Phase noise effects on OFDM : analysis and mitigation

Orthogonal frequency division multiplexing (OFDM) is a promising technique which has high spectrum efficiency and the robustness against channel frequency selectivity. One drawback of OFDM is its sensitivity to phase noise. It has been shown that even small phase noise leads to significant performance loss of OFDM. Therefore, phase noise effects on OFDM systems need to be analyzed and methods be provided to its mitigation. Motivated by what have been proposed in the literature, the exact signal to interference plus noise ratio (SINR) is derived in this dissertation for arbitrary phase noise levels. In a multiple access environment with multiple phase noise, the closed form of bit error rate (BER) performance is derived as a function of phase noise parameters. Due to the detrimental effects of phase noise on OFDM, phase noise mitigation is quite necessary. Several schemes are proposed to mitigate both single and multiple phase noise. It is shown that, while outperforming conventional methods, these schemes have the performance close to no-phase-noise case. Two general approaches are presented which extend the conventional schemes proposed in the literature, making them special cases of these general approaches. Moreover, different implementation techniques are also presented. Analytical and numerical results are provided to compare the performance of these migitation approaches and implementation techniques. Similar to OFDM, an OFDM system with multiple antennas, i.e., Multiple Input. Multiple Output (MIMO)-OFDM, also suffer severe performance degradation due to phase noise, and what have been proposed in the literature may not be applicable to MIMO-OFDM. Therefore, a new scheme is proposed to mitigate phase noise for MIMO-OFDM, which provides significant performance gains over systems without phase noise mitigation. This scheme provides a very simple structure and achieves adequate performance with high spectrum efficiency, which makes it very attractive for practical implementations

Uplink Performance of Time-Reversal MRC in Massive MIMO Systems Subject to Phase Noise

Multi-user multiple-input multiple-output (MU-MIMO) cellular systems with an excess of base station (BS) antennas (Massive MIMO) offer unprecedented multiplexing gains and radiated energy efficiency. Oscillator phase noise is introduced in the transmitter and receiver radio frequency chains and severely degrades the performance of communication systems. We study the effect of oscillator phase noise in frequency-selective Massive MIMO systems with imperfect channel state information (CSI). In particular, we consider two distinct operation modes, namely when the phase noise processes at the $M$ BS antennas are identical (synchronous operation) and when they are independent (non-synchronous operation). We analyze a linear and low-complexity time-reversal maximum-ratio combining (TR-MRC) reception strategy. For both operation modes we derive a lower bound on the sum-capacity and we compare their performance. Based on the derived achievable sum-rates, we show that with the proposed receive processing an $O(\sqrt{M})$ array gain is achievable. Due to the phase noise drift the estimated effective channel becomes progressively outdated. Therefore, phase noise effectively limits the length of the interval used for data transmission and the number of scheduled users. The derived achievable rates provide insights into the optimum choice of the data interval length and the number of scheduled users.Comment: 13 pages, 6 figures, 2 tables, IEEE Transactions on Wireless Communications (accepted

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

Effect of Synchronizing Coordinated Base Stations on Phase Noise Estimation

In this paper, we study the problem of oscillator phase noise (PN) estimation in coordinated multi-point (CoMP) transmission systems. Specifically, we investigate the effect of phase synchronization between coordinated base stations (BSs) on PN estimation at the user receiver (downlink channel). In this respect, the Bayesian Cram\'er-Rao bound for PN estimation is derived which is a function of the level of phase synchronization between the coordinated BSs. Results show that quality of BS synchronization has a significant effect on the PN estimation

Effect of multipath and antenna diversity in MIMO-OFDM systems with imperfect channel estimation and phase noise compensation

The effect of phase noise in multiple-input–multiple-output systems employing orthogonal frequency division multiplexing is analyzed in a realistic scenario where channel estimation is not perfect, and the phase noise effects are only partially compensated. In particular, the degradation in terms of SNR is derived and the effects of the receiver and channel parameters are considered, showing that the penalty is different for different receiver schemes. Moreover it depends on the channel characteristics and on the channel estimation error. An analytical expression is used to evaluate the residual inter-channel interference variance and therefore the degradation. The effects of multipath and antenna diversity are shown to be different for the two types of linear receivers considered, the zero-forcing scheme and the minimum mean squared error receiver.This work has been partly funded by projects “MACAWI” TEC2005-07477-C02-02 and “MULTI-ADAPTIVE” TEC2008-06327-C03-02.Publicad

Channel, Phase Noise, and Frequency Offset in OFDM Systems: Joint Estimation, Data Detection, and Hybrid Cramer-Rao Lower Bound

Oscillator phase noise (PHN) and carrier frequency offset (CFO) can adversely impact the performance of orthogonal frequency division multiplexing (OFDM) systems, since they can result in inter carrier interference and rotation of the signal constellation. In this paper, we propose an expectation conditional maximization (ECM) based algorithm for joint estimation of channel, PHN, and CFO in OFDM systems. We present the signal model for the estimation problem and derive the hybrid Cramer-Rao lower bound (HCRB) for the joint estimation problem. Next, we propose an iterative receiver based on an extended Kalman filter for joint data detection and PHN tracking. Numerical results show that, compared to existing algorithms, the performance of the proposed ECM-based estimator is closer to the derived HCRB and outperforms the existing estimation algorithms at moderate-to-high signal-to-noise ratio (SNR). In addition, the combined estimation algorithm and iterative receiver are more computationally efficient than existing algorithms and result in improved average uncoded and coded bit error rate (BER) performance