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1 Abstract--In this paper we revisited a methodology for planning and capacity evaluation of community-deployed wireless mesh networks in rural areas, based on radio equipment parameters for WiMax technology. The capacity is described by the maximum end-to-end transmission rate (throughput) provided to each node that composes the network utilizing interference-based link scheduling. A community-deployed scenario for Internet access is studied utilizing 13 sites in rural communities located in the north center highland region of Nicaragua in Central America. To reduce the Internet service cost shared common access points are used in mesh configuration under asymmetric traffic demands. The radio propagation environment is estimated utilizing free-available tools that can be used to support rapidly-deployable broadband networks. Finally, the (upper-bound) capacity resulting from this approach is computed by applying nonlinear optimization, and the results show a substantial gain in comparison with Wi-Fi networks operating on similar conditions. Index TermsRural Communications, Wireless Mesh Networks, Community-deployed networks, Wimax. I. INTRODUCTION ICARAGUA is the largest country located midway across Central America, but one of the least densely populated. Like its economic indicators, Nicaraguas fixed-line teledensity and mobile penetration is one of the lowest in the subregion. Since 1990s important policy reforms has been done by countries of Central America. The reforms have fostered private sector investment in telecommunication services and infrastructure providing benefits to their citizens who now, at least in urban areas, have access to several telecommunication services. However, although we have observed tremendous growth in infrastructure and services (voice and data), it seems to be economically difficult to extend these benefits to rural areas without the financial support of the government [1]. So far, the rural areas far from the main cities have been unattractive to private investors due to low population density, long distance, and usually irregular terrain together with low incomes of potential users. In par-ticular, this problem continues to be a challenge to the governments of developing countries, whose ultimate goal is to eliminate the digital divide. This work was supported in part by the Faculty of Electrical and Computer engineering (FEC) from UNI, Managua, Nicaragua. In countries with so many needs, one may think that investment in telecommunications might have low priority level. However, for instance the Nicaraguan government recognizes that the development of and access to telecommunication means is a key enabler [2] in promoting job creation, knowledge-based growth, business innovation, access to valuable information, and can be utilized to improve education and health-care assistance. Fig.1 shows the general vision of the Regulator of Nicaragua (TELCOR). To guaranty universal access to telecommunications to all citizens of the country requires reducing what is called by the regulator the market efficiency gap and the real access gap (aimed to be financed by the Telecommunication funds called, FITEL by its name in spanish). Furthermore, since the broadband market is extremely very low in Nicaragua, with less than 1% penetration. Recently, TELCOR has announced plans for developing universal broadband access as well, in order to boost the economic growth of the country. Broadband technology for rural communications seems to be a key element in this strategic planning. Fig. 1. The general vision of the Nicaraguan Regulator regarding universal access (version of the original in Spanish, www.telcor.gob.ni). In this context wireless mesh networks (WMNs) are an appealing technology to provide broadband rural area communication. WMNs are those networks that mix the two topologies of wireless networks, Ad-hoc topology and infrastructure topology. The used of this technology could influence important changes to the current mechanisms used regarding the financial support done by governments. By Wireless Mesh Network Based on Wimax: A Broadband Technology for Rural Comunications Oscar Somarriba Jarqun, Member, IEEE National University of Engineering (UNI), Managua, Nicaragua Tel:+ 505 22781460, e-mail: oscar.somarriba@uni.edu.ni N 2 taking advantage of the self-organizing capability of mesh networks the communities themselves or even new potential local players can take an active part in the solution to their own needs of telecommunications. However, even in the foreseen scenario where potential users are assumed to be fixed, urge the availability of easy-to-use and free-of-charge tools for network planning and capacity estimation as the one presented in this paper. Recent work on this area have make used of simulation tools to analyze the performance in Wimax networks like the one in [4], and [5], however their work has focus on the performance analysis and testbed rather than a common frame work to facilitate community network planning. The contribution of our work is to apply a methodology of planning for community-deployed mesh networks making, this time based on Wimax (Worldwide Interoperability for Microwave Access) technology. By the way, Wimax is the commercial name of the IEEE 802.16. Besides, a Wimax network has been rolled out with an initial coverage over our capital, Managua, in order to provide internet services during the fourth quarter of 2009. This network works mainly based on the infrastructure mode suitable for urban environment, accordingly to the cellular paradigm. On the other hand, WiMAX shares Wi-Fi's strength of being a wireless technology and of allowing for even cheaper use of unlicensed spectrum. Besides, WiMAX provides additional range and better quality of service [6]. So, we will utilize of the free software called Radio Mobile that incorporate topographical information (with free available cartography) combined with the use Google EarthTM [3]. Using these tools we will present an approach that could be used for the network deployment and then we will revisit our methodology [1] for capacity evaluation. The capacity is described by the maximum end-to-end transmission rate (throughput) provided to each node that composes the network. We denote the throughput by and N is the number of nodes in WMNs, respectively. The remainder of the article is organized as follows. In Section II we present the system model and methodology we apply to study the capacity analysis of a rural region in our country. Next in Section III, we then describe the community-deployed networks and capacity evaluation of them. Finally in Section IV, we have the concluding remarks of the study. II. SYSTEM MODEL AND METHOD OF ANALYSIS We will present as an illustrative example the deployment scenario for Internet access for 13 sites in rural communities of Nicaragua introduced in [1]. These communities are located in the north central highlands region of the country, at the departments of Estel, Madriz and Nueva Segovia. Fig. 2 shows the geographical locations for the communities of interest utilizing a digital map of the terrain. The general research question of interest that we would like to answer is: What is the capacity that a community-deployed MWNs can provide subject to low cost deployment constrain for internet access for the 13 telecenters utilizing Wimax? For low-cost user-deployment we consider the following: Share internet access: for low-cost internet service (network service recurrent cost) nodes share access provider. Utilization of radio equipment parameters on the 2.4GHz frequency bands (WiMax physical layers). Similar rules to the FCC part 15 have been adopted in Nicaragua through the rules in AA001-2006. We follow a similar approach to the one presented in [1] but also considering the use of mesh networking with parameters for WiMax technologies similar the ones utilized in [7] but at 20MHz (bandwidth), in the unlicensed 2.4 GHz frequency band. A. Capacity Evaluation To share common Internet access points in a mesh configuration we assume asymmetric traffic demand from each node to a gateway node connected to the internet and the other way round. In addition to that, we assume that the average traffic from a node to the internet is 10% of the traffic from the internet to that node. This is a reasonable assumption if for instance the gateway is connected via an ADSL (Asymmetric Digital Subscriber Line) service over the PSTN (Public Switched Telephone Network) and we share this connection providing similar capacity to all the rural telecenters. The user-deployed scenario is analyzed estimating the radio propagation environment of located nodes. The path-losses in the network are derived utilizing the digital map GTOPO30 with the Longley-Rice model as implemented by the simulation program Radio Mobile [3]. The (upper-bound) capacity resulting from a user-deployed approach is evaluated by finding the link transmission schedule applying nonlinear optimization [8]. Fig. 2. Rural communities of Nicaragua involved in the study (120 km 80km). Source: Map was derived using the freeware software Radio Mobile [3]. 3 B. Analysis and User-deployed Methodology We can summarize the methodology applied in the next sections by the following steps from [1]: I) Network Deployment (User-deployment): i. Determine the radio network parameters in use ii. Define the Internet gateway to be used iii. Determine the link budget between station including the gateway (this is done with Radio Mobile) iv. Establish the current network topology v. If there are nodes that cannot reach the gateway, add digi-repeater nodes (digipeaters) to extend the connectivity by multihopping and go to step Iiii. II) Capacity Analysis Deployment: i. Define the external traffic load demand from each node to the Internet gateway and conversely ii. Calculate the routing matrix iii. From step IIi and IIii estimate the link traffic load of the network iv. Compute the equivalent path-link routing matrix Rmesh to assess the real relative traffic load v. Determine the network capacity by interference-based scheduling (STDMA). At the early stage of the user-deployment, the network starts composed only by the nodes located at the communities. Then, progressively from the gateway towards the communities, the users add digital-repeaters (if that is necessary) to connect the network. Next, to determine the network topology we assume that the hardware utilized has the physical layer parameters shown in Table I. Those parameters are based on utilizing equipment with similar physical layer to IEEE 802.16-2004 group (IEEE 802.16d) operating on the unlicensed 2.4GHz frequency band. Mesh Mode is an optional topology for user-to-user communication in non-line of sight IEEE 802.16. It is included in the standard to allow overlapping, ad hoc networks in the unlicensed spectrum and extend the edges of the wireless range at low cost. Mesh support has been extended into the licensed bands too. Moreover, to find the path losses, we assume utilization of a 20MHz channel on IEEE802.16d that may correspond to operate on the frequency range: 2401 MHz- 2421 MHz. To determine the radio propagation path losses we have used the Radio Mobile freeware software with 20 meters antennas height in the nodes, and higher antenna heights in the Internet gateways that will be introduced in the following sections. C. Traffic Model We assume that the average from node to the internet is 10% the traffic from the internet to the nodes. This seems a reasonable assumption if for instance the gateway is connected via an ADSL (Asymmetric Digital Subscriber Line) service and we would like to share this connection providing similar service to all telecenters connected to the same gateway. In ADSL over Plain Old Telephone Service (POTS), ITU G.992.1 Annex A standard, the downstream rate is 12Mbps and the upstream rate is 1.3 Mbps (which is 10.8% the downstream rate). TABLE I WIMAX PHYSICAL LAYER PARAMETERS D. STDMA Scheduling for Mesh Network To find the interference-based scheduling for constant transmission power and variable rate systems we follow a procedure similar to the one described in [1]. Using the available rate sets and required SINR in Table I we find the sets of cliques containing links having the property that all links in the same clique can transmit simultaneously selecting one of the available data rates. The columns of S can be linearly combined to create the STDMA (Spatial TDMA) schedule by defining the vector of weights o = [o1 oK]T corresponding to the fraction of the time that each column vector of S is activated within a STDMA frame. Hence, for a given o the allocated link capacity, c = [c1 cL]T is given by (1) 4 The capacity allocation can be done through a scheduling algorithm. The scheduling algorithm allocates slots and transmission rates depending on the amount of traffic passing though each link and the objective function to be maximized. In order to find the interference-based schedule for max-min fair allocation we utilized the column generation method [8], for constant transmission power and variable transmission rate as formulated in [9] but with the redefined mesh equations derived in the paper [1]. That is, we find the columns S, o and Amesh = [1p] that solve the following optimization problem: maximize min subject to i min i ; Rmesh Amesh s S o; ok = 1; min 0 ; Amesh 0 ; 0s o s 1 ; III. USER-DEPLOYED AND CAPACITY EVALUATION FOR RURAL COMMUNITIES IN NICARA...

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