Non-adaptive methods for Dimension Reduction in Dispersive and Noncoherent Communication Channels

Abstract

The signal- and information-theoretic principles of communication under dispersive and non-coherent conditions is of great importance for the optimal design of future communication systems. Many newly proposed system setups have to operate on parameter sets with exponentially increasing dimension. Therein are exemplary: cooperating transmitters with multiple antennas, cognitive radio systems operating at large bandwidth, signal aggregiation in non–orthogonal multiuser scenarious and sensor networks. Conventional communication usually uses complex methods for estimation and coordination of this large number of system parameters. This includes synchronization, channel estimation and prediction, resource allocation and - increasingly important for cellular radio networks - routing in the backbone network. Just before transmitting any bit of user data this conventional procedure requires a substantial amount of communication and signal processing resources in a network - at the terminals, on the feedback channel, in intermediate communication between the several controlling and transmitter units and in the backbone network.

On the other hand, in an increasing number of applications the typical user traffic consists only of short messages like status updates. Thus, there is the paradox situation, that the control overhead for these complex communication systems is of the same and higer order as the intended exchange of the original information. Due to the increasing use of smartphones, the relevance of mobile machine to machine communication and wireless sensor networks, an even more exacerbation has to be expected in future. A solution to this problem could be the use of non–coherent strategies and new non-adaptive compression methods for the feedback channel with both having possibly random nature. Although these approaches are known for a long time in signal- and information theory, a new combined theory is necessary here which explicitely accounts for parameter sets of reduced complexity but in large dimension and the short message type of user data. The goal of this research project is to contribute here in estimation and detection theory and signal processing. Scaling results and algorithmic methods should be established in the project for situations where the overall set of communication parameters is essentially sparse and of low rank type, i.e. has in general a low-dimensional compressible structure in large dimension.

Related Publications

1. Yunyan Chang, Peter Jung, Chan Zhou and S.ławomir Staʼnczak, “Distributed ranking-based resource allocation for sporadic M2M communication,” EURASIP Journal on Wireless Communications and Networking, vol. 2022, no. 1, pp. 83, sep 2022.
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   @article{Yunyan:eurasip2022,
     author = {Chang, Yunyan and Jung, Peter and Zhou, Chan and Staʼnczak, S.ławomir},
     title = {Distributed ranking-based resource allocation for sporadic M2M communication},
     journal = {EURASIP Journal on Wireless Communications and Networking},
     year = {2022},
     volume = {2022},
     number = {1},
     pages = {83},
     url = {https://jwcn-eurasipjournals.springeropen.com/articles/10.1186/s13638-022-02144-0},
     doi = {https://doi.org/10.1186/s13638-022-02144-0}
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4. G. Cao, P. Jung, S. Stanczak and F. Yu, “Data Aggregation and Recovery in Wireless Sensor Networks Using Compressed Sensing,” International Journal of Sensor Networks (IJSNet), vol. 22, no. 4, pp. 209-219, 2016.
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5. Yunyang Chang, Peter Jung, Chan Zhou and Slawomir Stanczak, “Block Compressed Sensing Based Distributed Device Detection for M2M Communications,” pp. 1-27, sep 2016.
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6. Yunyang Chang, P. Jung, Chan Zhou and S. Stanczak, “Block Compressed Sensing based Distributed Resource Allocation for M2M Communications,” International Conference on Acoustics, Speech, and Signal Processing, ICASSP16, 2016.
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   @article{Yunyan:icassp16,
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7. Philipp Walk, Henning Becker and Peter Jung, “OFDM channel estimation via phase retrieval,” in Conference Record - Asilomar Conference on Signals, Systems and Computers, vol. 2016-Febru, pp. 1161-1168, 2016.
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   @inproceedings{Walk:asilomar15,
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9. D. Wieruch, P. Jung, T. Wirth and A. Dekorsky, “Identifying Non-Adjacent Multiuser Allocations by Joint l1-Minimisation,” in 2016 IEEE Wireless Communications and Networking Conference (WCNC), 2016.
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10. Dennis Wieruch, Peter Jung, Thomas Wirth, Armin Dekorsy and Thomas Haustein, “Cognitive Radios Exploiting Gray Spaces via Compressed Sensing,” Frequenz, vol. 70, no. 7-8, pp. 289-300, jan 2016.
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    @inproceedings{Wieruch:asilomar2015,
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    @inproceedings{Wieruch2013,
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    }