CFO Estimation for OFDM-based Massive MIMO Systems in Asymptotic Regime

Massive multiple input multiple output (MIMO) plays a pivotal role in the fifth generation (5G) wireless networks. However, the carrier frequency offset (CFO) estimation is a challenging issue in the uplink of multi-user massive MIMO systems. In fact, frequency synchronization can impose a considerable amount of computational complexity to the base station (BS) due to a large number of BS antennas. In this paper, thanks to the properties of massive MIMO in the asymptotic regime, we develop a simple synchronization technique and derive a closed form equation for CFO estimation. We show that the phase information of the covariance matrix of the received signals is solely dependent on the users’ CFOs. Hence, if a real-valued pilot is chosen, the CFO values can be straightforwardly calculated from this matrix. Hence, there is no need to deal with a complex optimization problem like the other existing CFO estimation techniques in the literature. Our simulation results testify the efficacy of our proposed CFO estimation technique. As we have shown, the performance of our method does not deteriorate as the number of users increases

System capacity enhancement for 5G network and beyond

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

Massive MIMO and Full-duplex Relaying Systems

In this thesis, we study how massive multiple-input and multiple-output (MIMO) can be employed to mitigate loop-interference (LI), multi-user interference and noise in a full-duplex (FD) relaying system. For a FD relaying system with massive MIMO deployed at both source and destination, we investigate three FD relaying schemes: co-located, distributed cooperative, and distributed non-cooperative relaying. Asymptotic analysis shows that the three schemes can completely cancel multi-user interference and LI when the number of antennas at the source and destination grows without bound, in the case where the relay has a finite number of antennas. For the system with massive MIMO deployed at the FD relay, we propose a pilot protocol for LI channel minimum-mean-square-error estimation by exploiting the channel coherence time difference between static and moving transceivers. To maximize the end-to-end achievable rate, we design a novel power allocation scheme to adjust the transmit power of each link at the relay in order to equalize the achievable rate of the source-to-relay and relay-to-destination links. The analytical and numerical results show that the proposed pilot protocol and power allocation scheme jointly improve both spectral and energy efficiency significantly. To enable the use of low resolution analog-to-digital converters (ADCs) at relays for energy saving, we propose a novel iterative power allocation scheme to mitigate the resulting quantization noise via reducing the received LI power and numerically identify the optimum resolutions of ADCs for maximizing throughput and energy efficiency. For massive MIMO receivers employing one-bit ADCs, we propose three carrier frequency (CFO) offset estimation schemes for dual-pilot and multiple-pilot cases. The three schemes are developed under different scenarios: large but finite number of antennas at the receiver, infinite number of antennas at the receiver, and very small CFO, respectively

Evaluation of Sigma-Delta-over-Fiber for High-Speed Wireless Applications

Future mobile communication networks aim to increase the communication speed,\ua0provide better reliability and improve the coverage. It needs to achieve all of these enhancements, while the number of users are increasing drastically. As a result, new base-station (BS) architectures where the signal processing is centralized and wireless access is provided through multiple, carefully coordinated remote radio heads are needed. Sigma-delta-over-fiber (SDoF) is a communication technique that can address both requirements and enable very low-complexity, phase coherent remote radio transmission, while transmitting wide-band communication signals with high quality. This thesis investigates the potential and limitations of SDoF communication links as an enabler for future mobile networks.In the first part of the thesis, an ultra-high-speed SDoF link is realized by using state-of-the-art vertical-cavity surface-emitting-lasers (VCSEL). The effects of VCSEL characteristics on such links in terms of signal quality, energy efficiency and potential lifespan is investigated. Furthermore, the potential and limitations of UHS-SDoF are evaluated with signals having various parameters. The results show that, low-cost, reliable, energy efficient, high signal quality SDoF links can be formed by using emerging VCSEL technology. Therefore, ultra-high-speed SDoF is a very promising technique for beyond 10~GHz communication systems.In the second part of the thesis, a multiple-input-multiple-output (MIMO) communication testbed with physically separated antenna elements, distributed-MIMO, is formed by multiple SDoF links. It is shown that the digital up-conversion, performed with a shared local-oscillator/clock at the central unit, provides excellent phase coherency between the physically distributed antenna elements. The proposed testbed demonstrates the advantages of SDoF for realizing distributed MIMO systems and is a powerful tool to perform various communication experiments in real environments.In general, SDoF is a solution for the downlink of a communication system, i.e. from central unit to remote radio head, however, the low complexity and low cost requirement of the remote radio heads makes it difficult to realize the uplinks of such systems. The third part of this thesis proposes an all-digital solution for realizing complementary uplinks for SDoF systems. The proposed structure is extensively investigated through simulations and measurements and the results demonstrate that it is possible realize all-digital, duplex, optical communication links between central units and remote radio heads.In summary, the results in this thesis demonstrate the potential of SDoF for wideband, distributed MIMO communication systems and proposes a new architecture for all-digital duplex communication links. Overall, the thesis shows that SDoF technique is powerful technique for emerging and future mobile communication networks, since it enables a centralized structure with low complexity remote radio heads and provides high signal quality

Massive Multi-Antenna Communications with Low-Resolution Data Converters

Massive multi-user (MU) multiple-input multiple-output (MIMO) will be a core technology in future cellular communication systems. In massive MU-MIMO systems, the number of antennas at the base station (BS) is scaled up by several orders of magnitude compared to traditional multi-antenna systems with the goals of enabling large gains in capacity and energy efficiency. However, scaling up the number of active antenna elements at the BS will lead to significant increases in power consumption and system costs unless power-efficient and low-cost hardware components are used. In this thesis, we investigate the performance of massive MU-MIMO systems for the case when the BS is equipped with low-resolution data converters.First, we consider the massive MU-MIMO uplink for the case when the BS uses low-resolution analog-to-digital converters (ADCs) to convert the received signal into the digital domain. Our focus is on the case where neither the transmitter nor the receiver have any a priori channel state information (CSI), which implies that the channel realizations have to be learned through pilot transmission followed by BS-side channel estimation, based on coarsely quantized observations. We derive a low-complexity channel estimator and present lower bounds and closed-form approximations for the information-theoretic rates achievable with the proposed channel estimator together with conventional linear detection algorithms. Second, we consider the massive MU-MIMO downlink for the case when the BS uses low-resolution digital-to-analog converters (DACs) to generate the transmit signal. We derive lower bounds and closed-form approximations for the achievable rates with linear precoding under the assumption that the BS has access to perfect CSI. We also propose novel nonlinear precoding algorithms that are shown to significantly outperform linear precoding for the extreme case of 1-bit DACs. Specifically, for the case of symbol-rate 1-bit DACs and frequency-flat channels, we develop a multitude of nonlinear precoders that trade between performance and complexity. We then extend the most promising nonlinear precoders to the case of oversampling 1-bit DACs and orthogonal frequency-division multiplexing for operation over frequency-selective channels.Third, we extend our analysis to take into account other hardware imperfections such as nonlinear amplifiers and local oscillators with phase noise.The results in this thesis suggest that the resolution of the ADCs and DACs in massive MU-MIMO systems can be reduced significantly compared to what is used in today\u27s state-of-the-art communication systems, without significantly reducing the overall system performance