Synchronization and Channel Estimation of OTFS with RF Impairments

Orthogonal Time Frequency Space (OTFS) modulation is a promising waveform for future wireless networks. However, its resilience to RF impairments remains relatively understudied. Low-cost RF front ends are crucial for next-generation wireless systems, yet their performance is often degraded by RF impairments such as transmit IQ imbalance (IQI), phase noise (PN), timing offset (TO), and carrier frequency offset (CFO). Hence, this paper addresses the estimation and compensation of these RF impairments in OTFS systems under high mobility. A unified system model is developed that incorporates TO, CFO, PN, IQI and other channel effects into an effective channel representation. Using the pilot with cyclic prefix (PCP), a low-peak to average power ratio (PAPR) pilot suitable for OTFS, we propose a pilot-aided synchronization and estimation framework. The dual periodicity of PCP is exploited in our proposed TO estimation technique. A maximum-likelihood-based technique is also proposed to jointly estimate the CFO and effective channel using a complex exponential basis expansion model (CE-BEM). Finally, a linear detection model is formulated in the delay-Doppler domain to mitigate residual interference caused by RF impairments. Our simulation results corroborate the efficacy of our proposed synchronization and channel estimation techniques.

Joint Phase Noise and Channel Estimation for OTFS

This paper investigates the effect of oscillator phase noise in orthogonal time frequency space (OTFS) systems. The paper provides in-depth analysis of the interference due to phase noise in the delay-Doppler domain and derives expressions for SINR for three different oscillator types, namely free-running oscillators, continuous-time phase locked loops (PLLs) and discrete-time PLLs. The analysis demonstrates the OTFS is sensitive to phase noise and requires appropriate estimation and compensation. In particular, the analysis shows phase noise imposed inter-Doppler-interference (IDI) is severe and that existing phase noise estimation techniques which only consider the common-phase-error (CPE) can not compensate this IDI effectively. Additionally, the existing methods in the OTFS literature on phase noise assume the channel to be a known single tap channel. Hence, in this paper, we propose a method for joint channel and phase noise estimation using a Wiener filtering approach. Our proposed method exploits the statistical nature of both the phase noise and the Doppler spread channel. Our numerical results demonstrate the superior performance of our proposed technique, with gains of up to 8~dB in terms of bit error rate (BER) over existing methods in the literature.

Comparison of OTFS and OFDM for RIS-aided Systems in the Presence of Phase Noise

In this paper, we investigate the performance of RIS-aided orthogonal time frequency space (OTFS) and orthogonal frequency division multiplexing (OFDM) systems in the presence of oscillator phase noise. OFDM is known to be sensitive to phase noise, which could limit the potential gains promised by RIS systems. OTFS, on the other hand, is a compelling potential waveform for RIS-aided systems in the presence of phase noise due to it's resilience to time-varying channels. However, the effect of phase noise on OTFS has not been fully analyzed in the literature as of yet. Additionally, no existing works in the literature consider the effect of phase noise on an RIS-aided OTFS system. Hence, we propose a joint RIS channel and phase noise estimation technique using a Wiener filtering approach. Our proposed method exploits the statistical nature of both the phase noise and the Doppler spread channel in a setup with RIS. Our numerical analysis demonstrates the significant gain of RIS-aided OTFS offers compared to RIS-aided OFDM in the presence in the presence of phase noise. Additionally, our results demonstrate the superiority of our proposed estimation technique, with gains of up to 3~dB in terms of bit error rate (BER), over existing methods in the literature.

Truncated Turbo Equalizer with SIC for OTFS

Orthogonal time frequency space (OTFS) is a promising candidate waveform for the next generation wireless communication systems. OTFS places data in the delay-Doppler (DD) domain, which simplifies channel estimation in highmobility scenarios. However, due to the 2-D convolution effect of the time-varying channel in the DD domain, equalization is still a challenge for OTFS. Existing equalizers for OTFS are either highly complex or they do not consider intercarrier interference present in high-mobility scenarios. Hence, in this paper, we propose a novel two-stage detection technique for coded OTFS systems. Our proposed detector brings orders of magnitude computational complexity reduction compared to existing methods. At the first stage, it truncates the channel by considering only the significant coefficients along the Doppler dimension and performs turbo equalization. To reduce the computational load of the turbo equalizer, our proposed method deploys the modified LSQR (mLSQR) algorithm. At the second stage, with only two successive interference cancellation (SIC) iterations, our proposed detector removes the residual interference caused by channel truncation. To evaluate the performance of our proposed truncated turbo equalizer with SIC (TTE-SIC), we set the minimum mean squared error (MMSE) equalizer without channel truncation as a benchmark. Our simulation results show that the proposed TTE-SIC technique achieves about the same bit error rate (BER) performance as the benchmark.

Low-Complexity Reliability-Based Equalization and Detection for OTFS-NOMA

Orthogonal time frequency space (OTFS) modulation has recently emerged as a potential 6G candidate waveform which provides improved performance in high-mobility scenarios. In this paper we investigate the combination of OTFS with non-orthogonal multiple access (NOMA). Existing equalization and detection methods for OTFS-NOMA, such as minimum-mean-squared error with successive interference cancellation (MMSE-SIC), suffer from poor performance. Additionally, existing iterative methods for single-user OTFS based on low-complexity iterative least-squares solvers are not directly applicable to the NOMA scenario due to the presence of multi-user interference (MUI). Motivated by this, in this paper we propose a low-complexity method for equalization and detection for OTFS-NOMA. The proposed method uses a novel reliability zone (RZ) detection scheme which estimates the reliable symbols of the users and then uses interference cancellation to remove MUI. The thresholds for the RZ detector are optimized in a greedy manner to further improve detection performance. In order to optimize these thresholds, we modify the least squares with QR-factorization (LSQR) algorithm used for channel equalization to compute the the post-equalization mean-squared error (MSE), and track the evolution of this MSE throughout the iterative detection process. Numerical results demonstrate the superiority of the proposed equalization and detection technique to the existing MMSE-SIC benchmark in terms of symbol error rate (SER).

Low-Complexity Equalization and Detection for OTFS-NOMA

Orthogonal time frequency space (OTFS) modulation has recently emerged as a potential 6G candidate waveform which provides improved performance in high-mobility scenarios. In this paper we investigate the combination of OTFS with non-orthogonal multiple access (NOMA). Existing equalization and detection methods for OTFS-NOMA, such as minimum-mean-squared error with successive interference cancellation (MMSE-SIC), suffer from poor performance. Additionally, existing iterative methods for single-user OTFS based on low-complexity iterative least-squares solvers are not directly applicable to the NOMA scenario due to the presence of multi-user interference (MUI). Motivated by this, in this paper we propose a low-complexity method for equalization and detection for OTFS-NOMA. Our proposed method uses an iterative process where in each iteration, an equalizer based on the least-squares with QR factorization (LSQR) algorithm is followed by a novel reliability zone (RZ) detection scheme which estimates the reliable symbols of the users and then uses interference cancellation to remove MUI. We present numerical results which demonstrate the superiority of our proposed method, in terms of symbol error rate (SER), to the existing MMSE-SIC benchmark scheme. Additionally, we present results which illustrate that a judicious choice of RZ thresholds is important for optimizing the performance of the proposed algorithm.

Resource Allocation for Mixed Numerology NOMA

6G wireless networks will require the flexibility to accommodate an extremely diverse set of service types. This necessitates the use of mixed numerologies to accommodate different quality of service (QoS) requirements. Non-orthogonal multiple access (NOMA) techniques can potentially be used to accommodate users with different numerologies while also gaining the performance benefits associated with NOMA. To achieve the full performance benefits of a mixed numerology NOMA (MN-NOMA) system, resource allocation among the users is paramount. However, the coexistence of mixed numerologies changes the nature of the interference that each user experiences. This means that techniques used in single-numerology NOMA (SN-NOMA) are no longer sufficient. In light of this, we approach the problem of optimizing subcarrier and power allocation for maximizing the spectral efficiency of MN-NOMA while considering a minimum rate constraint for each user. In this letter, we propose a two-stage sub-optimal approach to solve the problem. We present numerical results which show the superiority of our proposed method over existing benchmark schemes in both spectral efficiency and fairness.