a study on the spectrum efficient multi-hop wireless network

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CHAPTER 2 Mobile Ad-hoc Network 2.1 Introduction With significant increase in the popularity of wireless networks, more and more communication engineers showed their interest in implementing mobility in the wireless networks [2]. Mobile Ad-hoc networks consist of wireless stations which communicate with each other without a centralized access point or any kind of established infrastructure. Stations that are within each other’s coverage range can communicate directly, while others (which are not within each other’s coverage range) depend on their neighboring stations to route information towards destination. Since the stations can act as routers or clients, they can easily join or leave the network freely. The self configuring advantage of Mobile Ad-hoc networks resulted in a highly dynamic network environments [10]. Such networks can be utilized in various fields such as, emergency cases like natural disaster (earthquakes, typhoons, tsunami, etc.), battlefields and emergency medical situations [11]. Other application includes the Wireless Community Networks to provide broadband Internet access to communities that previously didn’t have such access due to terrain or cost restrictions [12]. Figure 2.1: Data forwarding to unknown destination 9
Routing protocols were developed to overcome limitations of the Ad-hoc mobile networks (MANET) such as high error rates, low throughputs and high power consumption [2], [2]. It’s a difficult task to maintain a route path for a long time in MANET due to limited resources (bandwidth, battery, etc), limited security and multi-hop nature. These limitations create a lot of constraints on the routing protocols [11], [4]. Moreover, Ad-hoc networks have lower capacity compared to WLANs although they utilize the same radio technology, channel reservation and data link protocols. Fig 2.1 illustrates the information exchange between neighboring stations in order to discover the best route between the source and destination. The yellow area represents the field in which the station can communicate with others. The black lines represent the request from the source stations to send data, and the blues lines indicate the reply for request from the destination. 2.2 Ad-hoc On Demand Distance Vector (AODV) The control information sent by stations in ad-hoc networks limits the capacity of the network. These control information are required to maintain the routing information while allowing mobility to the stations in the network. Each node in the network is required to locate a route to the destination and announce this routing information to the neighboring stations. One of the challenges in large networks is the congestion due to the large amount of control massages which consume a major part of the available bandwidth [14]. Routing protocols are categorized as reactive or proactive protocols. Proactive routing protocol such as Optimized Link State Routing Protocol (OLSR) maintains reliable routing information in the network by updating the topological information of the network continually. This is done through announcing (broadcasting) any changes in the route information to other nodes. This information is stored in the routing tables within the mobile nodes. On the other hand, the reactive routing protocol such as Ad-hoc On Demand Distance Vector (AODV) differs in that it defines the most suitable route from source to destination only when required. In this case, the route discovery is initiated when need by the source node. Once the route is established, it will be maintained by the route maintenance procedure until the route is no longer desired or the destination is no longer accessible from all routes[2][14]. 10
Page 1: A STUDY ON THE SPECTRUM EFFICIENT M
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Page 10 and 11: Table of Contents Abstract in Japan
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Table 5.2:Throughput of Mutli-hop W
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PathLoss ( dB) = 40 + [35log10 D( m
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Figure 5.17: Actual Interference ca
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Figure 5.20: Attenuation value vs.
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Figure 5.22 illustrates the S 21 pa
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link. The experimental results show
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Scenario A.1 This scenario simulate
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Destination address Table Table A.1
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Figure B.2: Attenuation value vs. t
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[10] S Gowrishankar, T G Basavaraju
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[32] Jing Zhu and Roy, S., “802.1
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