Sandesh Rao Mattu

In this paper, we present a novel low-complexity receiver that performs detection and channel estimation tasks in Zak-OTFS modulation using over-sampling in the delay-Doppler (DD) domain. Towards this, we partition the over-sampled signal into multiple two-dimensional (2D) blocks, which is equivalent to parallel branch conventional sampling of delay- and Doppler-shifted signals. This partitioning along with processing only a subset of the partitioned 2D blocks aids in reducing complexity. Specifically, in terms of detection, we propose a symbol-wise selection-based detection (SSD) algorithm which makes symbol-wise decisions based on selection among parallel branch outputs. While the partition based processing reduces complexity, the selection-based symbol decisions offer good performance. We also exploit the proposed partitioning for low-complexity path-wise estimation of the DD channel taps based on maximum energy across blocks. Simulation results with fractional DDs show that the proposed detection and channel estimation algorithms for Zak-OTFS achieve good performance at low complexity.

Orthogonal signaling or Nyquist signaling limits the number of information symbols transmitted in bandwidth $B$ and time $T$ to be $BT$, the time-bandwidth product. Transmitting more than $BT$ symbols leads to loss of orthogonality. The standard approach is to reduce the symbol interval and resolve the resulting inter-symbol interference. This requires changing the sampling frequency and possibly the sampling clock. This paper shows that it is possible to improve spectral efficiency on doubly spread channels without changing the sampling frequency. The idea is to superimpose the information symbols using mutually unbiased bases (MUB) while maintaining the original spacing. We carry this out in the delay-Doppler domain using Zak-transform based orthogonal time frequency space (Zak-OTFS) modulation as it allows construction of MUB. We also construct a precoder that mitigates the effect of the doubly-spread channel. This simplifies receiver processing to detection in Gaussian noise since each basis appears to the other as Gaussian noise. This reduction makes it possible to use trellis coded modulation to further improve the bit-error performance. Numerical results demonstrate that the proposed signaling scheme using MUB achieves good bit-error performance.

Zak-OTFS provides a framework for integrated sensing & communication (ISAC) in high delay and Doppler spread environments. Pulse shaping filter design enables joint optimization of sensing and communication performance. For sensing, a localized pulse shaping filter enables input-output (I/O) relation estimates close to the physical scattering channel. For communication, orthogonality of the pulse shape on the information lattice prevents inter-symbol interference, and no time and bandwidth expansion enables full spectral efficiency. A filter simultaneously meeting all three objectives is ideal for ISAC. Existing filter designs achieve two, but not all three objectives. In this work, we design pulse shaping filters meeting all three objectives via the Isotropic Orthogonal Transform Algorithm. The proposed filters have improved spectral efficiency, data detection and sensing performance over existing filter choices.

There is significant recent interest in designing new modulation schemes for doubly-selective channels with large delay and Doppler spreads, where legacy modulation schemes based on time-frequency signal representations underperform. Multiple modulation schemes, e.g., in the delay-Doppler, chirp, time-sequency, and other domains, have been proposed in the literature for this purpose, with varying implementation details. In this letter, we establish that all previously proposed modulation schemes for doubly-selective signaling are instances of a single family of complex Hadamard-modulated pulse trains. When the delay and Doppler spread of the doubly-selective channel is limited to a certain support, all modulation schemes in this waveform family offer equivalent, full diversity achieving performance with no symbol fading and low channel estimation overhead. The existence of this waveform family also enables flexible, multi-waveform co-existence – allowing a common transceiver architecture to generate multiple waveforms in the family, that may each be flexibly allocated to different users and services.

To meet the ever-increasing demand for higher data rates in mobile networks across generations, many novel schemes have been proposed in the standards. One such scheme is carrier aggregation (CA). Simply put, CA is a technique that allows mobile networks to combine multiple carriers to increase data rate and improve network efficiency. On the uplink, for power constrained users, this translates to the need for an efficient resource allocation scheme, where each user distributes its available power among its assigned uplink carriers. Choosing a good set of carriers and allocating appropriate power on the carriers is of paramount importance for good performance. Another factor that is critical to obtaining good performance is how well the degradation caused by the harmonic/intermodulation terms generated by the user’s transmitter non-linearities is handled. Specifically, for example, if the carrier allocation is such that a harmonic of a user’s uplink carrier falls on the downlink frequency of that user, it leads to a self coupling-induced sensitivity degradation of that user’s downlink receiver. Considering these factors, in this paper, we model the uplink carrier aggregation problem as an optimal resource allocation problem with the associated constraints of non-linearities induced self interference (SI). This involves optimization over a discrete variable (which carriers need to be turned on) and a continuous variable (what power needs to be allocated on the selected carriers) in dynamic environments, a problem which is hard to solve using traditional methods owing to the mixed nature of the optimization variables and the additional need to consider the SI constraint in the problem. Therefore, in this paper, we adopt a reinforcement learning (RL) framework involving a compound-action actor-critic (CA2C) algorithm for the uplink carrier aggregation problem. We propose a novel reward function that is critical for enabling the proposed CA2C algorithm to efficiently handle SI. The CA2C algorithm along with the proposed reward function learns to assign and activate suitable carriers in an online fashion. Numerical results demonstrate that the proposed RL based scheme is able to achieve higher sum throughputs compared to naive schemes. The results also demonstrate that the proposed reward function allows the CA2C algorithm to adapt the optimization both in the presence and absence of SI.

Polarimetry, which is the ability to measure the scattering response of the environment across orthogonal polarizations, is fundamental to enhancing wireless communication and radar system performance. In this paper, we utilize the Zak-OTFS modulation to enable instantaneous polarimetry within a single transmission frame. We transmit a Zak-OTFS carrier waveform and a spread carrier waveform mutually unbiased to it simultaneously over orthogonal polarizations. The mutual unbiasedness of the two waveforms enables the receiver to estimate the full polarimetric response of the scattering environment from a single received frame. Unlike existing methods for instantaneous polarimetry with computational complexity quadratic in the time-bandwidth product, the proposed method enables instantaneous polarimetry at near-linear complexity in the time-bandwidth product. Via numerical simulations, we show ideal polarimetric target detection and parameter estimation results with the proposed method, with improvements in computational complexity and greater clutter resilience over comparable baselines.

Zak-transform based orthogonal time frequency space (Zak-OTFS) is a delay-Doppler (DD) domain modulation scheme in which the signal processing is carried out in the DD domain. The channel when viewed in the DD domain is predictable. However, even with Zak-OTFS, pilots need to be sent periodically, albeit at a lower rate. In this paper, we propose a differential communication scheme for Zak-OTFS systems that alleviates the need for periodic pilot transmission. Towards this, we analytically show that the detected data can be used as a pilot and that the channel estimate obtained from the detected data can enable further detection enabling the “differential” aspect of the communication. Specifically, we leverage the prediction capability of the DD channel in Zak-OTFS to use the channel estimate (obtained from detected data symbols treated as pilots) in the previous instant to detect data in the next instant and propagate this forward. The advantages are two fold. First, it allows the data symbols to enjoy higher energy since the energy that would otherwise be required for pilot symbols can also be allocated to data symbols. Second, it allows for full spectral efficiency compared to point or embedded pilots. Comparison with the full spectral efficiency achieving spread pilot scheme shows that the proposed method achieves better bit-error rate at lower complexity.