1. INTRODUCTIONS OF SDRSoftware-defined radio is a radio communication system where components that have been typically implemented in hardware (i.e mixers, filters, amplifiers, modulators, demodulators, detectors etc.) are instead implemented by means of software on a personal computer or embedded system. While the concept of SDR is not new, the rapidly evolving capabilities of digital electronics render practical many processes which used to be only theoretically possible. Traditional hardware radios are implemented with Analog hardware and solid poly-Si elements. In SDR, The traditional hardware are replaced by software modules such as SDR was proposed by Josef Mitola in the beginning of 1990. Unlike adopt applications specific integrated circuit (ASIC) to implement radio elements. In the past, the technologies such as Field Programmable Gate Array (FPGA).Digital Signal Processor (DSP) and General Purpose Processor (GPP) are used to build the software defined radio element. These Components have reconfigurable capability which making these Components tend to Generalization In order to implement a variety of different radio-applications.

Figur.1 Basic SDR architecture [4]In the same way that automotive engines have rested for more than 100 years on the same principle and mechanical parts, radio has been resting on the same architecture and electronic parts. Some technological evolutions, such as the transistor, have of course enabled miniaturization of the systems and increasing their performance, but the same basis of discreet electronic components has been kept. Software radio is the most recent major

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technological change in the field. Indeed, the amazing evolution of digital technologies during the 1980s enabled this well established paradigm to be challenged, and since the beginning of the 1990s,2 certain baseband processing techniques started to be performed and gathered within digital integrated circuits. This development led to software radio, the main ideas of which are that circuit processing is a general-purpose processor, and that some of the processing that was previously performed analogically by means of several discreet components can now be performed by a sole processor. First of all, it is interesting to put software radio in its historical context in order to fully understand the interests that led to its advent, at both the design and utilization phases of equipment. Software radio is a convergence of different technological fields. Hence, each concerned scientific community has appropriated the concept and uses this naming to illustrate its work. This fact entails as many standpoints as there are concerned communities: this is dealt with in the third section. The objective reality of software radio, due to the technological developments it has generated, are highlighted after that. The software radio vs. velcro approach is discussed in the final section, in which we also present our vision for the future of software radio.

Figur 1.1. Evolution of software-radio-related articles pub- lished since[3]

1.1 Cognitive radio:

 It is a form of wireless communication in which a transceiver can intelligently detect which communication channels are in use and which are not, and instantly move into vacant channels while avoiding occupied ones. In response to the operator's commands, the cognitive engine is capable of configuring radio-system parameters. These parameters include "waveform, protocol, operating frequency, and networking". This functions as an autonomous unit in the communications environment, exchanging information about the environment with the networks it accesses and other cognitive radios (CRs). A CR "monitors

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its own performance continuously", in addition to "reading the radio's outputs"; it then uses this information to "determine the RF environment, channel conditions, link performance, etc.", and adjusts the "radio's settings to deliver the required quality of service subject to an appropriate combination of user requirements, operational limitations, and regulatory constraints".

Some "smart radio" proposals combine wireless mesh network dynamically changing the path messages take between two given nodes using cooperative diversity; cognitive radio dynamically changing the frequency band used by messages between two consecutive nodes on the path; and software-defined radio dynamically changing the protocol used by message between two consecutive nodes.

1.2 Software-defined networking (SDN):

It is an approach to computer networking that allows network administrators to manage network services through abstraction of higher-level functionality. Software-defined networking (SDN) is an architecture purporting to be dynamic, manageable, cost-effective, and adaptable, seeking to be suitable for the high-bandwidth, dynamic nature of today's applications. SDN architectures decouple network control and forwarding functions, enabling network control to become directly programmable and the underlying infrastructure to be abstracted from applications and network services. The Open Flow protocol is a foundational element for building SDN solutions. The SDN architecture is:

Directly programmable: Network control is directly programmable because it is decoupled from forwarding functions.

Agile: Abstracting control from forwarding lets administrators dynamically adjust network-wide traffic flow to meet changing needs.

Centrally managed: Network intelligence is centralized in software-based SDN controllers that maintain a global view of the network, which appears to applications and policy engines as a single, logical switch.

Programmatically configured: SDN lets network managers configure, manage, secure, and optimize network resources very quickly via dynamic, automated SDN programs, which they can write themselves because the programs do not depend on proprietary software.

1.3 Software-defined radio (SDR):

It is a radio communication system where components that have been typically implemented in hardware (e.g. mixers, filters, amplifiers, modulators/demodulators, detectors, etc.) are instead implemented by means of software on a personal computer or embedded system. The ideal receiver scheme would be to attach an analog-to-digital converter to an antenna. A digital signal processor would read the converter, and then its software would transform the stream of data from the converter to any other form the application requires. An

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ideal transmitter would be similar. A digital signal processor would generate a stream of numbers. These would be sent to a digital-to-analog converter connected to a radio antenna.

The ideal scheme is not completely realizable due to the actual limits of the technology. The main problem in both directions is the difficulty of conversion between the digital and the analog domains at a high enough rate and a high enough accuracy at the same time, and without relying upon physical processes like interference and electromagnetic resonance for assistance.

Most receivers use a variable-frequency oscillator, mixer, and filter to tune the desired signal to a common intermediate frequency or baseband, where it is then sampled by the analog-to-digital converter. However, in some applications it is not necessary to tune the signal to an intermediate frequency and the radio frequency signal is directly sampled by the analog-to-digital converter (after amplification).

Real analog-to-digital converters lack the dynamic range to pick up sub-microvolt, nanowatt-power radio signals. Therefore, a low-noise amplifier must precede the conversion step and this device introduces its own problems. For example, if spurious signals are present (which is typical), these compete with the desired signals within the amplifier's dynamic range. They may introduce distortion in the desired signals, or may block them completely. The standard solution is to put band-pass filters between the antenna and the amplifier, but these reduce the radio's flexibility. Real software radios often have two or three analog channel filters with different bandwidths that are switched in and out.

2.THE FUNDAMENTAL ARCHITECTURE OF SDR

Figur 2 Fundamental architecture of SDR[4]

The fundamental architecture of SDR is shown in figure above. It include front end, processing engine and application, the radio frequency front-end module digitizes the radio frequency data from antenna after the baseband is digitized by front-end. The processing engine converts baseband data and data frames. The applications side receives data frames at last. Implementation of the ideal software-defined radio would require either the digitization

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at the antenna, allowing complete flexibility in the digital domain, or the design of a completely flexible radio frequency (RF) front-end for handling a wide range of frequencies and modulation. The receiver begins with a smart antenna that provides a gain versus direction characteristic to minimize interference, multipath, and noise. The smart antenna provides similar benefits for the transmitter. Most practical software-defined radios digitize the signal as early as possible in the receiver chain while keeping the signal in the digital domain and converting to the analog domain as late as possible for the transmitter using a digital to analog converter (DAC). Often the received signal is digitized in the intermediate frequency (IF) band. Conventional radio architectures employ a super heterodyne receiver, in which the RF signal is picked up by the antenna along with other spurious/unwanted signals, filtered, amplified with a low noise amplifier (LNA), and mixed with a local oscillator (LO) to an IF. Depending on the application, the number of stages of this operation may vary. Finally, the IF is then mixed exactly to baseband.

Figur.3 Hardware architecture of SDR[5]

Implementation of the ideal software-defined radio would require either the digitization at the antenna, allowing complete flexibility in the digital domain, or the design of a completely flexible radio frequency (RF) front-end for handling a wide range of frequencies and

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modulation. A model of a practical software-defined radio is shown in Figure 1. The receiver begins with a smart antenna that provides a gain versus direction characteristic to minimize interference, multipath, and noise. The smart antenna provides similar benefits for the transmitter. Most practical software-defined radios digitize the signal as early as possible in the receiver chain while keeping the signal in the digital domain and converting to the analog domain as late as possible for the transmitter using a digital to analog converter (DAC). Often the received signal is digitized in the intermediate frequency (IF) band. Conventional radio architectures employ a super heterodyne receiver, in which the RF signal is picked up by the antenna along with other spurious/unwanted signals, filtered, amplified with a low noise amplifier (LNA), and mixed with a local oscillator (LO) to an IF. Depending on the application, the number of stages of this operation may vary. Finally, the IF is then mixed exactly to baseband. Digitizing the signal with an analog to digital converter (ADC) in the IF range eliminates the last stage in the conventional model in which problems like carrier offset and imaging are encountered. When sampled, digital IF signals give spectral replicas that can be placed accurately near the baseband frequency, allowing frequency translation and digitization to be carried out simultaneously. Digital filtering (channelization) and sample rate conversion are often needed to interface the output of the ADC to the processing hardware to implement the receiver. Likewise, digital filtering and sample rate conversion are often necessary to interface the digital hardware that creates the modulated waveforms to the digital to analog converter. Processing is performed in software using DSPs, field programmable gate arrays (FPGAs), or application specific integrated circuits (ASICs). The algorithm used to modulate and demodulate the signal may use software methodologies, such as middleware, e.g., common object request broker architecture (CORBA) or virtual radio machines, which are similar in function to JAVA virtual machines.

3.SCA ARCHITECTURE Common SCA Perceptions The previous section provided a brief description of the SCA. It is a truism that any technology is often received and perceived differently by each individual: Some of the perceptions are based in fact and some are based on an incomplete understanding of the technology. The following paragraphs discuss some of the commonly cited misconceptions about the SCA.

There is nothing in the SCA specification that provides technical data or guidance on the design and implementation of a software radio. The SCA, based on the CORBA Components Model, defines an architecture for the deployment of applications. In the case of a software radio, those applications tend to be waveforms. The SCA enhances reusability from two perspectives. First, the SCA specification defines a common set of interfaces for basic deployment configuration, and control of applications. So, from the perspective of user interfaces and external control of the system, the same interface calls that are used to load, start, and stop a SINCGARS waveform are identical to the FM3TR waveform. Second, the Application Programmer Interface (API) appendix to the specification is intended to promote

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reusability of waveform software components through common waveform interfaces. This continues to be an area of on-going discussion because all radio system developers have different perspectives as to what the interfaces should be for a specific waveform. A waveform can be moved from one SCA platform to another without modification many individuals have interpreted the portability objective of the SCA as reusability without modification. The SCA specification defines common, high-level interfaces for deploying, configuring, controlling, and monitoring the hardware and software applications within an SCA-based radio system. This simplifies the effort required to port applications because the interfaces do not change. However, deploying waveforms across multiple radio systems without modification was never a stated requirement. The SCA results in a waveform performance impact on my system The simple fact is that, once the SCA deploys the waveform on the radio system, the SCA Core Framework goes into a quiescent state and does not utilize significant processor cycles. Also, for waveforms implemented largely in FPGA or DSP processors, there is typically no impact due to the SCA on functioning waveforms in those processors. There are some impacts in terms of the memory footprint required to support an SCA framework. However, the SDR Forum, NASA, and other groups are looking into reduced footprint architectures. Where the framework is running on the same GPP being used for waveform processing, some performance impact may be encountered. In this case, standard systems analysis to evaluate the load margins is necessary.

Figur.4 Functional architecture of SDR[3]

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CORBA should be the starting point but is not mandatory if performance reasons prohibit it. Also, individuals often confuse the latency impacts of the underlying transport mechanism, which typically defaults to TCP/IP, as being synonymous with CORBA. In reality, CORBA is a protocol layer, much like Hypertext Transfer Protocol (HTTP), that rides on top of the data transport mechanism. Most modern ORBs support plugable transports allowing customization and optimization of the actual data transport. The SCA is only applicable for small radios The SCA is not specifically targeted for any one type or class of radio system. Small form- factor, resource-limited radio systems have a more significant set of issues to overcome when building an SCA-compliant handheld or manpack radio, due to their Size Weight, and Power (SWaP) constraints. This is usually due to the fact that the GPP on the small radio is already used extensively for waveform code, and processing impacts due to adding the framework can be significant.Electronic design automation (EDA) tools that have tremendously progressed in number and quality for the digital domain these last 20 years and Digital compensation of analog defects (dirty RF) and Cheaper digital solutions than analog

The SCA and/or CORBA is not suitable for large, complex systems The origins of the SCA are based on the JTRS program which focused on tactical radio systems. These systems ranged from small handhelds to rack-mount systems in vehicles, ships, and aircraft. Although these systems do not have the complexity of large terminal systems, it is possible to apply the SCA to larger systems. More thought must go into the architecture of the system, however. It may be the case that the SCA manages the core set of radio equipment and waveform deployment under the direction of a higher-level system or network management operation. The key aspect is that the SCA is targeted towards the management of the hardware and software that implement and support the end-to-end waveform application. As for the applicability of CORBA to large scale systems, it can be said that it is in wide use throughout industry. Large, distributed Java-based applications are, in fact, using CORBA and Java remote procedure calls are using the CORBA protocol. Also, the Iridium satellite Command and Control segment integrated a COTS-based system, OS/COMET, within a comprehensive CORBA framework. The resultant system ran on over 50 computers and was comprised of several hundred processes.

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4.FEATURE OF SOFTWARE DEFINED RADIO

i. Reprogrammability or reconfigurabilityii. Require adequate hardware at runtime

iii. Need adequate software deployment iv. Digital way that opens a new era merging IT and telecommunations:v. Convergence of radio and computer science

vi. At both the radio equipment and network levels (SDN)vii. Earlier design of the hardware platform in the development cycle.

viii. Delay resulting from needed hardware adjustments is not so painfulix. New versions can be made within the specified time limitx. Reuse of pre-existing hardware components:

xi. Processing units instead of dedicated hardware componentsxii. New components instability is avoided

xiii. Standard instead of tailor madexiv. Software (application) can be improved until the very last minute before its

delivery:xv. Last moment errors can be fixed at reduced cost

xvi. Application changes do not entail any hardware ad5.NEW SERVICES

Adapt all processing thanks to a simple change of software. Offer an ubiquitous connection, that is, which is able to demodulate at reception. More comfort and better robustness is obtained. Reutilization of the same platform for different products is achieved. Several radio applications in a unique multi-standard product (unlike a velcro design, which comprises as many circuits as there are radio applications). Several products whose operations are specific to different software versions Radio application waveforms. Radio design environments and software facilities.Benefits of software radio In terms of functionality This is the main and true novelty of software radio, due to the possibility it offers to benefit from added flexibility during the lifetime of the product, that is, once it has been manufactured and is on the market. In that respect, software radio still remains a driver of wireless innovation since this capacity is far from being fully used in most radio systems. For mobile phone providers, wireless operators and users and respectively to modulate at transmission all communication standards with the same equipment.Minimize the impact on clients of maintenance operation thanks to OTAR Extend product life duration thanks to software update can concern an improvement ofthe radio equipment, or even the download of a new standard taht did not exist when the product was sold, such as for satellite industry and remote radio access point for operations and maintenance

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6. DISADVANAGES

6.1 COST AND POWER

The most common argument against SDR is cost. The argument is particularly important for high-volume, low-margin consumer products. Consider a garage or car door remote opener key fob. This extremely simple device has one and only function. The mechanical design a single button precludes the addition of new functionality in the future. Millions of essentially identical devices are sold every year, amortizing the development cost of an ASIC. The cost of the ASIC is then proportional to the size of the chip, which is in turn a function of the chip com- plexity. An SDR chip for garage door openers could be used in many other devices as well, but the increased market volume would not drive the cost of the chip down. In fact, since an SDR is necessarily more complex than a single-function radio, the SDR chip cost would be higher. The same cost argument has been made for AM and FM radio receivers. These products are also high-volume and potentially very low cost

6.2 COMPLEXITY

One generic argument against SDR is the additional complexity it requires. The complexity argument has at least three components. Increased time and cost to implement the radio. It takes more engineering effort to develop software and firmware to support multiple waveforms than to support just one. Some argue that the increase in complexity is super linear (i.e., it takes more than twice as long to implement a radio that supports two waveforms than to implement two radios that each support one waveform). This claim is not unreasonable if the radio has to conform to a complex standard such as JTRS. Specialized expertise required to develop on a particular SDR platform may disappear soon after the radio is delivered to the customers. Developing new waveforms for that platform in the future can easily be more expensive than starting from scratch. Longer and more costly specifications and requirements definition. An SDR design has to support a set of baseline waveforms but also anticipate additional waveforms. Some DSP resource margin must be provided to support future waveforms. Risk is Increased. At least two sources of risk must be considered: – Inability to complete the design on-time and on-budget due to the concerns presented above. Since SDR is still a relatively new technology, it is more difficult to anticipate schedule problems. – Inability to thoroughly test the radio in all of the supported and anticipated modes. Testing SDR is a very active area of research. In the author’s opinion, it is the single strongest argument against SDR. How does one test a radio that supports a huge number of waveforms? It is clearly not possible to test every combination of supported parameters (modulations, codes, data rates, etc.). Defining ‘corner’ cases is nontrivial since interaction between components is not obvious (e.g. the performance of a tracking loop stressed at low rates or high rates). Combinations of FEC block lengths and time constants of adaptive loops introduce a new level of complexity. Errors in SDR design can affect not only the faulty radio, but also the entire network. In fact, a wideband SDR could conceivably transmit a signal in an unauthorized band, thereby jamming other life-critical signals. Testing

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an SDR in steady-state (i.e., once a waveform has been selected) is not sufficient. Problems may be observed only when switching from one specific waveform to another. Concerns with security and information assurance problems in an SDR are related to the complexity argument. Most modern wireless standards include some form of encryption and authentication. We expect our phone conversations to be relatively immune from interception. The ability to change many aspects of a waveform also implies that the security-related aspects could be changed.

The most common argument against SDR is cost. The argument is particularly important for high-volume, low-margin consumer products. Consider a garage or car door remote opener key fob. This extremely simple device has one and only function. The mechanical design—a single button—precludes the addition of new functionality in the future. Millions of essentially identical devices are sold every year, amortizing the development cost of an ASIC. The cost of the ASIC is then proportional to the size of the chip, which is in turn a function of the chip com- plexity. An SDR chip for garage door openers could be used in many other devices as well, but the increased market volume would not drive the cost of the chip down. In fact, since an SDR is necessarily more complex than a single-function radio, the SDR chip cost would be higher. The same cost argument has been made for AM and FM radio receivers. These products are also high-volume and potentially very low costThe second most common argument against SDR is increased power consumption. Two sources contribute to higher power consumption in an SDR: increased DSP complexity and higher mixed-signal/RF bandwidth. Power con- sumption in an FPGA or GPP used to implement flexible signal processing is easily 10 times higher than in an equivalent ASIC.2 Wideband ADCs, DACs, and RF front ends required for SDR consume more power than their narrowband equivalents. The difference is especially dramatic for wideband power amplifiers, which account for at least 70 % of the total power in a radio. A wideband amplifier is often half as efficient as a narrowband one.3 Power consumption in the ADCs varies approximately linearly with bandwidth, but is less than linear for DACs. A wideband ADC often also requires higher dynamic range (more bits) to tolerate in-band interferers. Increasing ADC dynamic range significantly increases the power consumption . However, waveform adaptation enabled by SDR can reduce the required transmit power; thereby saving power (see Sect. 3.5). Cost and power consumption arguments are combined when considering the amount of signal processing margin to be included in an SDR. The margin is defined as the ratio of the DSP horsepower (e.g. measured in FLOPS) provided by an SDR relative to that required for the baseline set of waveforms. For example, an SDR is initially developed to support two waveforms, with the more complex one requiring 1 GFLOPs. A 100 % margin requires the SDR to provide 2 GFLOPs. It is difficult to predict what waveforms a user may wish to host on an SDR and even a small underestimate of the margin can preclude the ‘must have’ future waveform. Consider some of the early deep space missions that relied on simple and computationally non-demanding FEC codecs. Thirty years ago the designers could not imagine the enormous computational requirements of modern iterative codecs. It would have been (then) unreasonable to include enough DSP margin to

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enable an upgrade to the powerful codecs of today. Lack of sufficient DSP margin is a very strong argument against the ‘future-proof’ promise offered by SDR. Finally, it is important to keep in mind that SDR only addresses the physical layer. The user cannot take advantage of link throughput improvements made possible by SDR without cooperation from upper layers. One example demonstrating the need for cross-layer adaptation is described in Another example is described below. The ubiquitous network protocol, TCP/IP, was developed for fixed-rate chan- nels. A TCP transmitter sends data packets at the highest possible rate. The receiver responds with an acknowledgment packet (ACK) as it receives the data. If the transmitter does not get an acknowledgement, the protocol determines that the link is congested and quickly decreases the data rate. If more acknowledgement packets are not received, transmitter rate falls even further. The rate increases slowly once the ACK packets are received once again. Performance of TCP in the context of time-varying throughput caused by SDR adaptation to the environment has been extensively studied. Results show that end-to-end throughput is much lower than the physical layer throughput. Moreover, some combinations of channel fade rate and TCP settings lead to instability and throughput drops dra- matically. Achieving the average throughput made possible by ACM may also require large buffers at the network routers or in the SDR. Consider a fixed-rate data source9 with the rate equal to the average physical layer throughput, Ravg. The SDR supports two waveforms for good and bad channel conditions with rates Rhigh and Rlow. When the instantaneous throughput drops to Rlow due to a fade, data will start getting backed up. The buffer must be large enough to hold (Ravg - Rlow) for the duration of the fade, as shown in Fig. 6.2

Figur 6.2 Queue level versus time[7]

Since the fading channel is random, fade duration is theoretically unlimited. The buffer must be sized such that data is not lost more than some specified percentage of the time (e.g., no

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more than 0.01 %). The average throughput and buffer size can be derived analytically by assuming a Markov model for transitions between different ACM waveforms . Transition probabilities are derived by analyzing long-term channel statistics.

7.SOFTWARE-DEFINED RADIO EMERGING CONCEPTSThe emerging concepts of software-defined radios are in the field of smart antennas, networking, digital preprocessing, and software. Smart antennas digitally combine antenna channels to adaptively form beams and point nulls and equalize the received signal . Space Time Coding and Multiple Input Multiple Output (MIMO) Antenna System are the techniques used in SDR among many techniques to improve the performance in hostile wireless environment. Software radio architectures, originally developed for military applications, are now becoming economically viable in commercial products because of therapid advance of DSP technology. Razavilar extends to algorithms and traffic engineering aspects. This paper considers a wireless network with beam forming capabilities at the receiver which allows two or more transmitters to share the same channel to communicate with the base station. The concrete computational complexity and algorithm structure of a base station are considered in terms of a software radio system model, initially with an omnidirectional antenna. Hatchel and Fetweiss address the critical question of providing clock references for multiple air interfaces needed for multiple SDR softwarepersonalities. Given the accuracy requirements for diverse air interfaces, the authors show that deriving multiple clocks from a single master clock has more to do with antialiasing and preserving frequency domain properties than with time domain interpolation. Papers by Munro and Shepherd address emerging aspects of software. Shepherd sets the software issues in a deployment context. The paper proposes a consistent software architectural framework for the dynamic implementation of these different protocols within an embedded environment. Munro critically examines the emerging needs for middleware thatinsulates radio applications from the rapidly evolving radio hardware platforms. The paper explores the issues of integration, the components of mobile middleware, and likely demands placed on such systems when mobile access comes to dominate personal communications. The Cognitive Radio [18] extends the SDR by enhancing the flexibilities of personal servicesthrough a Radio Knowledge Representation Language. The cognitive radio empowers SDRs to conduct expressive negotiations among peers about the use of radio spectrum across fluents of space, time and user context.

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8.TECHNILOGICAL SOLUTIONS AND CHALLENGESAn effective solution to implement SDR consists in the combination of programmable digital baseband engines and reconfigurable analog front-end circuits. For the programmable digital baseband engine, one has to carefully trade off flexibility and energy efficiency. Flexibility should only be introduced where its impact on the total average power is sufficiently low orwhere it offers a broad range of control options that can be exploited effectively later in the control step. For the reconfigurable analog front end, architectures and circuits should be designed for a broad range of requirements in carrier frequency, channel bandwidth and noise performance with minimal penalty in power consumption, while also offering energy scalability. A major challenge is to enable low energy reconfigurable radio implementations, suited for handheld multimedia terminals and competitive with fixed hardware implementations. To make such terminals a reality; firstly effective energy scalability isenabled in the design of the radio baseband and front end. And secondly, the scalability is exploited to achieve low power operation by across layer controller that follows at run time the dynamics in the application requirements and propagation conditions. Future communication systems will have to seamlessly and opportunistically integrate multiple radio technologies and heterogeneous wireless access networks to offer context dependent ubiquitous connectivity and content access. The growing demand for large data rates reveals an increasing spectrum scarcity. So, new paradigms for efficiently exploiting the spectrum are clearly needed. A continuously growing role for adaptive spectrum radios exploiting the capabilities of reconfigurable radio architectures is to be expected. Pushed to the limit, this leads to the disruptive concept of cognitive radio . Cognitive radio is defined as a radio that can autonomously change its transmission parameters based on interaction with the complex environment in which it operates. The spectrum data/mining and agile air interface requirements of such cognitive radios also claim for SDR based implementations. These CR systems can in fact be thought of as extensions of the concepts introduced above, i.e., a reconfigurable radio coupled with a now ―cognitive‖ adaptive control that can sense, adapt and learn. The need to detect and/or generate virtually any kind of waveform in any band pushes, on the other end, the specification of the underlying reconfigurable radio to the limit.

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9. CONCLUSIONS

With the emergence of new standards and protocols, wireless communication is developing at furious pace. The software defined radio represent a major change in the design paradigm for radios in which a large portion of the functionality is implemented through programmable signal processing devices, giving radio the ability to change its operating parameters toaccommodate new features and capabilities. A software radio approach reduces the content of RF and other analog components of conventional radio and emphasizes DSP to enhance overall receiver flexibilities. The mobile wireless communications infrastructure developers and service providers are now coming up with applications of software-defined radio in their business solutions and that is a great success of the concept of the future technology radio- the SDR

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10.REFERANCE

[1] J. Mitola, “The Software Radio Architecture,” IEEE Com- mun. Mag., May 1995[2] Claude Belisle, Vince Kovarik, Lee Pucker, and Mark Turner, “The Software Communications Architecture: Two Decades of Software Radio Technology Innovation”IEEE Communications Magazine., September 2015[3] Christophe Moy and Jacques Palicot,”Software Radio: A Catalyst for Wireless Innovation” IEEE Communications Magazine September”, 2015 [4] www.sdrfuram.org/.../documents[5] Mehul R. Naik1, C. H. Vithalani”The software-defined radio is now a reality”IJAREEIE , Issue 7, July 2013[6] J. Bard and V. Kovarik, Jr., “Software Defined Radio: The Software Communications Architecture”, Wiley, Apr. 2007[7] Eugene Grayver., “Implementing Software Defined Radio”,Springer, 2013

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