BER Prediction in Partially Blocked Rayleigh Channels for Distributed Antenna Systems

Distributed antenna systems (DASs) are known to be effective to enhance coverage, spectral efficiency, and reliability in mobile communication systems. Because multiple antennas are physically separated in space, DASs benefit from both micro- and macro-diversity, which makes DASs significantly more robust compared to conventional co-located antenna systems in fading channels. However, when multiple antennas are not dispersed enough, there exists a certain degree of correlation in large-scale fading (shadowing), which degrades the macro-diversity gain. In practice, various measurements indicate a high degree of correlation of shadowing in DASs. However, most of the previous studies on DASs have not considered the correlated shadowing and its corresponding performance loss. Motivated by this limitation, we analyze the impact of the correlated shadowing to better evaluate DAS-based schemes with dual diversity transmitters. Assuming that shadowing correlation is an exponentially decreasing function of the inter-element separation, we derive the outage probability of DAS in composite Rayleigh-lognormal shadowing channels. Also, we present numerical and simulation results, which indicate there exists an optimal inter-separation between antennas that minimizes the outage rate to balance a trade-off between macro-diversity and path loss.

Two main concerns for designing a wireless system are more network capacity and less energy consumption. Recently, distributed antenna system (DAS) has received considerable attention due to its potential to provide higher spectral efficiency (SE) and uniform coverage for cellular networks. In this regard, this paper compares the performance of DAS with centralized antenna system (CAS) in LTE-A system in terms of energy efficiency (EE), where practical restrictions such as out-of-cell interference, path loss, and small scale fading are taken into account. Furthermore, the EE and system power consumption are investigated under three different cell-load scenarios (high, moderate, and low load) where different numbers of antennas are activated and remaining of antennas are under sleep mode. Finally, based on the tradeoff between power-saving and EE, two optimal DAS antenna deployments are proposed for low and moderate cell-load scenarios. The results reveal that DAS considerably outperforms CAS in terms of EE and by optimal deploying antennas of DAS significant power-saving and EE are achievable. The proposed methodology achieved savings of up to 27.63% in terms of energy savings in a macrocell with guarantee of a high capacity of data.

In order to demonstrate the channel capacity improvement by multiple-input multiple-output (MIMO) transmission techniques in distributed antenna systems (DAS), the channel capacities of both centralized antenna systems (CAS) and DAS are compared assuming spatially correlated shadowing. Many studies deal with these channel capacities assuming spatially independent shadowing. In this paper, we compare the characteristics of MIMO channel capacity in CAS and DAS under the effect of distance-dependent path loss, spatially correlated shadowing loss, Rayleigh fading, and inter-cell interference. Computer simulation results indicate that DAS-MIMO transmission can significantly reduce the spatially correlated shadowing loss, thus improving the outage capacity compared to CAS-MIMO transmission. Furthermore, the simulation results also show a relationship between inter-antenna distance and channel capacity.

Sum Rate and Power Consumption of a Circular-Layout Distributed Antenna System with MMSE Receivers

An efficient uplink user selection algorithm for distributed antenna systems (DAS) is proposed in this paper. Previous user selection algorithms in multiple-input-multiple-output (MIMO) systems are designed for conventional MIMO systems where antennas are located together. Since DAS can be thought as a variation of MIMO systems, the user selection algorithms which are originally designed for conventional MIMO systems can also be applied to DAS. However, the channel characteristics of DAS are different from those of conventional MIMO systems. Thus there should be specific user selection algorithm for DAS environments which utilizes the channel characteristics of DAS. This paper proposes an efficient uplink user selection algorithm specified for DAS. Simulation results show that the proposed algorithm gives near optimal performance which reaches up to 98.5% of the optimal spectral efficiency. Furthermore, the complexity of the proposed algorithm is also examined and the results show that it is easy to implement in practical systems.

As small cell solutions for efficient in-building wireless deployment, the distributed antenna system (DAS) and Femtocells constitute two major options. In this work, we study the Total Cost of Ownership (TCO) in combination with system performance in order to reach technology-economical conclusions regarding of these deployment options. Our aim is to identify the most cost economical solution for indoor wireless deployment which meets the indoor capacity need and provides ubiquitous indoor coverage. In the analysis we focus on LTE enhancement in the enterprise buildings. We discuss the unique cost features of DAS and Femto systems and highlight the importance of backhaul visibility in the cost analysis. For enterprise building solutions, we show the cost advantage of low-cost Femtocells over DAS in all scenarios regardless of coverage building size. We also suggest when DAS becomes more economical for large buildings with low data traffic need.

This study proposes an integrated framework of single-selection distributed antenna systems (DAS) and simultaneous wireless information and power transfer (SWIPT) with orthogonal multiple access (OMA), and analyzes the synergetic effects of SWIPT and DAS. To demonstrate the performance gains of the proposed SWIPT-enabled OMA with DAS, we jointly optimize power allocation for the OMA and power splitting (PS) ratio for energy harvesting of SWIPT with three different optimization goals: sum-rate maximization, user fairness, and energy efficiency. Although all of the above optimization problems are non-convex, the closed-form solutions of the problems maximizing the sum-rate and fairness are presented. Owing to difficult analytical tractability of the problem maximizing the energy efficiency, the problem is divided into three subproblems: power allocation for the base station (BS), power allocation for radio remote unit (RRU), and PS ratio assignment. Then, an iterative algorithm is presented to provide the energy-efficient SWIPT-enabled OMA with DAS. Theoretical findings are validated by numerical results, which show that the framework of applying DAS to SWIPT-OMA improves data rates and energy efficiency compared to SWIPT-OMA without DAS, while satisfying the minimum rate and harvested energy requirements.

The wireless power transfer via an electro-magnetic (EM) wave enables far-field power transfer. In this paper, we provide an analytic and experimental study on a distributed antenna system for the wireless power transfer as a mean to overcome low end-to-end power transfer efficiency of a conventional collocated antenna system. We study the wireless power transfer system with or without the frequency and phase synchronization between antennas. Based on the experimental results, we show that the distributed antenna system is advantageous in terms of the coverage probability as long as the optimal distributed beamforming is available in the distributed antenna system.

This paper formulates resource allocation problem in orthogonal frequency division multiplexing (OFDM) distributed antenna systems (DAS) by extending conventional one in OFDM co-located antenna systems (CAS). The algorithm to achieve maximum rate-sum capacity is derived, and the achievable capacity of a single user is also given by theoretical analysis. Simulated and theoretical results show that OFDM DAS can achieve much more rate-sum capacity than OFDM CAS, and the performance gain increases with the number of antennas in systems.

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).

Opportunistic packet scheduling optimization problem in orthogonal frequency division multiplexing (OFDM) distributed antenna systems (DAS) is investigated by this paper. Physical-layer channel state information (CSI) and wireless links' requirements for bit error rate are taken into account during problem formulation. The optimization aim is to minimize packet loss rate (PLR) subject to limited wireless resource, which is characterized by power, subcarrier, antenna et al. According to the characteristics of users' packet queues as well as CSI, the proposed algorithm adaptively allocates wireless resource to users to exploit as much spatial and multiuser diversity as possible. Simulation results show the proposed algorithm achieves the lowest PLR in all compared algorithms. Further more, the proposed circular DAS significantly outperforms co-located antenna systems (CAS) due to distributed antenna deployment.

In this paper we extend the concept of the well-known input–output clustering (IOC) technique in Uykan et al. (IEEE Trans Neural Netw 11(4):851–858, 2000) to antenna location optimization problem in wireless networks and propose an input–output space clustering criterion (IOCC) to optimize the locations of the remote antenna units (RAUs) of generalized distributed antenna systems (DASs) under sum power constraint. In IOCC, the input space refers to RAU location space and output space refers to location specific ergodic capacity space for noise-limited environments. Given a location-specific arbitrary desired ergodic capacity function over a geographical area, we define the error as the difference between actual and desired ergodic capacity. Following the major steps of the well-known IOC technique in Uykan et al. (IEEE Trans Neural Netw 11(4):851–858, 2000) and Uykan (IEEE Trans Neural Netw 14(3):708–715, 2003) we show that for the DAS wireless networks: (1) the IOCC provides an upper bound to the cell averaged ergodic capacity error; and (2) the derived upper bound is equal to a weighted quantization error function in location-capacity space (input–output space) and (3) the upper bound can be made arbitrarily small by a clustering process increasing the number of RAUs for a feasible DAS. IOCC converts the RAU location problem into a codebook design problem in vector quantization in input–output space, and thus includes the Squared Distance Criterion (SDC) for DAS in Wang et al. (IEEE Commun Lett 13:315–317, 2009) (and other related papers) as a special case, which takes only the input space into account. Computer simulations confirm the theoretical findings and show that the IOCC outperforms the SDC for DAS in terms of the defined cell averaged “effective” ergodic capacity.

Recently, much attention has been drawn to distributed antenna systems (DAS), which are proposed to improve the performance of mobile communication systems. This paper focuses on the analysis of the average symbol error rate (SER) of DAS over a generic composite channel. Initially, a new composite channel model is considered for DAS, which is a mixture of path loss, lognormal shadowing and generalized-Gamma fast fading. This composite channel model is a generic model, which includes many well-known composite channel models as special cases. Based on the channel model, the cumulative distribution function of the output signal-to-noise ratio is obtained by employing selective transmission scheme. Moreover, by averaging the channel conditions and the positions of the MS in the cell, an approximate expression of the average SER is derived, which is a unified form of expression for many commonly used modulation schemes. Numerical results show that the derived expression of the average SER can provide sufficient precision for evaluating the SER performance of DAS under different modulation schemes.

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.

The network planning is a key factor that directly affects the performance of the wireless networks. Distributed antenna system (DAS) is an effective strategy for the network planning. This paper investigates the antenna deployment in a DAS for the high-speed railway communication networks and formulates an optimization problem which is NP-hard for achieving the optimal deployment of the antennas in the DAS. To solve this problem, a scheme based on an improved cuckoo search based on dimension cells (ICSDC) algorithm is proposed. ICSDC introduces the dimension cell mechanism to avoid the internal dimension interferences in order to improve the performance of the algorithm. Simulation results show that the proposed ICSDC-based scheme obtains a lower network cost compared with the uniform network planning method. Moreover, ICSDC algorithm has better performance in terms of the convergence rate and accuracy compared with the conventional cuckoo search algorithm, the particle swarm optimization, and the firefly algorithm.