Abstract
Self-interference occurs when there is electromagnetic coupling between the transmission and reception of the same node; thus, degrading the RX sensitivity to incoming signals. In this paper we present a low-complexity technique for self-interference cancellation in multiple carrier multiple access systems employing whole band direct to digital sampling. In this scenario, multiple users are simultaneously received and transmitted by the system at overlapping arbitrary bandwidths and powers. Traditional algorithms for self-interference mitigation based on recursive least squares (RLS) or least mean squares (LMS), fail to provide sufficient rejection, since the incoming signal is far from being spectrally flat, which is critical for their performance. The proposed algorithm mitigates the interference by modeling the incoming multiple user signal as an autoregressive (AR) process and jointly estimates the AR parameters and self-interference. The resulting algorithm can be implemented using a low-complexity architecture comprised of only two RLS modules. The novel algorithm further satisfies low latency constraints and is adaptive, supporting time varying channel conditions. We compare this to many self-interference cancellation algorithms, mostly adopted from the acoustic echo cancellation literature, and show significant performance gain.
Highlights
Received: 29 November 2021Future multiple access systems, supporting heterogeneous services and applications, such as virtual reality (VR), augmented reality, holographic telepresence, industry 4.0, and robotics, will have to accommodate multiple users in different resource blocks, such as time slots, frequency bands, spreading codes, and power levels
These systems have to go to higher bandwidth efficiencies and higher connectivities compared to conventional multiple access schemes
A novel algorithm for mitigating self-interference in full duplex communication systems was presented. This algorithm is capable of mitigating self-interference in multiple access systems, where multiple users are simultaneously received and transmitted at overlapping arbitrary bandwidths and powers
Summary
Future multiple access systems, supporting heterogeneous services and applications, such as virtual reality (VR), augmented reality, holographic telepresence, industry 4.0, and robotics, will have to accommodate multiple users in different resource blocks, such as time slots, frequency bands, spreading codes, and power levels. Digital signal processing algorithms counter the residual noise by estimating the leakage filter and removing its interference on the UL. In the full duplex literature, estimation of the leakage filter is traditionally based on least squares (LS) techniques [9] While these techniques are adequate for simple narrow band problems, they perform poorly for wide band systems in complex scenarios, which will be demonstrated in this paper. The far-end signal, can be viewed as the DL leakage signal while the near-end signal as the UL signal from users; the double-talk scenario is basically equivalent to the self-interference scenario This problem has been extensively studied and there are a variety of techniques for echo cancellation that can be applied to our setting. A proof for convergence of the algorithm is provided
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