Algorithms for Joint Phase Estimation and Decoding for MIMO Systems in the Presence of Phase Noise and Quasi-Static Fading Channels

In this work, we derive the maximum a posteriori (MAP) symbol detector for a multiple-input multiple-output system in the presence of Wiener phase noise due to noisy local oscillators. As in single-antenna systems, the computation of the optimum receiver is an analytically intractable problem and is unimplementable in practice. In this purview, we propose three suboptimal, low-complexity algorithms for approximately implementing the MAP symbol detector, which involve joint phase noise estimation and data detection. Our first algorithm is obtained by means of the sum-product algorithm, where we use the multivariate Tikhonov canonical distribution approach. In our next algorithm, we derive an approximate MAP symbol detector based on the smoother-detector framework, wherein the detector is properly designed by incorporating the phase noise statistics from the smoother. The third algorithm is derived based on the variational Bayesian framework. By simulations, we evaluate the performance of the proposed algorithms for both uncoded and coded data transmissions, and we observe that the proposed techniques significantly outperform the other important algorithms from prior works, which are considered in this work. Index Terms – Maximum a posteriori (MAP) detection, phase noise, sum-product algorithm (SPA), variational Bayesian (VB) framework, extended Kalman smoother (EKS), MIMO

On the Impact of Phase Noise in Communication Systems –- Performance Analysis and Algorithms

The mobile industry is preparing to scale up the network capacity by a factor of 1000x in order to cope with the staggering growth in mobile traffic. As a consequence, there is a tremendous pressure on the network infrastructure, where more cost-effective, flexible, high speed connectivity solutions are being sought for. In this regard, massive multiple-input multiple-output (MIMO) systems, and millimeter-wave communication systems are new physical layer technologies, which promise to facilitate the 1000 fold increase in network capacity. However, these technologies are extremely prone to hardware impairments like phase noise caused by noisy oscillators. Furthermore, wireless backhaul networks are an effective solution to transport data by using high-order signal constellations, which are also susceptible to phase noise impairments. Analyzing the performance of wireless communication systems impaired by oscillator phase noise, and designing systems to operate efficiently in strong phase noise conditions are critical problems in communication theory. The criticality of these problems is accentuated with the growing interest in new physical layer technologies, and the deployment of wireless backhaul networks. This forms the main motivation for this thesis where we analyze the impact of phase noise on the system performance, and we also design algorithms in order to mitigate phase noise and its effects. First, we address the problem of maximum a posteriori (MAP) detection of data in the presence of strong phase noise in single-antenna systems. This is achieved by designing a low-complexity joint phase-estimator data-detector. We show that the proposed method outperforms existing detectors, especially when high order signal constellations are used. Then, in order to further improve system performance, we consider the problem of optimizing signal constellations for transmission over channels impaired by phase noise. Specifically, we design signal constellations such that the error rate performance of the system is minimized, and the information rate of the system is maximized. We observe that these optimized constellations significantly improve the system performance, when compared to conventional constellations, and those proposed in the literature. Next, we derive the MAP symbol detector for a MIMO system where each antenna at the transceiver has its own oscillator. We propose three suboptimal, low-complexity algorithms for approximately implementing the MAP symbol detector, which involve joint phase noise estimation and data detection. We observe that the proposed techniques significantly outperform the other algorithms in prior works. Finally, we study the impact of phase noise on the performance of a massive MIMO system, where we analyze both uplink and downlink performances. Based on rigorous analyses of the achievable rates, we provide interesting insights for the following question: how should oscillators be connected to the antennas at a base station, which employs a large number of antennas

Receiver Algorithm based on Differential Signaling for SIMO Phase Noise Channels with Common and Separate Oscillator Configurations

In this paper, a receiver algorithm consisting of differential transmission and a two-stage detection for a single-input multiple-output (SIMO) phase-noise channels is studied. Specifically, the phases of the QAM modulated data symbols are manipulated before transmission in order to make them more immune to the random rotational effects of phase noise. At the receiver, a two-stage detector is implemented, which first detects the amplitude of the transmitted symbols from a nonlinear combination of the received signal amplitudes. Then in the second stage, the detector performs phase detection. The studied signaling method does not require transmission of any known symbols that act as pilots. Furthermore, no phase noise estimator (or a tracker) is needed at the receiver to compensate the effect of phase noise. This considerably reduces the complexity of the receiver structure. Moreover, it is observed that the studied algorithm can be used for the setups where a common local oscillator or separate independent oscillators drive the radio-frequency circuitries connected to each antenna. Due to the differential encoding/decoding of the phase, weighted averaging can be employed at a multi-antenna receiver, allowing for phase noise suppression to leverage the large number of antennas. Hence, we observe that the performance improves by increasing the number of antennas, especially in the separate oscillator case. Further increasing the number of receive antennas results in a performance error floor, which is a function of the quality of the oscillator at the transmitter.Comment: IEEE GLOBECOM 201

Performance and Compensation of I/Q Imbalance in Differential STBC-OFDM

Differential space time block coding (STBC) achieves full spatial diversity and avoids channel estimation overhead. Over highly frequency-selective channels, STBC is integrated with orthogonal frequency division multiplexing (OFDM) to achieve high performance. However, low-cost implementation of differential STBC-OFDM using direct-conversion transceivers is sensitive to In-phase/Quadrature-phase imbalance (IQI). In this paper, we quantify the performance impact of IQI at the receiver front-end on differential STBC-OFDM systems and propose a compensation algorithm to mitigate its effect. The proposed receiver IQI compensation works in an adaptive decision-directed manner without using known pilots or training sequences, which reduces the rate loss due to training overhead. Our numerical results show that our proposed compensation algorithm can effectively mitigate receive IQI in differential STBC-OFDM.Comment: 7 pages, 2 figures, IEEE GLOBECOM 201

MIMO Systems

In recent years, it was realized that the MIMO communication systems seems to be inevitable in accelerated evolution of high data rates applications due to their potential to dramatically increase the spectral efficiency and simultaneously sending individual information to the corresponding users in wireless systems. This book, intends to provide highlights of the current research topics in the field of MIMO system, to offer a snapshot of the recent advances and major issues faced today by the researchers in the MIMO related areas. The book is written by specialists working in universities and research centers all over the world to cover the fundamental principles and main advanced topics on high data rates wireless communications systems over MIMO channels. Moreover, the book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Doctor of Philosophy

dissertationMultiple-input and multiple-output (MIMO) technique has emerged as a key feature for future generations of wireless communication systems. It increases the channel capacity proportionate to the minimum number of transmit and receive antennas. This dissertation addresses the receiver design for high-rate MIMO communications in at fading environments. The emphasis of the thesis is on the cases where channel state information (CSI) is not available and thus, clever channel estimation algorithms have to be developed to bene t from the maximum available channel capacity. The thesis makes four distinct novel contributions. First, we note that the conventional MCMC-MIMO detector presented in the prior work may deteriorate as SNR increases. We suggest and show through computer simulations that this problem to a great extent can be solved by initializing the MCMC detector with regulated states which are found through linear detectors. We also introduce the novel concept of staged-MCMC in a turbo receiver, where we start the detection process at a lower complexity and increase complexity only if the data could not be correctly detected in the present stage of data detection. Second, we note that in high-rate MIMO communications, joint data detection and channel estimation poses new challenges when a turbo loop is used to improve the quality of the estimated channel and the detected data. Erroneous detected data may propagate in the turbo loop and, thus, degrade the performance of the receiver signi cantly. This is referred to as error propagation. We propose a novel receiver that decorrelates channel estimation and the detected data to avoid the detrimental e ect of error propagation. Third, the dissertation studies joint channel estimation and MIMO detection over a continuously time-varying channel and proposes a new dual-layer channel estimator to overcome the complexity of optimal channel estimators. The proposed dual-layer channel estimator reduces the complexity of the MIMO detector with optimal channel estimator by an order of magnitude at a cost of a negligible performance degradation, on the order of 0.1 to 0.2 dB. The fourth contribution of this dissertation is to note that the Wiener ltering techniques that are discussed in this dissertation and elsewhere in the literature assume that channel (time-varying) statistics are available. We propose a new method that estimates such statistics using the coarse channel estimates obtained through pilot symbols. The dissertation also makes an additional contribution revealing di erences between the MCMC-MIMO and LMMSE-MIMO detectors. We nd that under the realistic condition where CSI has to be estimated, hence the available channel estimate will be noisy, the MCMC-MIMO detector outperforms the LMMSE-MIMO detector with a signi cant margin