the lower-bound of SINR is derived by using the piece-wise linear approximation. Moreover, considering that the joint transmission of multiple antenna units will lead to a huge data transmission on the backhaul links, we formulate an l0-norm minimization problem to minimize the system backhaul overhead. An approximated optimal solution is found through applying the weighted l1-norm relaxation. Finally, we propose a joint beamforming algorithm that is robust to the time asynchronism of the received signals. Simulation results illustrate that the proposed algorithm has a good performance when the relative time delay is less than30%of the symbol duration, and it can significantly reduce the system backhaul overhead. 5. The joint beamforming design is studied with the aim of maximizing the energy efficiency of a DAS. With the consideration of the transmit power and circuit power consumed at each antenna unit, the power consumed on the backhaul links and the signal processing power consumed at the CU, we propose a new power consumption model that can be applied in DAS. Then, a non-linear fractional optimization problem is formulated to maximize the system energy efficiency, which can be equivalently turned to a D.C.(Difference of Convex functions) problem. By applying the first order Taylor series relaxation and successive convex approximation (SCA) method, we fi-nally obtain the joint beamforming algorithm. Compared to the traditional sum rate maximization and total power minimization algorithms, simulation results show that the proposed algorithm can not only satisfy the rate requirement of each user but also achieve the target of energy efficiency maximization.