With the development of wireless technologies, wireless relay systems have become a popular topic. To design practical wireless relay systems, link adaptation is an important technique. Because there are both broadcast and multiple access channels in wireless relay systems, link adaptation is difficult to design and hence the optimal throughput is hard to achieve. In this study, a novel method is proposed to maximize the system throughput of wireless relay systems by utilizing the most popular link adaptation methods, adaptive modulation and coding (AMC) and hybrid automatic repeat request (HARQ). The proposed method utilizes the characteristics and operations of AMC and HARQ to adaptively adjust the thresholds for selecting modulation and coding scheme (MCS) to be used. Thus the system can keep tracking the optimal values of the thresholds. Therefore, the system throughput can be maximized. We set up simulations for different relay environment settings, such as different relay HARQ protocols, placements, and multiplexing schemes, to verify the capability of the proposed method. The simulation results show that, compared to the existing method, the proposed method indeed improves system throughput under a variety of relay settings and can be easily applied to different system platforms.

Large-scale distributed antenna systems (LS-DASs) are gaining increasing interest and emerging as highly promising candidates for future wireless communications. To improve the user's quality of service (QoS) in these systems, this study proposes a user cooperation aided clustering approach based on device-centric architectures; it enables multi-user multiple-input multiple-output transmissions with non-reciprocal setups. We actively use device-to-device communication techniques to achieve the sharing of user information and try to form clusters on user side instead of the traditional way that performs clustering on base station (BS) side in data offloading. We further adopt a device-centric architecture to break the limits of the classical BS-centric cellular structure. Moreover, we derive an approximate expression to calculate the user rate for LS-DASs with employment of zero-forcing precoding and consideration of inter-cluster interference. Numerical results indicate that the approximate expression predicts the user rate with a lower computational cost than is indicated by computer simulation, and the proposed approach provides better user experience for, in particular, the users who have unacceptable QoS.