Software Defined Radio (SDR) is a flexible architecture which can be configured to adapt various wireless standards, waveforms, frequency bands, bandwidths, and modes of operations. This paper presents a detailed survey of the existing hardware and software platform for SDRs. It also presents prototype system for designing and testing of software defined radios in MATLAB/Simulink and briefly discusses the salient functions of the prototype system for Cognitive Radio (CR). A prototype system for wireless personal area network is built and interfaced with a Universal Software Radio Peripheral-2 (USRP2) main-board and RFX2400 daughter board from EttusResearch LLC. The philosophy behind the prototype is to do all waveform-specific processing such as channel coding, modulation, filtering etc. on a host (PC) and general purpose high-speed operations like digital up and down conversion, decimation and interpolation etc. inside FPGA on an USRP2. MATLAB has a rich family of toolboxes that allows building software-defined and cognitive radio to explore various spectrum sensing, prediction and management techniques.

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SUMMARYThin client computing trades local processing for network bandwidth by off-loading application logic to remote servers. User input and display updates are exchanged between client and server through a thin client protocol. In a wireless device context, it is important to achieve bandwidth efficient thin client protocols because bandwidth availability is limited and the power consumption of the wireless network interface card is directly related to the amount of data that is sent and received. This paper presents and evaluates a novel client-based mechanism which is transparent to the server to reduce upstream bandwidth consumption. Typically, thin client protocols encode user input as a series of small packets, resulting in a major packetization overhead. By buffering user events at the thin client protocol layer, this overhead can be reduced. However, buffering strategies might result in increased response delays for the user. Therefore, models of the upstream bandwidth and the user perceived responsiveness of pull thin client protocols are presented and validated. These models are used in an adaptive framework, which determines the appropriate buffering time to minimize the bandwidth as much as possible without degrading the responsiveness. For lower network roundtrip times and users actively generating input, it is shown how bandwidth savings up to 78% can be achieved while keeping the average user perceived responsiveness below 150 ms.

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