In this study, an overloaded large-scale distributed antenna network is considered, for which the number of active users is larger than that of antennas distributed in a base station coverage area (called a cell). To avoid overload, users in each cell are divided into multiple user groups, and, to reduce the computational complexity required for multi-user multiple-input and multiple-output (MU-MIMO), users in each user group are grouped into multiple user clusters so that cluster-wise distributed MU-MIMO can be performed in parallel in each user group. However, as the network size increases, conventional computational methods may not be able to solve combinatorial optimization problems, such as user scheduling and user clustering, which are required for performing cluster-wise distributed MU-MIMO in a finite amount of time. In this study, we apply quantum computing to solve the combinatorial optimization problems of user scheduling and clustering for an overloaded distributed antenna network and propose a quantum computing-based user scheduling and clustering method. The results of computer simulations indicate that as the technology of quantum computers and their related algorithms evolves in the future, the proposed method can realize large-scale dense wireless systems and realize real-time optimization with a short optimization execution cycle.

This paper evaluates the throughput of a distributed antenna network (DAN) with multiple mobile terminal scheduling and the usage of joint maximum-likelihood detection (MLD). Mobile terminals are closer to the desired antennas in the DAN which leads to higher throughput and better frequency utilization efficiency. However, when multiple mobile terminal scheduling is applied to the DAN, interference can occur between transmitted signals from antennas. Therefore, in this research, mobile terminal scheduling along with joint MLD is applied to reduce the effects of interference. A system level simulation shows that the usage of joint MLD in a densely packed DAN provides better system throughput regardless of the numbers of mobile terminals and fading channels.

In this paper, the recent advances in cooperative distributed antenna transmission (CDAT) are introduced for spatial diversity and multi-user spatial multiplexing in 5G mobile communications network. CDAT is an advanced version of the coordinated multi-point (CoMP) transmission. Space-time block coded transmit diversity (STBC-TD) for spatial diversity and minimum mean square error filtering combined with singular value decomposition (MMSE-SVD) for multi-user spatial multiplexing are described under the presence of co-channel interference from adjacent macro-cells. Blind selected mapping (blind SLM) which requires no side information transmission is introduced in order to suppress the increased peak-to-average signal power ratio (PAPR) of the transmit signals when CDAT is applied. Some computer simulation results are presented to confirm the effectiveness of CDAT techniques.

Broadband wireless technology that enables a variety of gigabit-per-second class data services is a requirement in future wireless communication systems. Broadband wireless channels become extremely frequency-selective and cause severe inter-symbol interference (ISI). Furthermore, the average received signal power changes in a random manner because of the shadowing and distance-dependant path losses resulted from the movement of a mobile terminal (MT). Accordingly, the transmission performance severely degrades. To overcome the performance degradation, two most promising approaches are the frequency-domain equalization (FDE) and distributed antenna network (DAN). The former takes advantage of channel frequency-selectivity to obtain the frequency-diversity gain. In DAN, a group of distributed antennas serve each user to mitigate the negative impact of shadowing and path losses. This article will introduce the recent advances in FDE and DAN for the broadband single-carrier (SC) transmissions.

In this paper, joint water filling and maximal ratio transmission (joint WF-MRT) downlink transmit diversity for a single-carrier distributed antenna network (SC DAN) is proposed. The joint WF-MRT transmit weight allocates the transmit power in both transmit antenna dimension and frequency dimension, i.e., the power allocation is done both across frequencies based on WF theorem and across transmit antennas based on MRT strategy. The cumulative distribution function (CDF) of the channel capacity achievable by joint WF-MRT transmit diversity is evaluated by Monte-Carlo numerical computation method. The channel capacities achievable with joint WF-MRT, MRT, and WF transmit weight (WF transmit weight is done across transmit antennas and frequencies based on WF theorem) are compared. It is shown that the joint WF-MRT transmit weight provides the highest channel capacity among three transmit weights.