735 research outputs found

    Single carrier frequency domain equalization and energy efficiency optimization for MIMO cognitive radio.

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    This dissertation studies two separate topics in wireless communication systems. One topic focuses on the Single Carrier Frequency Domain Equalization (SC-FDE), which is a promising technique to mitigate the multipath effect in the broadband wireless communication. Another topic targets on the energy efficiency optimization in a multiple input multiple output (MIMO) cognitive radio network. For SC-FDE, the conventional linear receivers suffer from the noise amplification in deep fading channel. To overcome this, a fractional spaced frequency domain (FSFD) receiver based on frequency domain oversampling (FDO) is proposed for SC-FDE to improve the performance of the linear receiver under deep fading channels. By properly designing the guard interval, a larger sized Discrete Fourier Transform (DFT) is equipped to oversample the received signal in frequency domain. Thus, the effect of frequency-selective fading can still be eliminated by a one-tap frequency domain filter. Two types of FSFD receivers are proposed based on the least square (LS) and minimum mean square error (MMSE) criterion. Both the semi-analytical analysis and simulation results are given to evaluate the performance of the proposed receivers. Another challenge in SC-FDE is the in-phase/quadrature phase (IQ) imbalance caused by unideal radio frequency (RF) front-end at the transmitter or the receiver. Most existing works in single carrier transmission employ linear compensation methods, such as LS and MMSE, to combat the interference caused by IQ imbalance. Actually, for single carrier transmissions, it is possible for the receivers to adopt advanced nonlinear compensation methods to improve the system performance under IQ imbalance. For such purpose, an iterative decision feedback receiver is proposed to compensate the IQ imbalance caused by unideal RF front-end in SC-FDE. Numerical results show that the proposed iterative IQ imbalance compensation can significantly improve the performance of SC-FDE system under IQ imbalance compared with the conventional linear method. For the energy efficiency optimization in the MIMO cognitive radio network, multiple secondary users (SUs) coexisting with a primary user (PU) adjust their antenna radiation patterns and power allocations to achieve energy-efficient transmission. The optimization problems are formulated to maximize the energy efficiency of a cognitive radio network in both distributed and centralized point of views. Also, constraints on the transmission power and the interference to PU are introduced to protect the PU’s transmission. In order to solve the non-convex optimization problems, convex relaxations are used to transform them into equivalent problems with better tractability. Then three optimization algorithms are proposed to find the energy-efficient transmission strategies. Simulation results show that the proposed energy-efficiency optimization algorithms outperform the existing algorithms

    Multipath Multiplexing for Capacity Enhancement in SIMO Wireless Systems

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    This paper proposes a novel and simple orthogonal faster than Nyquist (OFTN) data transmission and detection approach for a single input multiple output (SIMO) system. It is assumed that the signal having a bandwidth BB is transmitted through a wireless channel with LL multipath components. Under this assumption, the current paper provides a novel and simple OFTN transmission and symbol-by-symbol detection approach that exploits the multiplexing gain obtained by the multipath characteristic of wideband wireless channels. It is shown that the proposed design can achieve a higher transmission rate than the existing one (i.e., orthogonal frequency division multiplexing (OFDM)). Furthermore, the achievable rate gap between the proposed approach and that of the OFDM increases as the number of receiver antennas increases for a fixed value of LL. This implies that the performance gain of the proposed approach can be very significant for a large-scale multi-antenna wireless system. The superiority of the proposed approach is shown theoretically and confirmed via numerical simulations. {Specifically, we have found {upper-bound average} rates of 15 bps/Hz and 28 bps/Hz with the OFDM and proposed approaches, respectively, in a Rayleigh fading channel with 32 receive antennas and signal to noise ratio (SNR) of 15.3 dB. The extension of the proposed approach for different system setups and associated research problems is also discussed.Comment: IEEE Transactions on Wireless Communication

    Channel estimation in massive MIMO systems

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    Last years were characterized by a great demand for high data throughput, good quality and spectral efficiency in wireless communication systems. Consequently, a revolution in cellular networks has been set in motion towards to 5G. Massive multiple-input multiple-output (MIMO) is one of the new concepts in 5G and the idea is to scale up the known MIMO systems in unprecedented proportions, by deploying hundreds of antennas at base stations. Although, perfect channel knowledge is crucial in these systems for user and data stream separation in order to cancel interference. The most common way to estimate the channel is based on pilots. However, problems such as interference and pilot contamination (PC) can arise due to the multiplicity of channels in the wireless link. Therefore, it is crucial to define techniques for channel estimation that together with pilot contamination mitigation allow best system performance and at same time low complexity. This work introduces a low-complexity channel estimation technique based on Zadoff-Chu training sequences. In addition, different approaches were studied towards pilot contamination mitigation and low complexity schemes, with resort to iterative channel estimation methods, semi-blind subspace tracking techniques and matrix inversion substitutes. System performance simulations were performed for the several proposed techniques in order to identify the best tradeoff between complexity, spectral efficiency and system performance

    Resource allocation and optimization techniques in wireless relay networks

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    Relay techniques have the potential to enhance capacity and coverage of a wireless network. Due to rapidly increasing number of smart phone subscribers and high demand for data intensive multimedia applications, the useful radio spectrum is becoming a scarce resource. For this reason, two way relay network and cognitive radio technologies are required for better utilization of radio spectrum. Compared to the conventional one way relay network, both the uplink and the downlink can be served simultaneously using a two way relay network. Hence the effective bandwidth efficiency is considered to be one time slot per transmission. Cognitive networks are wireless networks that consist of different types of users, a primary user (PU, the primary license holder of a spectrum band) and secondary users (SU, cognitive radios that opportunistically access the PU spectrum). The secondary users can access the spectrum of the licensed user provided they do not harmfully affect to the primary user. In this thesis, various resource allocation and optimization techniques have been investigated for wireless relay and cognitive radio networks

    Feedback Mechanisms for Centralized and Distributed Mobile Systems

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    The wireless communication market is expected to witness considerable growth in the immediate future due to increasing smart device usage to access real-time data. Mobile devices become the predominant method of Internet access via cellular networks (4G/5G) and the onset of virtual reality (VR), ushering in the wide deployment of multiple bands, ranging from TVWhite Spaces to cellular/WiFi bands and on to mmWave. Multi-antenna techniques have been considered to be promising approaches in telecommunication to optimize the utilization of radio spectrum and minimize the cost of system construction. The performance of multiple antenna technology depends on the utilization of radio propagation properties and feedback of such information in a timely manner. However, when a signal is transmitted, it is usually dispersed over time coming over different paths of different lengths due to reflections from obstacles or affected by Doppler shift in mobile environments. This motivates the design of novel feedback mechanisms that improve the performance of multi-antenna systems. Accurate channel state information (CSI) is essential to increasing throughput in multiinput, multi-output (MIMO) systems with digital beamforming. Channel-state information for the operation of MIMO schemes (such as transmit diversity or spatial multiplexing) can be acquired by feedback of CSI reports in the downlink direction, or inferred from uplink measurements assuming perfect channel reciprocity (CR). However, most works make the assumption that channels are perfectly reciprocal. This assumption is often incorrect in practice due to poor channel estimation and imperfect channel feedback. Instead, experiments have demonstrated that channel reciprocity can be easily broken by multiple factors. Specifically, channel reciprocity error (CRE) introduced by transmitter-receiver imbalance have been widely studied by both simulations and experiments, and the impact of mobility and estimation error have been fully investigated in this thesis. In particular, unmanned aerial vehicles (UAVs) have asymmetric behavior when communicating with one another and to the ground, due to differences in altitude that frequently occur. Feedback mechanisms are also affected by channel differences caused by the user’s body. While there has been work to specifically quantify the losses in signal reception, there has been little work on how these channel differences affect feedback mechanisms. In this dissertation, we perform system-level simulations, implement design with a software defined radio platform, conduct in-field experiments for various wireless communication systems to analyze different channel feedback mechanisms. To explore the feedback mechanism, we then explore two specific real world scenarios, including UAV-based beamforming communications, and user-induced feedback systems

    Massive MIMO transmission techniques

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    Next generation of mobile communication systems must support astounding data traffic increases, higher data rates and lower latency, among other requirements. These requirements should be met while assuring energy efficiency for mobile devices and base stations. Several technologies are being proposed for 5G, but a consensus begins to emerge. Most likely, the future core 5G technologies will include massive MIMO (Multiple Input Multiple Output) and beamforming schemes operating in the millimeter wave spectrum. As soon as the millimeter wave propagation difficulties are overcome, the full potential of massive MIMO structures can be tapped. The present work proposes a new transmission system with bi-dimensional antenna arrays working at millimeter wave frequencies, where the multiple antenna configurations can be used to obtain very high gain and directive transmission in point to point communications. A combination of beamforming with a constellation shaping scheme is proposed, that enables good user isolation and protection against eavesdropping, while simultaneously assuring power efficient amplification of multi-level constellations
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