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OTFS Matlab Codes – Orthogonal Time Frequency Space Modulation

75 £

The OTFS codes provided in this product allow you to study the OTFS modulation’s performance and extend its functionality to different scenarios and use cases by building on the top of the provided codes.

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Description

The OTFS codes provided in this product allow you to study the OTFS modulation’s performance and extend its functionality to different scenarios and use cases by building on the top of the provided codes.

 

The 5G air interface and associated modulation have to support a number of diverse requirements and use cases (e.g.,
eMBB, high-speed use case, mMTC, etc.) as detailed in many publications.
The associated modulation waveform would then have to exhibit high performance in many diverse scenarios of high or
low Doppler, delay spread, carrier frequency, etc. This is possible if the modulation scheme takes full advantage of the
fading multipath nature of the channel and extracts the full diversity present in the channel in all dimensions of time,
frequency, and space. Such a flexible waveform can serve as an integral part of a flexible air interface and associated
core network.
Therefore, researchers have recently introduced a novel modulation technique called Orthogonal Time
Frequency Space (OTFS). It has been shown recently that OTFS arises as a well-suited modulation for the time and
frequency selective fading channel. OTFS characterizes the Doppler induced time-varying nature of the wireless
channel and parameterizes it as a 2D impulse response in the delay-Doppler domain. 

In addition to the OTFS diversity gains
mentioned above, we have additional benefits of low reference signal overhead and enhanced CSI quality and MIMO
performance.
There are many areas where an OTFS-inspired air interface design can provide benefits to 5G systems. It’s found that OTFS has two main advantages:  i) the ability to extract the channel capacity and exploit its diversity with
reasonable complexity as the number of antennas grows and ii) the ability to design reference signal schemes that
multiplex a large number of antenna ports in a dedicated (“pilot”) subgrid of the time-frequency plane.

The performance results of OTFS show significant performance gains over OFDM for multiple configurations.
In a nutshell, the OTFS modulation establishes a novel coordinate system to reveal the geometry of the wireless
channel. OTFS augments the existing channel model by adding a second dimension representing the Doppler
characteristics of each reflective path. In this regard, OTFS captures the exact behavior of the wireless multipath
medium in a concise two-dimensional physical representation that is stable and slowly varying compared to the
channel’s time and frequency variations. OTFS converts the time-varying impulse response to a time-independent 2D
convolution operation for the duration of the TTI, governed by the geometry (aka location, relative velocity, and angle
of arrival) of the physical objects in the propagation path. In this way, every symbol experiences the full diversity of the
channel. Due to its precise, efficient delay-Doppler channel representation, OTFS allows the acquisition of the exact
coupling between a large number of antennas in the network, setting the ground for beamforming, null steering, and
scaling with the MIMO order and the number of devices.

In summary, the delay-Doppler domain provides a novel view of the effects of the wireless channel and points to significant benefits
when modulating information symbols in that domain. In particular, the wireless fading channel response becomes a
two-dimensional time-invariant convolution response. All QAM symbols see the same static channel response
throughout the transmission interval and extract the maximum diversity of the channel in both the time and frequency
dimensions. Significant performance improvements are seen for various MIMO configurations in high Doppler
scenarios.
The delay-Doppler domain is also suitable for designing RS sequences for multiplexing a large number of antenna ports
with reduced RS overhead. This can result in significant RS overhead improvements for massive MIMO systems.

 

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