Dense deployments of wireless local area network (WLAN) access points (APs) are accelerating to accommodate the massive wireless traffic from various mobile devices. The AP densification improves the received power at mobile devices; however, total throughput in a target area is saturated by inter-cell interference (ICI) because of the limited number of frequency channels available for WLANs. To substantially mitigate ICI, we developed and described a distributed smart antenna system (D-SAS) proposed for dense WLAN AP deployment in this paper. We also describe a system configuration based on our D-SAS approach. In this approach, the distributed antennas externally attached to each AP can be switched so as to make the transmit power match the mobile device's conditions (received power and packet type). The gains obtained by the antenna switching effectively minimize the transmission power required of each AP. We also describe experimental measurements taken in a stadium using a system prototype, the results show that D-SAS offers double the total throughput attained by a centralized smart antenna system (C-SAS).

This paper proposes a hardware configuration for uplink multi-user multiple-input multiple-output (MU-MIMO) transmissions in a distributed antenna system (DAS). The demand for high-speed transmission in the uplink has increased recently, because of which standardizations in LTE-advanced and IEEE 802.11ax networks is currently underway. User terminal (UT) scheduling on the downlink MU-MIMO transmission is easy even in unlicensed band such as those in wireless local area network (WLAN) systems. However, the detailed management of the UTs is difficult on the uplink MU-MIMO transmissions because of the decentralized wireless access control. The proposed configuration allows an antenna to be selected from an external device on the access point (AP). All AP antennas are divided into groups, and the received signal in each group is input to the amplitude detector via a directional coupler. Subsequently, the selected antenna is fed by a multiple-to-one switch instead of a matrix switch. To clarify the effectiveness of the proposed configuration, we conduct computer simulations based on the ray-tracing method for propagation channels in an indoor environment.

This paper proposes a novel method of reducing channel state information (CSI) feedback by using transmit antenna selection for downlink multiuser multiple input multiple output (DL-MU-MIMO) transmission in dense distributed antenna systems. It is widely known that DL-MU-MIMO transmission achieves higher total bit-rate by mitigating inter-user interference based on pre-coding techniques. The pre-coding techniques require CSI between access point (AP) and multiple users. However, overhead for CSI acquisition degrades the transmission efficiency of DL-MU-MIMO transmission. In the proposed CSI feedback reduction method, AP first selects the antenna set that maximizes the received power at each user, second it skips the sequence of CSI feedback for users whose signal to interference power ratio is larger than a threshold, and finally it performs DL-MU-MIMO transmission to multiple users by using the selected antenna set. To clarify the proposed method, we evaluate it by computer simulations in an indoor scenario. The results show that the proposed method can offer higher transmission efficiency than the conventional DL-MU-MIMO transmission with the usual CSI feedback method.

Downlink multi-point transmission as a capacity enhancement method for the users at cell edge and the operators is studied in this paper. It is based on the so-called aggregate base station architecture using distributed antennas and cloud computing. Its advantages are analyzed by both its architectural side and simulation. The simulation results show that the capacity may be affected by the number of cell belonging to an aggregate base station and by the parameters related to the operation of it.

In this letter, coordinated power allocation (PA) is investigated for the downlink of a generalized multi-cluster distributed antenna system (DAS). Motivated by practical applications, we assume only the global large-scale channel state information is known at the transmitter. First, an upper bound (UB) for the ergodic sum capacity of the system is derived and used as a simplified optimization target. Then, a coordinated PA scheme is proposed based on Geometric Programming (GP), which is demonstrated to be nearly optimal by Monte Carlo simulations.

In this letter, we address the problem of downlink power allocation for the generalized distributed antenna system (DAS) with cooperative clusters. Considering practical applications, we assume that only the large-scale channel state information is available at the transmitter. The power allocation scheme is investigated with the target of ergodic achievable sum rate maximization. Based on some approximations and the Rayleigh Quotient Theory, the simple selective power allocation scheme is derived for the low SNR scenario and the high SNR scenario, respectively. The methods are applicable in practice due to their low complexity.

The distributed antenna system (DAS) offers significant power savings but only if the antennas are properly located. In this letter, we convert antenna location optimization to the codebook design problem. For the widely studied circular-layout DAS with uniform user distribution, we derive closed-form expressions for antenna locations that yield near-optimal performance. For more general user distribution and antenna topology, the codebook design algorithms can provide numerical optimization results with acceptable performance and low complexity.

This letter focuses on the simplified capacity evaluation for the downlink of a distributed antenna system (DAS) with random antenna layout. Based on system scale-up, we derive a good approximation of the downlink capacity by developing the results from random matrix theory. We also propose an iterative method to calculate the unknown parameters in the approximated expression of the downlink capacity. The approximation is illustrated to be quite accurate and the iterative method is shown to be quite efficient by Monte Carlo simulations.

In this letter, the influence of the downlink average ratio of the other cell interference to other-user interference in the serving cell (DARI) on the distributed repeater system (DRS) performance is analyzed. It is found that the improvement of DARI depends on a propagation path loss environment. Applying the computed DARI to a 3-RS DRS cell, as high as 13.9% capacity enhancement was obtained when the path loss exponent is 4.5. In addition, by using the power allocation equation, it is expected that a hexagonal DRS cell without coverage holes or excessive coverage overlap can be realized.

Multilink MIMO technique is a promising technology for cellular networks with a guaranteed quality-of-service. It will provide high capacity and wide coverage. We evaluated the downlink performance of the multilink MIMO system from the perspective of quality-of-service. The presence of Rayleigh fading, shadowing, and path loss was assumed. To evaluate the proposed system, we developed a performance measure for MIMO cellular system. The measure is ergodic capacity taking into account area coverage. Our numerical results show that the area coverage of proposed multilink MIMO system is greatly improved compared with that of the conventional singlelink MIMO system. Using the proposed measure, we also found that the multilink MIMO system could achieve high capacity with guaranteed QoS for a wide coverage.

In this letter, we investigate the sum-rate capacity of a power-controlled multi-user distributed antenna system (DAS) with antennas deployed symmetrically on a circle. The sum-rate capacity, when divided by user number, is proved to converge to an explicit expression as user number and antenna number go to infinity with a constant ratio. We further show how this theoretical result can be used to optimize antenna deployment. Simulation results are also provided to demonstrate the validity of our analysis and the applicability of the asymptotic results to a small-scale system.