Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/107239
Title: Transmit optimization with improper Gaussian signaling for interference channels
Authors: Zeng, Yong
Gunawan, Erry
Guan, Yong Liang
Zhang, Rui
Yetis, Cenk M.
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Issue Date: 2013
Source: Zeng, Y., Yetis, C. M., Gunawan, E., Guan, Y. L., & Zhang, R. (2013). Transmit Optimization With Improper Gaussian Signaling for Interference Channels. IEEE Transactions on Signal Processing, 61(11), 2899-2913.
Series/Report no.: IEEE transactions on signal processing
Abstract: This paper studies the achievable rates of Gaussian interference channels with additive white Gaussian noise (AWGN), when improper or circularly asymmetric complex Gaussian signaling is applied. For the Gaussian multiple-input multiple-output interference channel (MIMO-IC) with the interference treated as Gaussian noise, we show that the user's achievable rate can be expressed as a summation of the rate achievable by the conventional proper or circularly symmetric complex Gaussian signaling in terms of the users' transmit covariance matrices, and an additional term, which is a function of both the users' transmit covariance and pseudo-covariance matrices. The additional degrees of freedom in the pseudo-covariance matrix, which is conventionally set to be zero for the case of proper Gaussian signaling, provide an opportunity to further improve the achievable rates of Gaussian MIMO-ICs by employing improper Gaussian signaling. To this end, this paper proposes widely linear precoding, which efficiently maps proper information-bearing signals to improper transmitted signals at each transmitter for any given pair of transmit covariance and pseudo-covariance matrices. In particular, for the case of two-user Gaussian single-input single-output interference channel (SISO-IC), we propose a joint covariance and pseudo-covariance optimization algorithm with improper Gaussian signaling to achieve the Pareto-optimal rates. By utilizing the separable structure of the achievable rate expression, an alternative algorithm with separate covariance and pseudo-covariance optimization is also proposed, which guarantees the rate improvement over conventional proper Gaussian signaling.
URI: https://hdl.handle.net/10356/107239
http://hdl.handle.net/10220/17827
DOI: 10.1109/TSP.2013.2254480
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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