The past two decades have marked an unprecedented growth in size and sophistication of almost every aspect of telecommunications. Two major achievements stand out in this development. First, the Internet network, the quintessence of data communications and public/private access to information. Second, Cellular Mobile Radio wireless communication, the untethered jewel of voice communication beyond borders that opened another door to worldwide conversation. As a result, today, there are hundreds of millions of users with continuous access to the Internet and over three billion users of cell phones.

Cellular mobile communications has moved in a decade through three generations. The first generation was marked by the need to build a large physical/geographical presence. The second generation has moved from analog formats to digital communications and added features that allow decent data services running along with voice communications. More recent advancements have led to the third generation of cellular mobile transmission with a focus on providing data services in the class of broadband communications.

In the same span of time, a similar growth has taken place in the wireless expansion of well-established networking technologies, commonly known as “fixed wireless”. The most popular customer premises technology, the Local Area Network, has become Wireless LAN, matching its data rate with wired frontrunners. This metamorphosis has continued by adopting voice communication over a traditional data dedicated technology. Identical phenomena took place in the Wireless Personal Area Network thanks to the Bluetooth, ZigBee, and other technologies.

802.11n is the high throughput amendment to the 802.11 standard. This section describes all the aspects of the physical layer which increase the data rate. MIMO/SDM is a key feature of 802.11n, which is discussed in Chapters 3 and 4. The other significant increase in data rate is derived from the new 40 MHz channel width. This section also discusses short guard interval, Greenfield preamble, and other modifications to the 20 MHz waveform.

40 MHz channel

In the last several years, regulatory domains have made much more spectrum available for unlicensed operation in the 5.47–5.725 GHz band for wireless local area networking. The addition of the new spectrum has more than doubled the number of available 20 MHz channels in the USA and Europe. Table 5.9 and Table 5.10 in Appendix 5.1 describe the current allocation in the USA and Europe, and the corresponding 802.11 channel number. Even with doubling the channel width to create 40 MHz channels, there are still more channels available for frequency re-use than in the early days of 802.11a. Furthermore, products currently in the market with proprietary 40 MHz modes have demonstrated that the cost for 40 MHz products is roughly the same as for 20 MHz products. Therefore, with free spectrum and relatively no increase in hardware cost, doubling the channel bandwidth is the simplest and most cost effective way to increase data rate.

Introduction

The wireless arena has been experiencing exponential growth in the past decade. We have seen great advances in network infrastructures, rapid growth of cellular network users, the growing availability of wireless applications, and the emergence of omnipresent wireless devices such as portable or handheld computers, personal digital assistants (PDAs), and cellular phones, all becoming more powerful in their applications. The mobile devices are becoming smaller, cheaper, more convenient, and more powerful. They can also run more applications on the network services. For example, mobile users can rely on their cellular phones to check e-mail and browse the Internet. They can do so from airports, railway stations, cafes, and other public locations. Tourists can use the global positioning system (GPS) terminals installed in cars to view driving maps and locate attractions. All these factors are fueling the explosive growth of the cellular communication market. As of 2006, the number of cellular network users approached two billion worldwide. Market reports from independent sources show that worldwide cellular users have been doubling every 1.5 years.

In addition to that of the traditional cellular networks, an exponential growth of the wireless access point (AP), which is a device that connects wireless communication devices together to create a wireless network, is also being experienced. The AP is usually connected to a wired network and can relay data between devices on each side. Many APs can be connected together to create a larger network, which is a so-called ad hoc network.

Introduction

Ensuring the security of both the collected data and the process of data collection is vital for the success of WSNs. Because of the constraints of the particular applications and the resource limitations, the security of WSNs is vastly different from that of conventional wired networks. For the example of military applications, wireless sensor nodes usually are sent to an unattended environment (e.g., the battlefield). In these scenarios, wireless sensor nodes are easier to capture or destroy. Thus, the foremost important thing for WSNs is that they can tolerate the dysfunction of a certain number of nodes; e.g., the network formed by nondestroyed nodes should be always connected. The second possible attack for WSNs is that the enemy could distribute a certain number of faked sensor nodes to disturb or even disrupt the communications of legitimate sensors. It is important for a sensor network to design a security mechanism to protect the sensor nodes from malicious attack or to ensure that the sensor network can “tolerate” the malicious attack to some extent. The second challenge for the design of security mechanisms for WSNs is that sensor nodes are always equipped with limited battery and memory. Thus, the traditional public-key–based schemes, such as the Rivest–Shamir–Adleman (RSA) and Diffie–Hellman (D-H) protocols, are not suitable for WSNs. For example, Mica Mote, produced by UC Berkeley, has 128 kb Flash and 4 kb RAM.

Introduction

Multihop structures in wireless networks provide enhanced capacity and fault tolerance. This capacity allows the use of wireless nodes as repeaters, and thus not only enhances the range of communication at low power levels but at the same time short-hop communication causes less spatial interference and allows reuse of the bandwidth available on the frequency channels. The ability for nodes to act as intermediate routers builds into the communication system a natural resilience to node and link failures because alternative paths become available for routing of communications. An important requirement of these networks is that they be self-organizing; i.e., data paths or routes are dynamically restructured with changing topology.

One of the critical issues in the implementation of wireless networks is the design of routing structures and routing protocols. Of considerable importance in this context is the design of distributed efficient algorithms that dynamically update the routing structures. Because the geometric location information regarding the nodes is more readily available, routing algorithms that incorporate this information for effective routing form an increasingly important subject of study.

In this chapter and Chapter 14, we study a number of energy-efficient routing protocols for wireless ad hoc networks. Routing protocols can be categorized as proactive protocols or reactive protocols, depending on when the routing structure is constructed when a routing request is issued from a source node. Routing protocols can also be categorized as flat routing protocols and hierarchical routing protocols.

In this chapter, some simple but also widely accepted models of wireless ad hoc networks are introduced. Notice that WSNs comprise a special subclass of wireless ad hoc networks; thus, when we use the term “wireless ad hoc networks,” we also include WSNs if not specifically clarified. In this chapter, the main focus is on the wireless channel model, the interference model, the energy-consumption model, and the mobility model.

Wireless Channels

The main difference between wireless networks and traditional wired networks is that the wireless devices in a network communicate over wireless channels via wireless transceivers. Thus, to understand wireless ad hoc networks and design efficient protocols and algorithms for wireless networks, we need to understand the characteristics of wireless communications. An important building block of wireless ad hoc network studies is thus the wireless channel model. In the literature, there are a number of wireless channel models proposed and the model presented in this chapter is based on the material contained in Rappaport (1996) and Santi (2005b).

It is widely assumed that a radio channel from a transmitting wireless device u to a receiving wireless device v is established if and only if the received power of the radio signal at node v is above a certain threshold. Let p(u, v) denote the power assigned to node1u to transmit a signal from u to v. We always assume that this power can maintain a reasonably good communication link quality2 from node u to node v.

Power is one of the most critical resources in wireless ad hoc networks when the wireless nodes are powered by batteries only. In this chapter, we study how to assign each wireless node a transmission power (level) such that the resulting communication graph has certain desired properties. Recently, much progress has been made on algorithmic and probabilistic studies of various power-assignment problems. These problems come in many flavors, depending on the power-requirement function and the connectivity constraint, and minimizing the total power consumption by all wireless nodes in a network is NP-hard for most versions. We study some of the best-known approximation algorithms for minimizing the total power consumption in the network and sketch useful heuristics with practical value. Observe that a majority of the power-assignment problems use the same network setting as some problems we studied in other chapters, especially about topology control; some questions are different (although they look similar). For example, in this chapter, we study the power-assignment problem by minimizing the total power while the resulting network is connected. A similar problem is to find a broadcast tree that has the minimum total power consumption. The difference here is that the leaf nodes are not required to transmit for broadcast applications, whereas all nodes are required to transmit for a tree spanning all nodes to result in a connected network.

Introduction

In the next generation of wireless communication systems, there will be a need for the rapid deployment of independent mobile users. Significant examples include establishing survivable, efficient, dynamic communication for emergency/rescue operations, disaster relief efforts, and military networks. Such network scenarios cannot rely on centralized and organized connectivity and can be conceived as applications of mobile ad hoc networks (MANETs). A MANET is an autonomous collection of mobile users that communicate over relatively bandwidth-constrained wireless links. Because the nodes are mobile, the network topology may change rapidly and unpredictably over time. The network is decentralized; all network activity, including discovering the topology and delivering messages, must be executed by the nodes themselves; that is, routing functionality will be incorporated into mobile nodes.

In many commercial and industrial applications, we often need to monitor the environment and collect the information about the environment. In some of these applications, it would be difficult or expensive to monitor using wired sensors. If this is the case, wireless sensor networks in which sensors are connected by wireless networks are preferred. A wireless sensor network (WSN) consists of a number of sensors spread across a geographic area. Each sensor node has wireless communication capability and some level of intelligence for signal-processing and networking of data. A WSN could be deployed in wilderness areas for a sufficiently long time (e.g., years) without the need to recharge or replace the power supplies. Typical applications of WSNs include monitoring, tracking, and controlling.

Introduction

In Chapter 4, we basically studied how to assign time slots to communication links in quasi-static networks (e.g., WMNs and WSNs) such that the scheduled transmissions are interference-free and the scheduling period is minimized (thus maximizing the throughput). We assumed that there is only one spectrum used by all links in the network. In this chapter, we mainly focus on multichannel networks when there are multiple spectrums available for wireless terminals in the network. The wireless devices may have multiple wireless NICs or just a single wireless NIC. Because close by mesh routers compete for certain wireless channels, the capacity of a WMN will be increased tremendously when the single channel is extended to multiradio, multichannel, and multihop. For example, if two nodes vi and vj could communicate with each other by channel f1, and both nodes have at least one more available NIC that could operate on another channel f2, if f2 is also available for both nodes, vi and vj could use both f1 and f2 to communicate simultaneously. When such cases are applied to more wireless nodes, the throughput of the wireless network will be increased tremendously.

On the other hand, with recent fast-growing spectrum-based services and devices, the remaining spectrum available for future wireless services is being exhausted, known as the spectrum-scarcity problem.

Introduction

When designing routing protocols, it is often implicitly assumed that each participant (users or routers) will faithfully follow the prescribed protocols without any deviation–except, perhaps, for a few faulty or malicious ones. For example, in wireless ad hoc networks, it is commonly assumed that each terminal contributes its own resources to forward the data for other terminals to serve the common good and benefits from resources contributed by other terminals to route its packets in return. However, the critical observation that individual users who own these wireless devices are generally selfish, aiming to maximize their own benefit instead of contributing to the system, may severely undermine the expected performances of the wireless networks. The limitations of energy supply, memory, and computing resources of these wireless devices raise concerns about the traditional assumption about terminals' conforming to protocols. Sometimes, wireless devices owned by individual users may prefer not to participate in the routing in order to save its energy and resources. Therefore, if all users are selfish, providing incentives is a natural and common way to encourage contribution and thus maintain the robustness and availability of networking systems. The question turns to how to design the proper incentives.