177 research outputs found

    System capacity enhancement for 5G network and beyond

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    A thesis submitted to the University of Bedfordshire, in fulfilment of the requirements for the degree of Doctor of PhilosophyThe demand for wireless digital data is dramatically increasing year over year. Wireless communication systems like Laptops, Smart phones, Tablets, Smart watch, Virtual Reality devices and so on are becoming an important part of people’s daily life. The number of mobile devices is increasing at a very fast speed as well as the requirements for mobile devices such as super high-resolution image/video, fast download speed, very short latency and high reliability, which raise challenges to the existing wireless communication networks. Unlike the previous four generation communication networks, the fifth-generation (5G) wireless communication network includes many technologies such as millimetre-wave communication, massive multiple-input multiple-output (MIMO), visual light communication (VLC), heterogeneous network (HetNet) and so forth. Although 5G has not been standardised yet, these above technologies have been studied in both academia and industry and the goal of the research is to enhance and improve the system capacity for 5G networks and beyond by studying some key problems and providing some effective solutions existing in the above technologies from system implementation and hardware impairments’ perspective. The key problems studied in this thesis include interference cancellation in HetNet, impairments calibration for massive MIMO, channel state estimation for VLC, and low latency parallel Turbo decoding technique. Firstly, inter-cell interference in HetNet is studied and a cell specific reference signal (CRS) interference cancellation method is proposed to mitigate the performance degrade in enhanced inter-cell interference coordination (eICIC). This method takes carrier frequency offset (CFO) and timing offset (TO) of the user’s received signal into account. By reconstructing the interfering signal and cancelling it afterwards, the capacity of HetNet is enhanced. Secondly, for massive MIMO systems, the radio frequency (RF) impairments of the hardware will degrade the beamforming performance. When operated in time duplex division (TDD) mode, a massive MIMO system relies on the reciprocity of the channel which can be broken by the transmitter and receiver RF impairments. Impairments calibration has been studied and a closed-loop reciprocity calibration method is proposed in this thesis. A test device (TD) is introduced in this calibration method that can estimate the transmitters’ impairments over-the-air and feed the results back to the base station via the Internet. The uplink pilots sent by the TD can assist the BS receivers’ impairment estimation. With both the uplink and downlink impairments estimates, the reciprocity calibration coefficients can be obtained. By computer simulation and lab experiment, the performance of the proposed method is evaluated. Channel coding is an essential part of a wireless communication system which helps fight with noise and get correct information delivery. Turbo codes is one of the most reliable codes that has been used in many standards such as WiMAX and LTE. However, the decoding process of turbo codes is time-consuming and the decoding latency should be improved to meet the requirement of the future network. A reverse interleave address generator is proposed that can reduce the decoding time and a low latency parallel turbo decoder has been implemented on a FPGA platform. The simulation and experiment results prove the effectiveness of the address generator and show that there is a trade-off between latency and throughput with a limited hardware resource. Apart from the above contributions, this thesis also investigated multi-user precoding for MIMO VLC systems. As a green and secure technology, VLC is achieving more and more attention and could become a part of 5G network especially for indoor communication. For indoor scenario, the MIMO VLC channel could be easily ill-conditioned. Hence, it is important to study the impact of the channel state to the precoding performance. A channel state estimation method is proposed based on the signal to interference noise ratio (SINR) of the users’ received signal. Simulation results show that it can enhance the capacity of the indoor MIMO VLC system

    FPGA Prototyping of A High Data Rate LTE Uplink Baseband Receiver

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    The Third Generation Partnership Project (3GPP) Long Term Evolution (LTE) standard is becoming the appropriate choice to pave the way for the next generation wireless and cellular standards. While the popular OFDM technique has been adopted and implemented in previous standards and also in the LTE downlink, it suffers from high peak-to-average-power ratio (PAPR). High PAPR requires more sophisticated power amplifiers (PAs) in the handsets and would result in lower efficiency PAs. In order to combat such effects, the LTE uplink choice of transmission is the novel Single Carrier Frequency Division Multiple Access (SC-FDMA) scheme which has lower PAPR due to its inherent signal structure. While reducing the PAPR, the SC-FDMA requires a more complicated detector structure in the base station for multi-antenna and multi-user scenarios. Since the multi-antenna and multi-user scenarios are critical parts of the LTE standard to deliver high performance and data rate, it is important to design novel architectures to ensure high reliability and data rate in the receiver. In this paper, we propose a flexible architecture of a high data rate LTE uplink receiver with multiple receive antennas and implemented a single FPGA prototype of this architecture. The architecture is verified on the WARPLab (a software defined radio platform based on Rice Wireless Open-access Research Platform) and tested in the real over-the-air indoor channel.NokiaNokia Siemens Networks (NSN)XilinxAzimuth SystemsNational Science Foundatio

    Exploring HLS Coding Techniques to Achieve Desired Turbo Decoder Architectures

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    Software defined radio (SDR) platforms implement many digital signal processing algorithms. These can be accelerated on an FPGA to meet performance requirements. Due to the flexibility of SDR\u27s and continually evolving communications protocols, high level synthesis (HLS) is a promising alternative to standard handcrafted design flows. A crucial component in any SDR is the error correction codes (ECC). Turbo codes are a common ECC that are implemented on an FPGA due to their computational complexity. The goal of this thesis is to explore the HLS coding techniques required to produce a design that targets the desired hardware architecture and can reach handcrafted levels of performance. This work implemented three existing turbo decoder architectures with HLS to produce quality hardware which reaches handcrafted performance. Each targeted design was analyzed to determine its functionality and algorithm so a C implementation could be developed. Then the C code was modified and HLS directives were added to refine the design through the HLS tools. The process of code modification and processing through the HLS tools continued until the desired architecture and performance were reached. Each design was implemented and the bottlenecks were identified and dealt with through appropriate usage of directives and C style. The use of pipelining to bypass bottlenecks added a small overhead from the ramp-up and ramp-down of the pipeline, reducing the performance by at most 1.24%. The impact of the clock constraint set within the HLS tools was also explored. It was found that the clock period and resource usage estimate generated by the HLS tools is not accurate and all evaluations should occur after hardware synthesis

    1.5 Gbit/s FPGA implementation of a fully-parallel turbo decoder designed for mission-critical machine-type communication applications

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    In wireless communication schemes, turbo codes facilitate near-capacity transmission throughputs by achieving reliable forward error correction. However, owing to the serial data dependencies imposed by the underlying Logarithmic Bahl-Cocke-Jelinek-Raviv (Log- BCJR) algorithm, the limited processing throughputs of conventional turbo decoder implementations impose a severe bottleneck upon the overall throughputs of realtime wireless communication schemes. Motivated by this, we recently proposed a Fully Parallel Turbo Decoder (FPTD) algorithm, which eliminates these serial data dependencies, allowing parallel processing and hence offering a significantly higher processing throughput. In this paper, we propose a novel resource-efficient version of the FPTD algorithm, which reduces its computational resource requirement by 50%, which enhancing its suitability for Field-Programmable Gate Array (FPGA) implementations. We propose a model FPGA implementation. When using a Stratix IV FPGA, the proposed FPTD FPGA implementation achieves an average throughput of 1.53 Gbit/s and an average latency of 0.56 s, when decoding frames comprising N=720 bits. These are respectively 13.2 times and 11.1 times superior to those of the state-of-the- art FPGA implementation of the Log-BCJR Long- Term Evolution (LTE) turbo decoder, when decoding frames of the same frame length at the same error correction capability. Furthermore, our proposed FPTD FPGA implementation achieves a normalized resource usage of 0.42 kALUTs Mbit/s , which is 5.2 times superior to that of the benchmarker decoder. Furthermore, when decoding the shortest N=40-bit LTE frames, the proposed FPTD FPGA implementation achieves an average throughput of 442 Mbit/s and an average latency of 0.18 s, which are respectively 21.1 times and 10.6 times superior to those of the benchmarker decoder. In this case, the normalized resource usage of 0.08 kALUTs Mbit/s is 146.4 times superior to that of the benchmarker decoder

    Datacenter Design for Future Cloud Radio Access Network.

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    Cloud radio access network (C-RAN), an emerging cloud service that combines the traditional radio access network (RAN) with cloud computing technology, has been proposed as a solution to handle the growing energy consumption and cost of the traditional RAN. Through aggregating baseband units (BBUs) in a centralized cloud datacenter, C-RAN reduces energy and cost, and improves wireless throughput and quality of service. However, designing a datacenter for C-RAN has not yet been studied. In this dissertation, I investigate how a datacenter for C-RAN BBUs should be built on commodity servers. I first design WiBench, an open-source benchmark suite containing the key signal processing kernels of many mainstream wireless protocols, and study its characteristics. The characterization study shows that there is abundant data level parallelism (DLP) and thread level parallelism (TLP). Based on this result, I then develop high performance software implementations of C-RAN BBU kernels in C++ and CUDA for both CPUs and GPUs. In addition, I generalize the GPU parallelization techniques of the Turbo decoder to the trellis algorithms, an important family of algorithms that are widely used in data compression and channel coding. Then I evaluate the performance of commodity CPU servers and GPU servers. The study shows that the datacenter with GPU servers can meet the LTE standard throughput with 4× to 16× fewer machines than with CPU servers. A further energy and cost analysis show that GPU servers can save on average 13× more energy and 6× more cost. Thus, I propose the C-RAN datacenter be built using GPUs as a server platform. Next I study resource management techniques to handle the temporal and spatial traffic imbalance in a C-RAN datacenter. I propose a “hill-climbing” power management that combines powering-off GPUs and DVFS to match the temporal C-RAN traffic pattern. Under a practical traffic model, this technique saves 40% of the BBU energy in a GPU-based C-RAN datacenter. For spatial traffic imbalance, I propose three workload distribution techniques to improve load balance and throughput. Among all three techniques, pipelining packets has the most throughput improvement at 10% and 16% for balanced and unbalanced loads, respectively.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120825/1/qizheng_1.pd

    SCATTER PHY : an open source physical layer for the DARPA spectrum collaboration challenge

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    DARPA, the Defense Advanced Research Projects Agency from the United States, has started the Spectrum Collaboration Challenge with the aim to encourage research and development of coexistence and collaboration techniques of heterogeneous networks in the same wireless spectrum bands. Team SCATTER has been participating in the challenge since its beginning, back in 2016. SCATTER's open-source software defined physical layer (SCATTER PHY) has been developed as a standalone application, with the ability to communicate with higher layers through a set of well defined messages (created with Google's Protocol buffers) and that exchanged over a ZeroMQ bus. This approach allows upper layers to access it remotely or locally and change all parameters in real time through the control messages. SCATTER PHY runs on top of USRP based software defined radio devices (i.e., devices from Ettus or National Instruments) to send and receive wireless signals. It is a highly optimized and real-time configurable SDR based PHY layer that can be used for the research and development of novel intelligent spectrum sharing schemes and algorithms. The main objective of making SCATTER PHY available to the research and development community is to provide a solution that can be used out of the box to devise disruptive algorithms and techniques to optimize the sub-optimal use of the radio spectrum that exists today. This way, researchers and developers can mainly focus their attention on the development of smarter (i.e., intelligent algorithms and techniques) spectrum sharing approaches. Therefore, in this paper, we describe the design and main features of SCATTER PHY and showcase several experiments performed to assess the effectiveness and performance of the proposed PHY layer

    LTE uplink MIMO receiver with low complexity interference cancellation

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    In LTE/LTE-A uplink receiver, frequency domain equalizers (FDE) are adopted to achieve good performance. However, in multi-tap channels, the residual inter-symbol and inter-antenna interference still exist after FDE and degrade the performance. Conventional interference cancellation schemes can minimize this interference by using frequency domain interference cancellation. However, those schemes have high complexity and large feedback latency, especially when adopting a large number of iterations. These result in low throughput and require a large amount of resource in software defined radio implementation. In this paper, we propose a novel low complexity interference cancellation scheme to minimize the residual interference in LTE/LTE-A uplink. Our proposed scheme can bring about 2 dB gains in different channels, but only adds up to 7.2 % complexity to the receiver. The scheme is further implemented on Xilinx FPGA. Compared to other conventional interference cancellation schemes, our scheme has less complexity, less data to store, and shorter feedback latency.Renesas MobileTexas IntrumentsXilinxSamsungHuaweiNational Science Foundation (NSF

    Unified turbo/LDPC code decoder architecture for deep-space communications

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    Deep-space communications are characterized by extremely critical conditions; current standards foresee the usage of both turbo and low-density-parity-check (LDPC) codes to ensure recovery from received errors, but each of them displays consistent drawbacks. Code concatenation is widely used in all kinds of communication to boost the error correction capabilities of single codes; serial concatenation of turbo and LDPC codes has been recently proven effective enough for deep space communications, being able to overcome the shortcomings of both code types. This work extends the performance analysis of this scheme and proposes a novel hardware decoder architecture for concatenated turbo and LDPC codes based on the same decoding algorithm. This choice leads to a high degree of datapath and memory sharing; postlayout implementation results obtained with complementary metal-oxide semiconductor (CMOS) 90 nm technology show small area occupation (0.98 mm 2 ) and very low power consumption (2.1 mW)

    State of the art baseband DSP platforms for Software Defined Radio: A survey

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    Software Defined Radio (SDR) is an innovative approach which is becoming a more and more promising technology for future mobile handsets. Several proposals in the field of embedded systems have been introduced by different universities and industries to support SDR applications. This article presents an overview of current platforms and analyzes the related architectural choices, the current issues in SDR, as well as potential future trends.Peer reviewe
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