In this paper, we investigate a method for clustering user equipment (UE)-specific transmission access points (APs) in downlink cell-free multiple-input multiple-output (MIMO) assuming that the APs distributed over the system coverage know only part of the instantaneous channel state information (CSI). As a beamforming (BF) method based on partial CSI, we use a layered partially non-orthogonal zero-forcing (ZF) method based on channel matrix muting, which is applicable to the case where different transmitting AP groups are selected for each UE under partial CSI conditions. We propose two AP clustering methods. Both proposed methods first tentatively determine the transmitting APs independently for each UE and then iteratively update the transmitting APs for each UE based on the estimated throughput considering the interference among the UEs. One of the two proposed methods introduces a UE cluster for each UE into the iterative updates of the transmitting APs to balance throughput performance and scalability. Computer simulations show that the proposed methods achieve higher geometric-mean and worst user throughput than those for the conventional methods.

This paper extends our previously reported non-orthogonal multiple access (NOMA)-based highly-efficient and low-latency hybrid automatic repeat request (HARQ) method for ultra-reliable low latency communications (URLLC) to the case with inter-base station cooperation. In the proposed method, delay-sensitive URLLC packets are preferentially multiplexed with best-effort enhanced mobile broadband (eMBB) packets in the same channel using superposition coding to reduce the transmission latency of the URLLC packet while alleviating the throughput loss in eMBB. Although data transmission to the URLLC terminal is conducted by multiple base stations based on inter-base station cooperation, the proposed method allocates radio resources to URLLC terminals which include scheduling (bandwidth allocation) and power allocation at each base station independently to achieve the short transmission latency required for URLLC. To avoid excessive radio resource assignment to URLLC terminals due to independent resource assignment at each base station, which may result in throughput degradation in eMBB terminals, we employ an adaptive path-loss-dependent weighting approach in the scheduling-metric calculation. This achieves appropriate radio resource assignment to URLLC terminals while reducing the packet error rate (PER) and transmission delay time thanks to the inter-base station cooperation. We show that the proposed method significantly improves the overall performance of the system that provides simultaneous eMBB and URLLC services.

This paper proposes applying random (opportunistic) beamforming to base station (BS) cooperative multiuser multiple-input multiple-output (MIMO) transmission. This proposal comprises two parts. First, we propose a block-diagonalized random unitary beamforming matrix. The proposed beamforming matrix achieves better throughput distribution compared to the purely random unitary beamforming matrix when the average path loss determined by distance-dependent loss and shadowing loss is largely different among transmitter antennas, which is true in BS cooperative MIMO. Second, we propose an online update algorithm for a random beamforming matrix to improve the throughput compared to the purely random and channel-independent beamforming matrix generation, especially when the number of users is low. Different from conventional approaches, the proposed online update algorithm does not increase the overhead of the reference signal transmission and control delay. Simulation results show the effectiveness of the proposed method using a block-diagonalized random unitary beamforming matrix with online updates in a BS cooperative multiuser MIMO scenario.

This paper extends our previously proposed non-orthogonal multiple access (NOMA) scheme to the base station (BS) cooperative multiple-input multiple-output (MIMO) cellular downlink for future radio access. The proposed NOMA scheme employs intra-beam superposition coding of a multiuser signal at the transmitter and the spatial filtering of inter-beam interference followed by the intra-beam successive interference canceller (SIC) at the user terminal receiver. The intra-beam SIC cancels out the inter-user interference within a beam. This configuration achieves reduced overhead for the downlink reference signaling for channel estimation at the user terminal in the case of non-orthogonal user multiplexing and enables the use of the SIC receiver in the MIMO downlink. The transmitter beamforming (precoding) matrix is controlled based on open loop-type random beamforming using a block-diagonalized beamforming matrix, which is very efficient in terms of the amount of feedback information from the user terminal. Simulation results show that the proposed NOMA scheme with block-diagonalized random beamforming in BS cooperative multiuser MIMO and the intra-beam SIC achieves better system-level throughput than orthogonal multiple access (OMA), which is assumed in LTE-Advanced. We also show that BS cooperative operation along with the proposed NOMA further enhances the cell-edge user throughput gain which implies better user fairness and universal connectivity.

This paper proposes a novel method for adaptively controlling the admission of interference to users in our previously proposed layered partially non-orthogonal block diagonalization (BD) precoding method for downlink multiuser multiple-input multiple-output (MIMO) transmission that employs cooperation among multiple base stations (BSs). The proposed method is applicable when some of the instantaneous channel state information (CSI) feedback between the user equipment and the respective BSs is missing if the path loss between the user equipment and BS is higher than a predetermined threshold. The proposed method suppresses the loss in the transmitter diversity (beam forming) gain caused by the perfect nulling of inter-user interference in BD. By allowing the inter-user interference from a link that has a high average path loss, the overall throughput performance of simple BD is enhanced. We show that the combination of layered transmission that restricts the set of BSs used for the signal transmission and adaptive control of interference admission significantly increases the throughput of BS cooperative multiuser MIMO with partial CSI feedback.

In this letter, we propose a novel precoding scheme for base station (BS) cooperation in downlink cellular networks that allow overlapped clusters. The proposed precoding scheme is designed to mitigate the overlapping-BS interference by maximizing the so-called clustered virtual signal-to-interference-plus-noise ratio (CVSINR). Simulations show that with the proposed scheme, overlapped clustering provides substantial throughput gain over the traditional non-overlapped clustering methods, and user fairness is also improved.

This paper proposes applying our inter-cell interference (ICI) cancellation method to fractional frequency reuse (FFR) and evaluates the resulting spectral efficiency improvement. With our ICI cancellation method based on base station cooperation, the control station generates ICI replica signals by simple linear processing. Moreover, FFR effectively utilizes frequency resources by both allowing users in the cell-center region to access all available sub-channels and increasing the transmission power to users in the cell-edge region. FFR provides the conditions under which the ICI cancellation method works effectively. Computer simulations show that the average spectral efficiency of the proposed method is comparable to that of cooperative MU-MIMO, which can completely remove ICI.

This paper investigates a precoding method in downlink multiuser multiple-input multiple-output (MIMO) transmission with multiple base station (BS) cooperation, where each user device basically feeds back the instantaneous channel state information (CSI) to only the nearest BS, but the users near the cell edge additionally feedback the instantaneous CSI to the second nearest BS among the cooperating BSs. Our precoding method is categorized as a form of multi-cell processing (MCP) [5], in which the transmission information to a user is shared by the cooperating BSs in order to utilize fully the degrees of freedom of the spatial channel, and is based on block diagonalization of the channel matrix. However, since some elements of the channel matrix are unknown, we allow partially non-orthogonal transmission. More specifically, we allow inter-user interference to users with limited instantaneous CSI feedback from the channel where the instantaneous CSIs of those users are not obtained at the BSs. The other sources of inter-user interference are set to zero based on the block diagonalization of the channel matrix. The proposed method more efficiently utilizes the degrees of freedom of the spatial channel compared to the case with full orthogonal transmission at the cost of increased inter-user interference. Simulation results show the effectiveness of the proposed method compared to the conventional approaches, which can accommodate the partial CSI feedback scenario, from the viewpoints of the required transmission power and achievable throughput.

Traditional cellular networks suffer the so-called “cell-edge problem” in which the user throughput is deteriorated because of pathloss and inter-cell (co-channel) interference. Recently, Base Station Cooperation (BSC) was proposed as a solution to the cell-edge problem by alleviating the interference and improving diversity and multiplexing gains at the cell-edge. However, it has minimal impact on cell-inner users and increases the complexity of the network. Moreover, static clustering, which fixes the cooperating cells, suffers from inter-cluster interference at the cluster-edge. In this paper, dynamic fractional cooperation is proposed to realize dynamic clustering in a shared RRU network. In the proposed algorithm, base station cooperation is performed dynamically at cell edges for throughput improvement of users located in these areas. To realize such base station cooperation in large scale cellular networks, coordinated scheduling and distributed dynamic cooperation are introduced. The introduction of coordinated scheduling in BSC multi-user MIMO not only maximizes the performance of BSC for cell-edge users but also reduces computational complexity by performing simple single-cell MIMO for cell-inner users. Furthermore, the proposed dynamic clustering employing shared RRU network realizes efficient transmission at all cell edges by forming cooperative cells dynamically with minimal network complexity. Owing to the combinations of the proposed algorithms, dynamic fractional cooperation achieves high network performance at all areas in the cellular network. Simulation results show that the cell-average and the 5% cell-edge user throughput can be significantly increased in practical cellular network scenarios.

Base station (BS) cooperation is a promising technique to suppress co-channel interference for cellular networks. However, practical limitations constrain the scale of cooperation, thus the network is divided into small disjoint BS cooperation groups, namely clusters. A decentralized scheme for BS cluster formation is proposed based on efficient BS negotiations, of which the feedback overhead per user is nearly irrelevant to the network size, and the number of iteration rounds scales very slowly with the network size. Simulations show that our decentralized scheme provides significant sum-rate gain over static clustering and performs almost the same as the existing centralized approach. The proposed scheme is well suited for large-scale cellular networks due to its low overhead and complexity.

Base Station (BS) cooperation has been considered as a promising technology to mitigate co-channel interference (CCI), yielding great capacity improvement in cellular systems. In this paper, by combining frequency domain cooperation and space domain cooperation together, we design a new CCI mitigation scheme to maximize the total utility for a multi-cell OFDMA network. The scheme formulates the CCI mitigation problem as a mixture integer programming problem, which involves a joint user-set-oriented subcarrier assignment and power allocation. A computationally feasible algorithm based on Lagrange dual decomposition is derived to evaluate the optimal value of the problem. Moreover, a low-complexity suboptimal algorithm is also presented. Simulation results show that our scheme outperforms the counterparts incorporating BS cooperation in a single domain considerably, and the proposed low-complexity algorithm achieves near optimal performance.

In this paper, we study the performance of base station (BS) cooperation for downlink transmission. Based on a modified Wyner multicell model, an opportunistic intra cell scheduling scheme is proposed. Then, we derive a closed-form expression for the sum-rate capacity of the proposed scheme in the Rayleigh flat-fading channel. Also, we prove that the opportunistic scheme can be regarded as providing a downlink beam-forming scheme to achieve a tighter lower bound for the downlink sum rate capacity. Numerical results confirm our theoretical analysis.

The present paper focuses on the application of the base station cooperation (BSC) technique in fractional frequency reuse (FFR) networks. Fractional frequency reuse is considered to be a promising scheme for avoiding the inter-cell interference problem in OFDMA cellular systems, such as WiMAX, in which the edge mobile stations (MSs) of adjacent cells use different subchannels for separate transmission. However, the problem of FFR is that the cell edge spectral efficiency (SE) is much lower than that of the cell center. The BSC technique, in which adjacent BSs perform cooperative transmission for one cell edge MS with the same channel, may improve the cell edge SE. However, since more BSs transmit signals for one cell edge MS, the use of BSC can also increase the inter-cell interference, which might degrade the network performance. In this paper, with a focus on this tradeoff, we propose an adaptive BSC scheme in which BSC is only performed for the cell edge MSs that can achieve a significant capacity increase with only a slight increase in inter-cell interference. Moreover, a channel reallocation scheme is proposed in order to further improve the performance of the adaptive BSC scheme. The simulation results reveal that, compared to the conventional FFR scheme, the proposed schemes are effective for improving the performance of FFR networks.