Green Wireless Network Deployments in Indoor Environments Using Radio-over-Fiber Distributed Antenna Systems

International Journal of Networks and Communications 2012, 2(6): 142-147 DOI: 10.5923/j.ijnc.20120206.02 Green Wireless Network Deployments in Indoor...
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International Journal of Networks and Communications 2012, 2(6): 142-147 DOI: 10.5923/j.ijnc.20120206.02

Green Wireless Network Deployments in Indoor Environments Using Radio-over-Fiber Distributed Antenna Systems Yves Josse* , Frédéric Lucarz, Bruno Fracasso Optics department Telecom Bretagne, Institut M ines-Telecom, Brest, CS83818 29238, France

Abstract Distributed antenna systems (DAS) are known to improve coverage and performance of wireless communicat ions in indoor environ ments. In the present paper, we propose a method to determine the position of distributed antennas that optimizes the network capacity for a given deployment scenario. We also consider power consumption measurements of commercially-available W i-Fi access points and dongles, in order to quantify the energy efficiency of a DAS using Radio-over-Fiber (RoF) technologies. Our results show that there exists an optimal nu mber of distributed antennas for a given topology of the indoor environment. Keywords Green Wireless, Rad io-Over-Fiber, Energy Efficiency

1. Introduction Capping the power consumption of mobile and wireless networks, whilst accommodating growth in the number of subscribers, has become a crucial issue in view of the growing need for un-tethered and ubiquitous connectivity. Within that context, new strategies for greener telecoms are being extensively researched to reach higher energy efficiency and greater power saving, not only for terminals to increase their battery life, but also for access points to reduce their carbon footprint. Furthermore, demands on throughput and performance keep on increasing, with extended coverage especially in indoor environments, such as homes and public places (stadiums, co mmercial centres, transport hubs) where users are densely located. Distributed Antenna Systems (DAS) are kno wn to improve coverage[1] and performance o f wireless commun ications in indoor environments. One approach for reaching higher energy efficiency consists in forming s maller coverage cells by reducing the transmit power at each antenna site[2]. A future-proof and high-capacity optical communicat ion network can be advantageously provided to interconnect all antenna sites. In that case, radio-over-fib re (RoF) transmission techniques are used to transport optically high bit -rate rad iofrequency (RF) signals. The main advantages of RoF distributed antenna systems * Corresponding author: [email protected] (Yves Josse) Published online at Copyright © 2012 Scientific & Academic Publishing. All Rights Reserved

include very low fibre transmission loss, large bandwidth, and low transmit RF power levels, which enable us to improve the coverage of in-building wireless services[3]. In this paper, our aim is to give so me ru les to design an energy-efficient RoF DAS network. In a given configuration, the number and position of distributed antenna is determined to optimize overall energy efficiency.

2. Related Work In order to achieve energy efficiency in wireless networks, a possible approach is to reduce the power consumption of the devices (both access points and terminals) or to optimize the communication protocols to efficiently use wireless interfaces. Many investigations on the electrical power consumption of physical devices and interfaces have been performed in the past[4], main ly focusing on reducing power consumption of devices and thus increasing the battery life. However, reducing the power consumed by the terminal has a relative little impact on the overall energy efficiency of the system since this power is usually lo w (a few mW ). An alternative approach consists in modifying the network arch itecture. For instance, DAS are known to improve coverage and performance of wireless communicat ions while reducing the total radiated power level[5]. So me works, like Zhang et al.[6], focus on the deployment of an energy efficient DAS and propose an algorith m fo r the position of the antennas. By minimizing the average distance between users and distributed antennas, the optimal position of antennas is given in a circular environment. Then considering a constant circuit power and


International Journal of Networks and Communications 2012, 2(6): 142-147

the transmission power for each antenna, the optimal number of antennas is obtained. However, a circuit power independent of the transmission data rate is considered without taking into account the link between the access point and the remote antennas. Crisp et al.[7], model the overall power consumption in a RoF DAS and optimize the output power at each remote antenna to provide a given wireless coverage area. Ho wever, the metric used (power per area unit) does not take performance (e.g., wireless link data-rate) into account, while we consider that the throughput has to be included in the energy efficiency metric in indoor environment.

3. Rof DAS Architecture Design 3.1. Rof DAS Archi tecture Design Figure 1 illustrates the architecture of the RoF DAS network considered in this paper. On the system downlink, RF signals fro m the access point are split electrically by a splitter and adapted by a laser drive amp lifier (ATTN) to a suitable power level to directly modulate a laser diode. The resulting intensity-modulated optical carrier is t ransported over an optical fiber to a photodiode and transimpedance amp lifier (TIA) to perform opto-electrical conversion. The RF signals obtained are simultaneously transmitted wirelessly fro m all distributed antennas (simu lcast transmission) to the terminal after being amplified by a power amplifier (PA). For uplink co mmunications, the same components are used in a symmetrical manner. We are interested in determining the optimized number of antennas and their location to offer the best possible coverage with the highest possible performance. 3.2. Design Methodol ogy The method proposed to design an energy efficient network co mprises the three following steps: • Measuring RF signal attenuations to estimate the average power decay index n that characterizes the indoor

environment. • Calcu lating the position of distributed antennas by maximizing the overall network performance using a defined scenario. • Determin ing the total radiated power and the number of distributed antennas to maximize energy efficiency for a given coverage.

4. Received Power Estimation The user received power is modelled by considering only the link between the distributed antenna and the terminal. Although indoor (RF) propagation has been extensively studied, the received RF power cannot be accurately predicted. Multiple scattering and reflections fro m walls and obstacles, as well as shadowing effects cause strong time and space variations in the received power. This is the reason why a statistical RF propagation model is used, which does not require any topographic database. In a DAS with N antennas, the average power received by the terminal fro m the ith antenna can be expressed (in dBm) as : (1) Pri = Pti + Gti + Gr − PLi

where Pti is the power transmitted by the ith antenna in dBm, Gti and Gr are the transmitter and receiver antenna gains, respectively, and PLi is the path loss in dB between the user terminal and the ith antenna. Considering isotropic antennas, Gti =Gr =0 d Bi, the path loss is modeled as follo ws :

PLi = PL(d 0 ) + 10n log10

di d0


where PL(d 0 ) is the path loss at d0 =1m, PL(d 0 )=40.2d B at 2.4GHz, d i is the distance between the ith antenna and the terminal and n is the power decay index that depends on the wireless environ ment. The prev ious med ian path loss formula was obtained fro m a linear regression of the measured mean signal levels at various locations.

Figure 1. Example of distributed antenna wireless network using radio-over-fiber technology

Yves Josse et al.: Green Wireless Network Deployments in Indoor Environments Using Radio-over-Fiber Distributed Antenna Systems

The total power received by the terminal Pr is the sum of the power received fro m the N antennas. Then, Pr can be used to estimate the capacity of the network and to determine an optimal criterion to place the distributed antennas.

5. Position of the Distributed Antennas 5.1. Positioning Criterion One of the criteria to determine the position of the distributed antennas is to maximize the capacity of the network[8]. This criterion provides an upper limit of the system capacity and enables better performance for mu lti-user cases[9]. The average capacity in bit/s/Hz can be formulated as :

P   C = E p log 2 (1 + r2 ) σ  


where Pr is the power received by the terminal, σ2 is the average power (variance) of the additive wh ite Gaussian noise and Ep {} denotes the expectation with respect to the location of the terminal. 5.2. Application to a Rectangul ar Shaped S pace A rectangular space with dimension 40m × 80m is considered: for instance, the floor of a building containing mu ltip le offices. Using the criterion presented in the previous section (4.a.), the positions of distributed antennas were determined for 1

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