In this paper, user set selection in the allocation sequences of round-robin (RR) scheduling for distributed antenna transmission with block diagonalization (BD) pre-coding is proposed. In prior research, the initial phase selection of user equipment allocation sequences in RR scheduling has been investigated. The performance of the proposed RR scheduling is inferior to that of proportional fair (PF) scheduling under severe intra-cell interference. In this paper, the multi-input multi-output technology with BD pre-coding is applied. Furthermore, the user equipment (UE) sets in the allocation sequences are eliminated with reinforcement learning. After the modification of a RR allocation sequence, no estimated throughput calculation for UE set selection is required. Numerical results obtained through computer simulation show that the maximum selection, one of the criteria for initial phase selection, outperforms the weighted PF scheduling in a restricted realm in terms of the computational complexity, fairness, and throughput.

In this paper, user scheduling with beam selection for full-digital massive multi-input multi-output (MIMO) is proposed. Inter-user interference (IUI) can be canceled by precoding such as zero-forcing at a massive MIMO base station if ideal hardware implementation is assumed. However, owing to the non-ideal characteristics of hardware components, IUI occurs among multiple user terminals allocated on the same resource. Thus, in the proposed scheme, the directions of beams for allocated user terminals are adjusted to maximize the total user throughput. User allocation based on the user throughput after the adjustment of beam directivity is then carried out. Numerical results obtained through computer simulation show that when the number of user terminals in the cell is two and the number of user terminals allocated to one resource block (RB) is two, the throughput per subcarrier per subframe improves by about 3.0 bits. On the other hand, the fairness index (FI) is reduced by 0.03. This is because only the probability in the high throughput region increases as shown in the cumulative distribution function (CDF) of throughput per user. Also, as the number of user terminals in the cell increases, the amount of improvement in throughput decreases. As the number of allocated user terminals increases, more user terminals are allocated to the cell-edge, which reduces the average throughput.

One of key technologies in the fifth generation mobile communications is a distributed antenna system (DAS). As DAS creates tightly packed antenna arrangements, inter-user interference degrades its spectrum efficiency. Round-robin (RR) scheduling is known as a scheme that achieves a good trade-off between computational complexity and spectrum efficiency. This paper proposes a user equipment (UE) allocation scheme for RR scheduling. The proposed scheme offers low complexity as the phase of UE allocation sequences are predetermined. Four different phase selection criteria are compared in this paper. Numerical results obtained through computer simulation show that maximum selection, which sequentially searches for the phase with the maximum tentative throughput realizes the best spectrum efficiency next to full search. There is an optimum number of UEs which obtains the largest throughput in single-user allocation while the system throughput improves as the number of UEs increases in 2-user RR scheduling.

In this paper, a macro cell switching scheme for distributed antennas is proposed. In conventional distributed antenna transmission (DAT), the macro cell to which each antenna belongs is fixed. Though a cell-free system has been investigated because of its higher system throughput, the implementation cost of front-hauls can be excessive. To increase the flexibility of resource allocation in the DAT with moderate front-haul complexity, we propose the macro cell switching of distributed antennas (DAs). In the proposed scheme, DAs switch their attribution macro cells depending on the amount of pre-assigned connections. Numerical results obtained through computer simulation show that the proposed scheme realizes a better system throughput than the conventional system, especially when the number of user equipments (UEs) is smaller and the distance between DAs are larger.