Highly-configurable FPGA-based platform for wireless network research

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 155-164).Over the past few years, researchers have developed many cross-layer wireless protocols to improve the performance of wireless networks. Experimental evaluations of these protocols require both high-speed simulations and real-time on-air experimentations. Unfortunately, radios implemented in pure software are usually inadequate for either because they are typically two to three orders of magnitude slower than commodity hardware. FPGA-based platforms provide much better speeds but are quite difficult to modify because of the way high-speed designs are typically implemented by trading modularity for performance. Experimenting with cross-layer protocols requires a flexible way to convey information beyond the data itself from lower to higher layers, and a way for higher layers to configure lower layers dynamically and within some latency bounds. One also needs to be able to modify a layer's processing pipeline without triggering a cascade of changes. In this thesis, we discuss an alternative approach to implement a high-performance yet configurable radio design on an FPGA platform that satisfies these requirements. We propose that all modules in the design must possess two important design properties, namely latency-insensitivity and datadriven control, which facilitate modular refinements. We have developed Airblue, an FPGA-based radio, that has all these properties and runs at speeds comparable to commodity hardware. Our baseline design is 802.11g compliant and is able to achieve reliable communication for bit rates up to 24 Mbps. We show in the thesis that we can implement SoftRate, a cross-layer rate adaptation protocol, by modifying only 5.6% of the source code (967 lines). We also show that our modular design approach allows us to abstract the details of the FPGA platform from the main design, thus making the design portable across multiple FPGA platforms. By taking advantage of this virtualization capability, we were able to turn Airblue into a high-speed hardware software co-simulator with simulation speed beyond 20 Mbps.by Man Cheuk Ng.Ph.D

Synchronization algorithms and architectures for wireless OFDM systems

Orthogonal frequency division multiplexing (OFDM) is a multicarrier modulation technique that has become a viable method for wireless communication systems due to the high spectral efficiency, immunity to multipath distortion, and being flexible to integrate with other techniques. However, the high-peak-to-average power ratio and sensitivity to synchronization errors are the major drawbacks for OFDM systems. The algorithms and architectures for symbol timing and frequency synchronization have been addressed in this thesis because of their critical requirements in the development and implementation of wireless OFDM systems. For the frequency synchronization, two efficient carrier frequency offset (CFO) estimation methods based on the power and phase difference measurements between the subcarriers in consecutive OFDM symbols have been presented and the power difference measurement technique is mapped onto reconfigurable hardware architecture. The performance of the considered CFO estimators is investigated in the presence of timing uncertainty conditions. The power difference measurements approach is further investigated for timing synchronization in OFDM systems with constant modulus constellation. A new symbol timing estimator has been proposed by measuring the power difference either between adjacent subcarriers or the same subcarrier in consecutive OFDM symbols. The proposed timing metric has been realized in feedforward and feedback configurations, and different implementation strategies have been considered to enhance the performance and reduce the complexity. Recently, multiple-input multiple-output (MIMO) wireless communication systems have received considerable attention. Therefore, the proposed algorithms have also been extended for timing recovery and frequency synchronization in MIMO-OFDM systems. Unlike other techniques, the proposed timing and frequency synchronization architectures are totally blind in the sense that they do not require any information about the transmitted data, the channel state or the signal-to-noise-ratio (SNR). The proposed frequency synchronization architecture has low complexity because it can be implemented efficiently using the three points parameter estimation approach. The simulation results confirmed that the proposed algorithms provide accurate estimates for the synchronization parameters using a short observation window. In addition, the proposed synchronization techniques have demonstrated robust performance over frequency selective fading channels that significantly outperform other well-established methods which will in turn benefit the overall OFDM system performance. Furthermore, an architectural exploration for mapping the proposed frequency synchronization algorithm, in particular the CFO estimation based on the power difference measurements, on reconfigurable computing architecture has been investigated. The proposed reconfigurable parallel and multiplexed-stream architectures with different implementation alternatives have been simulated, verified and compared for field programmable gate array (FPGA) implementation using the Xilinx’s DSP design flow.EThOS - Electronic Theses Online ServiceMinistry of Higher Education and Scientific Research (MOHSR) of IraqGBUnited Kingdo

Enhancing spectrum utilization through cooperation and cognition in wireless systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2013.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections."February 2013." Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (p. 201-217).We have seen a proliferation of wireless technologies and devices in recent years. The resulting explosion of wireless demand has put immense pressure on available spectrum. Improving spectrum utilization is therefore necessary to enable wireless networks to keep up with burgeoning demand. This dissertation presents a cognitive and cooperative wireless architecture that significantly enhances spectrum utilization. Specifically, it introduces four new systems that embody a cross-layer design for cognition and cooperation. The first system, SWIFT, is a cognitive cross technology solution that enables wideband devices to exploit higher layer network semantics to adaptively sense which portions of the spectrum are occupied by unknown narrowband devices, and weave the remaining unoccupied spectrum bands into a single high-throughput wideband link. Second, FARA is a cooperative system that enables multi-channel wireless solutions like 802.11 to dynamically use all available channels for all devices in a performance-aware manner by using information from the physical layer and allocating to each link the frequency bands that show the highest performance for that link. SourceSync, the third system, enables wireless nodes in last-hop and wireless mesh networks to cooperatively transmit synchronously in order to exploit channel diversity and increase reliability. Finally, MegaMIMO enables wireless throughput to scale linearly with the number of transmitters by enabling multiple wireless transmitters to transmit simultaneously in the same frequency bands to multiple wireless receivers without interfering with each other. The systems in this dissertation demonstrate the practicality of cognitive and cooperative wireless systems to enable spectrum sharing. Further, as part of these systems, we design several novel primitives - adaptive spectrum sensing, time alignment, frequency synchronization, and distributed phase-coherent transmission, that can serve as fundamental building blocks for wireless cognition and cooperation. Finally, we have implemented all four systems described in this dissertation, and evaluated them in wireless testbeds, demonstrating large gains in practice.by Hariharan Shankar Rahul.Ph.D

Adaptive Resource Allocation Algorithms For Data And Energy Integrated Networks Supporting Internet of Things

According to the forecast, there are around 2.1 billion IoT devices connected to the network by 2022. The rapidly increased IoT devices bring enormous pressure to the energy management work as most of them are battery-powered gadgets. What’s more, in some specific scenarios, the IoT nodes are fitted in some extreme environment. For example, a large-scale IoT pressure sensor system is deployed underneath the floor to detect people moving across the floor. A density-viscosity sensor is deployed inside the fermenting vat to discriminate variations in density and viscosity for monitoring the wine fermentation. A strain distribution wireless sensor for detecting the crack formation of the bridge is deployed underneath the bridge and attached near the welded part of the steel. It is difficult for people to have an access to the extreme environment. Hence, the energy management work, namely, replacing batteries for the rapidly increased IoT sensors in the extreme environment brings more challenges. In order to reduce the frequency of changing batteries, the thesis proposes a self-management Data and Energy Integrated Network (DEIN) system, which designs a stable and controllable ambient RF resource to charge the battery-less IoT wireless devices. It embraces an adaptive energy management mechanism for automatically maintaining the energy level of the battery-less IoT wireless devices, which always keeps the devices within a workable voltage range that is from 2.9 to 4.0 volts. Based on the DEIN system, RF energy transmission is achieved by transmitting the designed packets with enhanced transmission power. However, it partly occupies the bandwidth which was only used for wireless information transmission. Hence, a scheduling cycle mechanism is proposed in the thesis for organizing the RF energy and wireless information transmission in separate time slots. In addition, a bandwidth allocation algorithm is proposed to minimize the bandwidth for RF energy transmission in order to maximize the throughput of wireless information. To harvest the RF energy, the RF-to-DC energy conversion is essential at the receiver side. According to the existing technologies, the hardware design of the RF-to-DC energy converter is normally realized by the voltage rectifier which is structured by multiple Schottky diodes and capacitors. Research proves that a maximum of 84% RF-to-DC conversion efficiency is obtained by comparing a variety of different wireless band for transmitting RF energy. Furthermore, there is energy loss in the air during transmitting the RF energy to the receiver. Moreover, the circuital loss happens when the harvested energy is utilized by electronic components. Hence, how to improve the efficiency of RF energy utilization is considered in the thesis. According to the scenario proposed in the thesis, the harvested energy is mainly consumed for uplink transmission. a resource allocation algorithm is proposed to minimize the system’s energy consumption per bit of uplink data. It works out the optimal transmission power for RF energy as well as the bandwidth allocated for RF energy and wireless information transmission. Referring to the existing RF energy transmission and harvesting application on the market, the Powercast uses the supercapacitor to preserve the harvested RF energy. Due to the lack of self-control energy management mechanism for the embedded sensor, the harvested energy is consumed quickly, and the system has to keep transmitting RF energy. Existing jobs have proposed energy-saving methods for IoT wireless devices such as how to put them in sleep mode and how to reduce transmission power. However,they are not adaptive, and that would be an issue for a practical application. In the thesis, an energy-saving algorithm is designed to adaptively manage the transmission power of the device for uplink data transmission. The algorithm balances the trade-off between the transmission power and the packet loss rate. It finds the optimal transmission power to minimize the average energy cost for uplink data transmission, which saves the harvested energy to reduce the frequency of RF energy transmission to free more bandwidth for wireless information