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.

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.

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.

Non-orthogonal multiple access (NOMA) is a promising multiple access scheme for further improving the spectrum efficiency compared to orthogonal multiple access (OMA) in the 5th Generation (5G) mobile communication systems. As inter-user interference cancellers for NOMA, two kinds of receiver structures are considered. One is the reduced complexity-maximum likelihood receiver (R-ML) and the other is the codeword level interference canceller (CWIC). In this paper, we show that the R-ML is superior to the CWIC in terms of scheduling flexibility. In addition, we propose a link to system (L2S) mapping scheme for the R-ML to conduct a system level evaluation, and show that the proposed scheme accurately predicts the block error rate (BLER) performance of the R-ML. The proposed L2S mapping scheme also demonstrates that the system level throughput performance of the R-ML is higher than that for the CWIC thanks to the scheduling flexibility.

This paper investigates a frame aggregation (FA) technique in the medium access control (MAC) layer for downlink multi-user multiple input multiple output (MU-MIMO) channels in wireless local area networks (WLANs), and proposes a high-efficient FA scheme that ehances system performance: transmission performance and fairness in communication between mobile terminals (MTs). The proposed FA scheme employs novel criteria for selecting receiving MTs and wireless frame setting with a frame size adaptation mechanism for MU-MIMO transmissions. The proposed receiving MT selection gives higher priority to the MTs expecting higher throughput in the next MU-MIMO transmission and having large amount transmission data while reducing signaling overhead, leading to improvements in system throughput and fairness in communication. The proposed wireless frame setting, which employs hybrid A-MSDU/A-MPDU FA, achieves frame error rate (FER) better than the requirement from communication services by using A-MSDU frame size adaptation. Through system-level simulation, the effectiveness of the proposed scheme is validated for downlink MU-MIMO channels in WLANs.

In a multi-cell MIMO system, the rate of edge users is limited by the inter-cell co-channel interference. The CoMP scheme which includes Joint Process (JP) and Coordinated Scheduling/Beamforming (CS/CB) was developed to reduce the inter-cell interference and enhance the edge rate. Because CS/CB can alleviate the overhead of network, it gains attention recently. In this paper, a modified zero forcing beamforming (ZFBF) is applied to downlink transmission in a two-cell MIMO system. In order to enhance system sum rate, a novel coordinated user scheduling algorithm is proposed. Firstly, we select users with high correlation among cross-channels as candidates, and then group users from candidates with high orthogonality among direct-channels, and match user groups in different cells as the final scheduling group pair. Simulations show that the proposed algorithm can achieve a higher system sum rate with low complexity than traditional scheduling algorithms.

Scheduling imposes a trade-off between sum capacity and fairness among users. In some situations, fairness needs to be given the first priority. Therefore, a scheduling algorithm which can flexibly control sum capacity and fairness is desirable. In this paper, assuming the single-carrier frequency division multiple access (SC-FDMA), we propose three scheduling algorithms: modified max-map, proportional fairness (PF)-map, and max-min. The available subcarriers are grouped into a number of subcarrier-blocks each having the same number of subcarriers. The scheduling is done on a subcarrier-block by subcarrier-block basis to take advantage of the channel frequency-selectivity. The same number of non-contiguous subcarrier-blocks is assigned to selected users. The trade-off between sum capacity and fairness is controlled by changing the number of simultaneously scheduling users per time-slot. Capacity, fairness, and peak-to-average power ratio (PAPR) when using the proposed scheduling algorithms are examined by computer simulation.

In this paper, we study the impact of opportunistic user scheduling on the outage probability of cognitive radio (CR) multiple-input multiple-output (MIMO) systems in the high power region where the peak transmit power constraint is higher than the peak interference constraint. The primary contributions of this paper are the derivation of exact closed-form expressions of the proposed scheduled CR-MIMO systems for outage probability and asymptotic analysis to quantify the diversity order and signal to noise ratio (SNR) gain. Through exact analytical results, we provide the achievable outage probability of the proposed scheduled systems as a function of SNR. Also, through asymptotic analysis, we show that the scheduled CR-MIMO systems provide some diversity order gain over the non-scheduled CR-MIMO systems which comes from multi-user diversity (MUD). Also, the SNR gain of the proposed scheduled systems is identical to that of the non-scheduled CR-MIMO systems.

In this paper, we investigate the user scheduling algorithms with statistical eigen-mode transmission (SET) for downlink multiuser multiple-input multiple-output (MU-MIMO) system by utilizing the statistical channel state information (SCSI). Given the objective of maximizing the ergodic achievable sum rate per group (EASRPG), our first proposal, the Munkres user assignment algorithm (MUAA), solves the optimal user grouping problem. Different from the conventional user grouping algorithm (e.g. max-min method), MUAA can efficiently solve the user assignment problem and acquire an optimal solution. However, some user groups of the optimal solution called “unfriendly” groups severely degrade the EASRPG by performing the multiuser SET (MU-SET) due to excessive inter-user interference. To overcome this obstacle, the MUAA with sequential iterative separation (MUAA-SIS) is proposed to find the “unfriendly” groups and switch from the MU-SET to the single-user SET. Finally, our numerical results show that MUAA-SIS offers a higher EASRPG.

The important issue of an adaptive scheduling scheme is to maximize throughput while providing fair services to all users, especially under strict quality of service requirements. To achieve this goal, we consider the problem of multiuser scheduling under a given fairness constraint. A novel Adaptive Fairness and Throughput Control (AFTC) approach is proposed to maximize the network throughput while attaining a given min-max fairness index. Simulation results reveal that comparing to straightforward methods, the proposed AFTC approach can achieve the desired fairness while maximizing the throughput with short convergence time, and is stable in dynamic scenarios. The trade-off between fairness and throughput can be accurately controlled by adjusting the scheduler's parameters.

We propose a network coordinated opportunistic beamforming (NC-OBF) protocol for downlink K-cell networks with M-antenna base stations (BSs). In the NC-OBF scheme, based on pseudo-randomly generated BF vectors, a user scheduling strategy is introduced, where each BS opportunistically selects a set of mobile stations (MSs) whose desired signals generate the minimum interference to the other MSs. Its performance is then analyzed in terms of degrees-of-freedom (DoFs). As our achievability result, it is shown that KM DoFs are achievable if the number N of MSs in a cell scales at least as SNRKM-1, where SNR denotes the received signal-to-noise ratio. Furthermore, by deriving the corresponding upper bound on the DoFs, it is shown that the NC-OBF scheme is DoF-optimal. Note that the proposed scheme does not require the global channel state information and dimension expansion, thereby resulting in easier implementation.

This letter considers a sum-rate maximization problem with user scheduling wherein each user has a minimum-rate requirement in multiple-input-multiple-output broadcast channel. The multiuser strategy used in the user scheduling is a joint transceiver scheme with block diagonal geometric mean decomposition. Since optimum solution to the user scheduling problem generally requires exhaustive search, we propose a suboptimum user scheduling algorithm with each user's minimum-rate requirement as the main constraint. In order to satisfy maximum sum-rate and minimum-rate constraints simultaneously, we additionally consider power allocation for scheduled users. Simulation results show that the proposed user scheduling algorithm, together with the user power allocation, achieves sum-rate close to the exhaustive search, while also guarantees minimum-rate requirement of each user.

In multiple-input multiple-output (MIMO) systems, the multiuser MIMO (MU-MIMO) systems have the potential to provide higher channel capacity owing to multiuser and spatial diversity. Block diagonalization (BD) is one of the techniques to realize MU-MIMO systems, where multiuser interference can be completely cancelled and therefore several users can be supported simultaneously. When the number of multiantenna users is larger than the number of simultaneously receiving users, it is necessary to select the users that maximize the system capacity. However, computation complexity becomes prohibitive, especially when the number of multiantenna users is large. Thus simplified user scheduling algorithms are necessary for reducing the complexity of computation. This paper proposes a simplified capacity-based user scheduling algorithm, based on analysis of the capacity-based user selection criterion. We find a new criterion that is simplified by using the properties of Gram-Schmidt orthogonalization (GSO). In simulation results, the proposed algorithm provides higher sum rate capacity than the conventional simplified norm-based algorithm; and when signal-to-noise power ratio (SNR) is high, it provides performance similar to that of the conventional simplified capacity-based algorithm, which still requires high complexity. Fairness of the users is also taken into account. With the proportionally fair (PF) criterion, the proposed algorithm provides better performance (sum rate capacity or fairness of the users) than the conventional algorithms. Simulation results also shows that the proposed algorithm has lower complexity of computation than the conventional algorithms.

This letter investigates the effects of spatial correlation on several multiple antenna schemes in multiuser environments. Using an order statistics upper bound on achievable capacity, we quantify the interaction among spatial correlation, spatial diversity, spatial multiplexing and multiuser diversity. Also, it is verified that the upper bound is tighter than asymptotic capacity when the number of users is relatively small.

We describe a user scheduling scheme suitable for zero-forcing beamforming (ZFBF) downlink multiuser multiple-input multiple-output (MU-MIMO) orthogonal frequency-division multiplexing (OFDM) transmissions in time-division-duplex distributed antenna systems. This user scheduling scheme consists of inter-cell-interference mitigation scheduling by using fractional frequency reuse, proportional fair scheduling in the OFDM frequency domain, and high-capacity ZFBF-MU-MIMO scheduling by using zero-forcing with selection (ZFS). Simulation results demonstrate in a severe user-distribution condition that includes cell-edge users that the proposed user scheduling scheme achieves high average cell throughputs close to that provided by only ZFS and that it also achieves almost the same degree of user fairness as round-robin user scheduling.

This letter proposes a new practical multiuser MIMO (MU-MIMO) scheme, which is an evolution of the well-known Per User Unitary beamforming Rate Control (PU2RC) proposed for 3GPP-LTE and IEEE802.16m standards. The proposed scheme includes an efficient user scheduling algorithm which alleviates the major weakness of the conventional PU2RC. Numerical results show that the proposed scheme provides notable performance improvement especially with small and medium user pool since it effectively exploits the benefit from large codebook size.

This letter presents an optimal user selection algorithm that provides a maximum sum-rate in a zero-forcing based Multiuser MIMO system for downlink. The proposed technique forms a primary group of users whose channel power exceeds a predetermined threshold. Through computer simulations, we have found that the proposed method outperforms the conventional technique yielding a sum rate that is 0.33 bps/Hz higher when the transmit SNR is 10 dB and the total number of users and transmit antennas in the cell is 100 and 4, respectively.

In this paper, we propose a multi-stage hybrid scheduling scheme for codebook-based precoding systems, which provides a framework to apply different scheduling criterions at different scheduling stages for selecting user equipment (UEs). Numerical simulation results show that the proposed scheme effectively fills the performance gap between maximum carrier-to-interference (Max C/I) power ratio and Proportional Fairness (PF) methods, and provides an important means at the media access control (MAC) layer to lever between aggregate cellular throughput and geometry-specific per-user fairness, in order to meet the requirements of more precise quality of service (QoS) provision for future mobile communication systems.

The problem of joint orthogonal precoding and user scheduling in a multi-user multi-input multi-output (MU-MIMO) downlink system is considered. Based on the theoretics of subspace and vector projection, a novel orthogonal precoding matrix is designed to achieve high sum-rate capacity with low to moderate number of active users and in low SNR regions. With respect to sum-rate capacity, numerical simulations show that the proposed algorithm outperforms the zero-forcing beam-forming (ZFBF) and linear orthogonal beam-forming (OLBF).

In this paper, a novel user scheduling algorithm for maximizing the sum-rate capacity of inhomogeneous network is investigated. In order to extract the multi-user diversity order and reduce the feedback quantity, selective feedback scheme is adopted. An algorithm of key parameter, the prescribed threshold, is proposed. Numerical simulations show that when adopted the proposed threshold in the inhomogeneous networks, selective feedback scheme can still preserve the majority of the sum-rate capacity of the full back scheme, while the feedback load is significantly reduced.