Clustering for determining distributed antenna locations in wireless networks

In order to improve the system capacity of distributed antenna system (DAS) in downlink high-speed train (HST) environments, this paper presents a power allocation scheme for remote antenna units (RAUs) based on the cooperative distributed antenna system (CDAS). The investigated power allocation scheme exploits the channel state information (CSI) between RAUs and vehicle-mounted relay (VMR). Based on the CDAS-CSI power allocation, a corresponding RAU selection algorithm is introduced to quickly find the suboptimal solution that maximizes the channel capacity and to optimize the number of RAUs in CDAS. Simulation results show that the CDAS-CSI power allocation greatly improves the downlink system capacity compared to the cases of non-cooperation among RAUs and equal power allocation among RAUs.

Distributed antenna system (DAS) can extend the cell coverage, increase the system capacity and decrease the other-cell interference. Dynamic spectrum access (DSA) can improve the whole system spectrum efficiency by allowing secondary system to access the licensed frequency bands. In this paper, a distributed-antenna based secondary system(DABSS) is considered, in which the antenna location is designed to obtain the maximum ergodic capacity of the secondary system. Particularly, a new metric called squared distance divided power criterion (SDDPC) is proposed to simplify the analysis of ergodic capacity. A linear DABSS is considered and the analytical solution of antenna location is derived using the squared distance divided power criterion. Simulation results show that the ergodic capacity using the proposed antenna location is closed to the maximum ergodic capacity.

In this paper, a distributed antenna system (DAS) is investigated for indoor high data rate wireless transmission in high buildings. In the proposed indoor DAS, radio transmission/ reception within several neighbouring floors is controlled by one central unit (CU) by exploiting the whole system bandwidth. However, the frequency channels can be reused among the CUs which results in co-channel interference. The capacity of the system is analyzed considering direct propagation inside the building and reflection from a nearby building. The impact of several system parameters, such as the position of the user on the floor, the number of remote antenna units (RAUs), the shape of the floor and the position of the RAUs on the performance is discussed.

In ultra-dense cellular networks, research works on enhancing cell edge performance receive considerable attention. Based on interlaced clustering, we propose a heuristic sparse beamforming strategy to improve the cell edge throughput effectively in distributed antenna systems (DASs). In our scheme, each cluster pattern (CP) is divided into several adaptive cells, where all the remote antenna units (RAUs) are connected to a central processor via finite-capacity backhaul links. Relying on the adaptive cells, we then provide a low-complexity alternating optimization algorithm for the high-burden sparse beamforming design. Simulations based on practical cell parameters show that the proposed adaptive cell based sparse beamforming can achieve significant performance gain on edge user rate and further improved the sum rate.

This paper presents an estimation method of the location of user equipment (UE) using the velocity measure based on Doppler frequency shift in square distributed antenna system (DAS) layout. When the UE enters the cell, all remote antenna units (RAU) estimate the entering border of the cell, the initial entering position, the velocity of the UE, then update the new position till the UE move out from the cell. Thus the moving track of UE can be estimated. The performance is theoretically analyzed and simulations are performed to verify the correctness

In this paper, the downlink performance of multi-cell distributed antenna systems (DAS) with a single user in each cell is investigated. Assuming the channel state information is available at the transmitter, four transmission modes are formulated as combinations of remote antenna units (RAUs) selection and cooperative transmission, namely, non-cooperative transmission without RAU selection (NCT), cooperative transmission without RAU selection (CT), non-cooperative transmission with RAU selection (NCT_RAUS), and cooperative transmission with RAU selection (CT_RAUS). By using probability theory, the cumulative distribution function (CDF) of a user’s signal to interference plus noise ratio (SINR) and the system ergodic capacity under the above four modes are determined, and their closed-form expressions are obtained. Furthermore, the system energy efficiency (EE) is studied by introducing a realistic power consumption model of DAS. An expression for determining EE is formulated, and the closed-form tradeoff relationship between spectral efficiency (SE) and EE is derived as well. Simulation results demonstrate their consistency with the theoretical analysis and reveal the factors constraining system EE, which provide a scientific basis for future design and optimization of DAS.

For the energy sharing problem of distributed antenna system (DAS) with energy harvesting (EH), a distributed antenna system model capable of sharing collected energy among the components in system is proposed. Compared with the existing model in literatures, the proposed model connects with smart grid through a unified interface and facilitates energy management and scheduling. Based on the proposed model, three kinds of energy sharing methods including the partial energy sharing method, the complete energy sharing method and the self-sustaining energy sharing method are analyzed. Under various energy sharing methods, the corresponding optimization problems of power allocation among the remote antenna units (RAUs) are described, formed and solved. As a result, the corresponding power allocation algorithm to each method has been concluded. Simulation results show that the proposed model is more efficient in terms of the channel capacity and energy efficiency, compared to the existing model.

This paper aims to find optimal antenna locations that maximize the cell averaged ergodic capacity for the distributed antenna system (DAS) with selective transmission (ST) in the downlink. We propose the squared distance criterion (SDC) and convert the antenna positioning problem to the codebook design problem. According to the SDC, we derive the suboptimal antenna placements for the linear and circular cells with uniform and non-uniform distribution of the mobile station. Simulation results show that the obtained antenna positions are near optimal and DAS with optimized antenna positions offers a large capacity gain over the traditional co-located antenna system (CAS).

Distributed antenna systems have been found to be an elegant solution for the problems arising in high-data-rate wireless communication, particularly in large service areas. This article considers radio over fiber links as an essential part of the DAS, connecting the central unit with the remote antenna units. In particular, we analyze and discuss delays and nonlinearities stemming from the RoF links. In addition, we study the compensation for these impairments. Our studies indicate that the RoF links are a viable and cost-effective solution for implementing the DAS, although some of the RoF link non-idealities require compensation.

Distributed Antenna Systems (DAS), wherein multiple antennas are distributed across the cell with the antennas being connected to the base station via a wired connector have been proposed as a means to improve coverage and capacity of traditional cellular systems. In this paper, we introduce the concept of Coordinated Antenna System (CAS), a variant of the DAS system wherein the antennas are context aware. A CAS deployment can be visualised as a controller unit and several remote antenna units (RUs) distributed in a physical premises such as an office, a shopping mall etc. with the controller unit handling the resource management of the different RUs connected to it. Even though such an architecture looks promising from the perspective of improving coverage and capacity (through better frequency reuse), interference issues need to be carefully addressed. This paper proposes a resource management mechanism for CAS (called CRRM) and highlights findings from its performance evaluation. CRRM is simple from an implementation perspective, adaptive to changes in the underlying radio environment and helps to avoid/minimise interference as indicated by the findings from the performance evaluation.

This paper presents a capacity enhancement algorithm by using cooperative transmission in distributed antenna system (DAS) under line-of-sight (LOS) multiple-input-multiple-output (MIMO) channels in high speed train scenario. In this algorithm, the Base Band Unit (BBU) of the DAS selects multiple Remote Antenna Units (RAU) according to the large-scale fading parameters, and cooperative transmission is then performed among these RAUs to increase channel capacity. WINNER II channel model is considered for the capacity analysis. Simulation results show that cooperative transmission greatly increases capacity under LOS MIMO channels in high speed train scenario.

In the wireless broadband network, most traffic are generated from indoor users. Meanwhile the indoor coverage is identified as the major bottleneck especially in dense urban environment with high-rising buildings. In this paper, the TD-LTE network downlink performance of indoor is studied with various network deployment options, including outdoor Macro cell, outdoor Micro cell, indoor distributed antenna system (DAS), indoor Femto cell, and their combinations in a realistic large-scale dense urban scenario. Since a DAS cell consists of several or even tens of access points (AP), the computation load is too high to be accepted when calculating the received signal power and the interference power by traditional widely-used methodology. Thus a new DAS model is proposed to decrease the computation complexity to a reasonable level in the simulation. To have more accurate channel modeling, the real three-dimensional (3D) city map of the investigated area is employed. A 3D ray-tracing tool is used to estimate the large scale propagation occurring between outdoor sites and buildings. The traffic offloading features of Micro, DAS, and Femto cell are evaluated through system simulations.

It is known that distributed antenna systems (DAS) using radio-over-fiber (RoF) links are able to increase coverage and to improve energy efficiency compared to traditional wireless access networks. In this paper, we focus on the energy efficiency of 802.11n RoF DAS architectures and we provide a methodology based on ns-3 to evaluate and optimize energy consumption in those environments. Our results confirm that there exists an optimal number of distributed antennas for a given scenario. Furthermore, we show that aggregation mechanisms included in IEEE 802.11n enable to further improve the energy efficiency in RoF DAS. Finally, we demonstrate that media access control protocol data unit aggregation techniques outperform media access control service data unit aggregation schemes in providing higher end-to-end throughput and a better energy efficiency in IEEE 802.11n RoF DAS.

Distributed antenna system (DAS)-aided unity frequency reuse (UFR) and fractional frequency reuse (FFR) transmission scenarios are investigated in this paper, employing the classic multiobjective of nondominated sorting genetic algorithm II (NSGA-II) for maximizing cell throughput and the coverage. More specifically, coordinated multipoint (CoMP) cooperation is invoked among the distributed antennas (DAs) and the base station (BS) in support of the mobile stations (MSs) roaming at the cell edge, while considering a range of practical impairments. We demonstrate that the received signal-to-interference ratio (SIR) of non-CoMP transmissions follows the lognormal distribution by taking into account both fast fading and large-scale shadowing and path-loss effects. Our simulation results demonstrate that DAS-aided cooperation is capable of achieving a fivefold increased throughput over that of the traditional arrangement. Explicitly, an average throughput per channel of 6.61 bits/symbol may be achieved.

Despite extensive studies on the capacity analysis of distributed antenna systems (DASs), how to derive the average ergodic capacity in a closed form still remains largely unknown, which is mainly attributed to the lack of explicit expressions of ergodic capacity and joint distribution of large-scale fading coefficients. To address this issue, this paper first proposes closed-form approximations, i.e., zero order and first order, of the asymptotic ergodic capacity by solving the fixed-point equations using an iterative method, where a flexible tradeoff between accuracy and computational complexity can be achieved by adjusting the number of iterations. For a large-scale multi-user DAS with both users and base station antenna clusters uniformly distributed in a circular cell, the proposed zero-order approximation of the ergodic sum capacity is further averaged over the large-scale fading coefficients to obtain a closed-form approximation of the average ergodic capacity by approximating the large-scale fading coefficients as independent and identically distributed Pareto random variables. Simulation results show that the proposed approximation of the average ergodic capacity is accurate in various scenarios, which sheds plenty of practical insights for system design.