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Current cellular systems use pilot-aided statistical channel state information (S-CSI) estimation and limited feedback schemes to aid in link adaptation and scheduling decisions. However, in the presence of pulsed radar signals, pilot-aided S-CSI is inaccurate since interference statistics on pilot and nonpilot resources can be different. Moreover, the channel will be bimodal as a result of the periodic interference. In this paper, we propose a max-min heuristic to estimate the post-equalizer SINR in the case of non-pilot pulsed radar interference, and characterize its distribution as a function of noise variance and interference power. We observe that the proposed heuristic incurs low computational complexity, and is robust beyond a certain SINR threshold for different modulation schemes, especially for QPSK. This enables us to develop a comprehensive semi-blind framework to estimate the wideband SINR metric that is commonly used for S-CSI quantization in 3GPP Long-Term Evolution (LTE) and New Radio (NR) networks. Finally, we propose dual CSI feedback for practical radar-cellular spectrum sharing, to enable accurate CSI acquisition in the bimodal channel. We demonstrate significant improvements in throughput, block error rate and retransmission-induced latency for LTE-Advanced Pro when compared to conventional pilot-aided S-CSI estimation and limited feedback schemes.
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Radio Frequency Interference Excision Using Cyclostationary Signal Processing
A cyclostationary process is one whose autocorrelation function is periodic or nearly periodic. The modulation schemes used to encode information give rise to cyclostationarity in many human-generated sources of interference. In contrast, nearly all astrophysical signals are expected to be wide-sense stationary on timescales of interest, making cyclostationarity a potentially robust way of discriminating between interference and astronomical sources. We are developing an algorithm that employs a well-known method of detecting cyclostationary signals and testing its efficacy against a suite of simulated interference covering a wide range of modulation schemes. We present receiver operating characteristic curves and binary classification scores for different types of interfering signals. Our algorithm performs well for many modulation schemes, with F1 and φ coefficient scores in excess of 0.9 in some cases, though it shows weaknesses in the case of frequency modulation. We also apply our algorithm to archived Robert C. Byrd Green Bank Telescope observations of a bright millisecond pulsar. We use standard pipelines for blindly detecting and timing pulsars and preliminarily find improvement in data quality according to several metrics, though some undesirable effects are still present. We also show that our algorithm has no negative impact when detecting Galactic HI emission. We thus believe that cyclostationary signal processing shows promise as a means of interference mitigation and discuss opportunities and challenges for employing it more widely.
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- Award ID(s):
- 1910302
- PAR ID:
- 10409303
- Date Published:
- Journal Name:
- The RFI2022 Workshop at ECMWF
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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