Growing Proliferation Of Wireless Applications Computer Science Essay

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With the growing proliferation of wireless applications and limited number of channels in the unlicensed bands, the classical networks are suffering from spectrum scarcity problem. It has become a bottleneck to restrict the continuous development of wireless mobile communication and services. However, significant parts of the licensed bands are underutilized. As a result the average spectral utilization is very low over most of the bands. Since spectrum is a natural resource, any wastage in spectrum affects the growth of wireless technologies and increases the demand for opportunistic usage of spectrum.

Besides stating the research motivation, objective, methodology and thesis outline in this chapter, an overview of the different wireless technologies has been presented in section 1.4. In Section 1.5, the principle of current spectrum management based on command and control has been discussed and its limitations have been pointed out.

Research Motivation

Recently wireless networks have been growing very rapidly. Aiming to meet the rapid growth in the wireless technologies and services, several researchers as well as industry have been worked together towards new techniques and standardizations. The most critical consequences during the growth in the wireless networks are related to the usage of electromagnetic radio spectrum which as the most precious natural resource when talk about wireless networks.

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Radio spectrum is a limited resource for wireless communication and services. Within the last few years, the demand for radio spectrum has been amplified noticeably as the new technologies are introduced. One of the common problems faced by the communications world today is the spectrum scarcity issue. With spectrum as a limited source, the scarcity issue can indeed interfere, and reduce the efficiency and the development of the communication community.

Traditionally, radio spectrum allocation is done by regulation agencies such as FCC in USA to assign radio spectrum to licensed users in a static manner. However, they lack adaptability and flexibility. As per the observations of FCC of USA [1], many of the frequency bands in the spectrum are unoccupied most of the times. These potential spectrum holes result in the underutilization of available frequency bands.

The cognitive radio is a key enabling technology to solve the underutilization issue. In 1998, Joseph Mitola III was first proposed that the concept of cognitive radio networks and later presented in an article of Mitola and Gerald [2]. According to their ideas, radio users or wireless links allowed to be empowered with cognitive capacities, and look for available spectrum holes for opportunistic and dynamic transmission. Underutilized spectrum usage could be improved through the proposed mechanism and numerous radio users or wireless links can coexist over the same spectrum. Besides that, it also allows that radio users or wireless links to transmit over spectrum bands in unspecific and unfixed manner.

From the research about the cognitive radio, spectrum mobility is one of the main functionalities in cognitive radio system. In this thesis, spectrum mobility in cognitive radio networks is examined with respect to spectrum handoff. The spectrum handoff is the process of transferring ongoing data transmission from the current channel to another free channel. The spectrum handoff decision plays an importance role in spectrum mobility. With the number of spectrum handoff increases will cause additional latency and power consumption to each cognitive user communication that eventually affects cognitive user performance. Thus, it motivates us to develop a quick and low rate of spectrum handoff scheme in order to improve the spectrum mobility in cognitive radio. This project begins with the analytical study of different schemes that related of spectrum mobility to evaluate the performance and interrelationships between the schemes. After that, an appropriate spectrum mobility scheme will be proposed and its algorithm will be simulated to generate successive results.

Research Objectives

The main objective of this project is to investigate the idea of efficient spectrum mobility in cognitive radio network through the research. As the project developed in a step by step basis, the first objective is therefore to understand different kinds of schemes that related of spectrum mobility. In this objective, it is required to grasp the idea of these schemes. After having the general idea, an efficient spectrum mobility scheme with sufficient protection to licensed users will be proposed.

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The second objective is to realize greener and more energy efficient communications. In this objective, an efficient of energy solution needs to be defined in networks. By optimizing an energy-efficiency based networks not only reduces power consumption, it also helps to cut down the network costs such as processing cost and signaling cost, and thus improves the performance of whole communication network.

The final objective of this project is to develop an algorithm and perform extensive simulations to prove the successful response of the algorithm in different manners. All these manners are defined and will be discussed in the chapter 3. Before performing simulations, it is also required to choose a medium of programming that will be used to prove the responses.

Research Methodology

After the research objectives have been stated, careful and through study in related field were done continuously and accordingly as work progressed.

A brief project timeline, to accomplish the research design where all the methods and parameters used for the cognitive radio and the spectrum mobility to develop the results and research, is as shown in Figure1.1.

The software tool used by this project is MATLAB®. It can exploit powerful programming that allows matrix manipulations, plotting of functions and data, algorithm implementation, scientific and engineering graphics and problems to be solved. MATLAB is widely used in academic and research institutions as well as industrial enterprises.

Figure 1.1: Flow of Project Development

Overview of Wireless Communications System

Wireless communications technology has become a key element in modern society. Nowadays, total number of users subscribing to the cellular wireless services has exceeded the number of users who subscribing to the wired telephone services. Apart from that, cordless phones, wireless local area networks, and satellites are being used widely for voice and data-oriented communications applications and entertainment services.

In 1895, Guglielmo Marconi demonstrated the feasibility of wireless communications by using electromagnetic waves. In 1906, the first radio broadcast was done by Reginald Fessenden to transmit voice and music over the air. In 1907, the commercial trans-Atlantic wireless transmission was launched. In 1946, the first interconnection of mobile users to public switched telephone network (PSTN) was introduced. In 1981, the first analog cellular system, Nordic Mobile Telephone System (NMT) was introduced in Europe. In 1983, first cellular wireless technology, Advanced Mobile Phone System (AMPS) was deployed in US in 900 MHz band and can supports about 666 duplex channels. Finally, there has been significant research and development in the wireless communications technology during these last two decades [3].

Radio Frequency Bands

Wireless communications systems are built on the transmission of electromagnetic waves which corresponds to the radio waves within frequencies range about 3 Hz to 300 GHz. These radio waves are transmitted and received through antennas which transform the radio waves from electrical energy to electromagnetic energy and vice versa. Table 1.1 shows the frequency of radio waves are divided into different groups.

Different parts of frequencies of the radio waves are used for different radio transmission technologies and applications. For example, 535 kHz- 1605 kHz in MF is used for AM radio transmission, 54 MHz- 88 MHz, 174 MHz- 216 MHz in VHF and 470 MHz- 806 MHz in UHF are used for TV signal transmission, and 88 MHz- 108 MHz in VHF is used for FM radio broadcast. Low frequency radio waves are suitable for long range communications and high frequency radio waves are more suitable for short range but high speed wireless communications.

Table 1.1: Radio Frequency Bands [3]

Frequency

Wavelength

Designation

Abbreviation

3 Hz- 30 Hz

104 km- 105 km

Extremely low frequency

ELF

30 Hz- 300 Hz

103 km- 104 km

Super low frequency

SLF

300 Hz- 3000 Hz

100 km- 103 km

Ultra low frequency

ULF

3 kHz- 30 kHz

10 km- 100 km

Very low frequency

VLF

30 kHz- 300 kHz

1 km- 10 km

Low frequency

LF

300 kHz- 3000 kHz

100 m- 1 km

Medium frequency

MF

3 MHz- 30 MHz

10 m- 100 m

High frequency

HF

30 MHz- 300 MHz

1 m- 10 m

Very high frequency

VHF

300 MHz- 3000 MHz

10 cm- 1 m

Ultra high frequency

UHF

3 GHz- 30 GHz

1 cm- 10 cm

Super high frequency

SHF

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30 GHz- 300 GHz

1 mm- 1 cm

Extremely high frequency

EHF

Wireless Communications Technologies

The various wireless communications systems available today differ in terms of transmission power, data rate of transmission, geographical coverage and mobility support for users. Current wireless communications technologies can be classified by the corresponding transmission range or coverage area as shown in Figure 1.2.

High-power wide area systems (or cellular systems), which support mobile users roaming over a wide geographic area;

Low-power local area systems, for example Bluetooth, IEEE 802.15.4-based ZigBee, cordless telephone system, which are implemented with relatively simpler technology;

Low-speed wide area systems, which are designed for mobile data services with relatively low data rates, for example paging systems;

High-speed local area systems, which are designed for high speed and local communications, for example WiFi.

Figure 1.2: Different Wireless Technologies [3]

The first and second categories are voice-oriented systems while the remaining are data-oriented systems. Although different types of wireless system have different transmission power, data rate, coverage and mobility requirements, the challenges include radio resource allocation/management and medium access control, rate control, handoff and mobility management, quality of services (QoS) provisioning, and security [3] and design and implementation of these systems.

NeXt Generation (xG) Heterogeneous Wireless Network and Cognitive Radio

The future generation wireless networks will have the following attributes:

With high transmission rate: New wireless applications and services, for example video and file transfer are require higher data rate in order to reduce their transmission time and thus support a number of users. Many advanced techniques in the physical layer have been developed to increase the data rate without having increase spectrum bandwidth and transmission power requirement.

With Cross layer design: In order to reduce the overhead in the protocol stack, the cross layer design concept was proposed to create a link among different protocols in different layers. The wireless system can be optimized throughout the protocol stack by cross layer design. Therefore, the overall system performance in terms of data rate, error and radio resource utilization is improved.

With QoS support: Various types of traffic, for example voice, video and data, will be supported by the xG wireless system. Service differentiation and QoS support are required to prioritize different types of traffic according to the performance requirement. Radio resource management framework has to be designed to efficiently access the available spectrum.

With Integration of different wireless access technologies [3]: xG wireless network will use the IP technology to merge different wireless access technologies into a converged wireless system. In the converged network, multi-interface mobile units will become common. With multiple radio interfaces, a mobile should be able to connect to different wireless networks through always changing the access technologies. For example, a mobile can connect to a Wireless Local Area Network (WLAN) through the IEEE 802.11-based radio interface. However, when the mobile starts to move out of range of the WLAN, it can connect to a cellular network or a Worldwide Interoperability for Microwave Access (WiMAX) network to resume the communication session. The heterogeneous wireless access network provides two major advantages: it can enhances the data transmission rate since multiple data streams can be transmitted concurrently and it enables seamless mobility through providing wireless connectivity anytime and anywhere. However, many different issues arise from this heterogeneous wireless access environment. It includes network selection, QoS support, bandwidth allocation, admission control, vertical handoff and routing. When multiple wireless networks are available, the mobile unit must choose a set of suitable networks to connect in order to maximize its utility. Besides that, admission control and mobility management are required to ensure QoS and seamless connectivity.

With software defined radio (SDR) and cognitive radio: Frequency spectrum in wireless network is the limited radio resource and its efficient usage is the key point in xG wireless communications systems. With the traditional approach of allocating frequency spectrum to wireless transceivers, it has been observed that some frequency bands are heavily used in some portion, while others are lightly utilized elsewhere. Spectrum opportunities are thus generated, which can be exploited by intelligent and adaptive cognitive wireless transceivers implemented through SDR. The wireless transceiver can change its transmission parameters such as transmission power and operating frequency band with SDR. The dynamic spectrum access (DSA) techniques is the key for implementing cognitive radio that need to be developed for different wireless systems with different capabilities and different operating environments. The adaptability of wireless transmission in cognitive radio can be achieved by employing intelligent algorithms to observe, learn, optimize and make decisions. Designing DSA methods for cognitive radio requires knowledge from multiple scientific and engineering disciplines that include traditional wireless communications and networking, optimization and game theory, machine learning and economics, to achieve the desired design objectives.

With integration of cognitive radio concepts: Cognitive radio and DSA techniques can be integrated into traditional wireless communications systems to achieve better flexibility of radio resource usage so that system performance can be improved.

Background of Spectrum Management

Nowadays, one of the vast challenges faced by wireless industry is to come out methods for low cost and efficient spectrum utilization. Interference can occur when radio waves are transmitted simultaneously from multiple sources in the same frequency. Therefore, spectrum management is required to control the transmission of radio waves to avoid interference among wireless users. Many technologies today have come together to achieve the spectrum efficiency. This chapter gives the reader the background context of the current spectrum management system and the motivation towards DSA.

Current Spectrum Management Techniques

Spectrum Management consists of providing a flexible and responsive approach to meet the need of spectrum users, making adequate prerequisite of spectrum for public and community services, maximizing the overall public benefit derived from use of the spectrum by ensuring its efficient allocation. A number of standards bodies work on standards for frequency allocation, including:

European Conference of Postal and Telecommunications Administrations (CEPT)

International Special Committee on Radio Interference (CISPR)

European Telecommunications Standards Institute (ETSI)

International Telecommunication Union (ITU)

The radio spectrum is organized by allocations and assignments. Allocation determines the type of use and respective transmission parameters. It is specified by the individual nations. Assignments are individual licenses within an allocation. There are still a lot of ways to determine the assignments as shown in Figure 1.3. However, three basic types of assignment are only employed which is command and control, auctions and protocols and etiquette.

Figure 1.3: Spectrum Access Regimes [3]

Command and control: Command and control assignments are provided by the regulatory agency by reviewing specific licensing applications and choosing the prospective licensee by criteria specific to the national goals [4].

Auctions: High demand sections of the radio spectrum may sometimes be allocated through auctions.

Protocols and etiquettes: Unlicensed devices and amateur licensees do not have specific frequency assignments. The allocation enables these devices to operate within a band, and the selection of a particular frequency is accomplished through protocols and etiquettes. Protocols are explicit interactions for spectrum access. Etiquettes are rules that are followed without explicit interaction between devices.

Static Spectrum Allocation

The static spectrum allocation can be defined as a static chunk of spectrum is allocated to the user statically through the spectrum regulatory bodies. These kinds of spectrum allocations are fixed, long-term and changes are made under the strict guidance of the regulatory bodies, for example FCC. Figure 1.4 shows the static spectrum allocation techniques.

Figure 1.4: Static Spectrum Allocation

Figure 1.5 shows the static allocation of frequency in the range of 3- 6 GHz by the FCC. Different type of color indicates different type of service allocated to the frequency band in the entire nation. Nowadays, almost all the spectrum has been allocated and there is no vacant spectrum for new users.

Figure 1.5: FCC Frequency Allocation from 3- 6 GHz

Traditional spectrum management techniques, as defined by the FCC, are based on the command and control model. In this model, radio bands are licensed to the authorized users by the government. The common method for allocation is referred to as spectrum auction. In spectrum auction, government opens a radio frequency band for bidding and could specify which type of wireless technology/ application for this particular radio frequency band. Any user/company interested in using this radio band will submit the bid. Government determines the winning user/company, which is basically the user/company offering the highest bid. The licensed user is authorized to use the radio frequency band under certain rules and regulations that specified by the government. The duration of the license issued to the authorized user is also determined by the government.

The benefit of command and control based spectrum management framework is it can guarantee the radio spectrum will be exclusively licensed to an authorized user who wins the radio frequency bidding and can use the spectrum without any interference. However, command and control model cause the spectrum usage inefficiency, as shown in the report from the Spectrum Policy Task Force (SPTF) of the FCC in 2002 [3]. The spectrum management inefficiency arises due the fact that an authorized user may not fully utilize the spectrum at all times in all locations. Besides that, regulatory requirements put limitations on the wireless technology that can use the licensed spectrum and this may prevent an authorized user from changing their wireless transmission techniques and services according to market demand.

Although most of the spectrum is managed under this command and control scheme, but there are some spectrum bands that are still reserved for industrial, scientific and medical purposes, referred to collectively as the industrial, scientific and medical (ISM ) radio band. This ISM band can also be used for data communication. Since there is no control on this ISM band, the data communication could be interfered by any ISM equipment.

Demand for Advanced Spectrum Management Technique

The demands for the wireless services are exponentially increasing. Not only the number of users at the world booming, but also more bandwidth is required for new services such as video telephony, wireless Internet, TV on demand and wireless gaming. Finding a way to adapt all these requirements is the main challenging issue in wireless networking.

Recent measurement by FCC shows that 70% of the allocated spectrum in USA is not utilized. Besides that, time scale of the spectrum occupancy varies from milliseconds to hours [4]. As some licensed frequency bands lie underutilized, even if transmission of unlicensed users do not interfere at all with the assigned services, the demand of broadband wireless services increased has made some part of the radio spectrum that allocated to mobile communications to be a scarce resource.

Thus, there was a request to FCC to change the spectrum management policy to make it more flexible in order to deal with spectrum scarcity problem. The recommendations to change the spectrum management policy are as follow [5]:

improve flexibility of spectrum usage,

take all dimensions and related issues of spectrum usage into the policy, and

support and encourage efficient use of the spectrum.

One of approach pursued in regulations is to license the spectrum to a licensee or PU; while the band also may be used by other users, for example SUs, under the condition that they are not allowed to cause any harmful interference to PU. Another approach under discussion is to have an entirely unlicensed spectrum, which has to be shared with equal priority with many users.

The objectives for these recommendations were to improve both the technical and economic efficiency of spectrum management. For the technical perspective, spectrum management needs to ensure the lowest interference and the highest utilization of the radio frequency band. While the economic aspects of spectrum management is relate to revenue and satisfaction of the spectrum licensee, which is adjusted by offering prices to the wireless service users to achieve the highest revenue and also by providing QoS to the users.

Different spectrum management models have been introduced in literature for different radio bands and wireless applications [3]. Spectrum management models have improved the flexibility of spectrum usage and also built up new opportunities for different wireless technologies to utilize the radio spectrum more efficiently. The wireless transceivers also need to be more intelligent to access the radio spectrum when exploited these opportunities.

Dynamic Spectrum Allocation

The current interest to regulators in field of cognitive radios is to provide new methods and mechanisms for spectrum access and utilization under consideration by international regulatory agencies. In DSA, frequency is shared from a spectrum pool, defined in the licensed band and is divided into a number of segments, by providers depending on demand from the SUs. Unlicensed or Secondary users (SUs) look for the spectrum band that is not occupied by the licensed or primary user (PU). SUs also need to sense the spectrum to determine the presence or absence of a primary signal and look for other white spaces in the frequency band after every certain period, which is called sensing period. If there are some free spaces, SUs are allowed to use that temporarily until the PU becomes active and vacant that band immediately to avoid interference.

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