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    Weighted sum rate maximization for cognitive MISO broadcast channel: Large system analysis


    He, Yuanyuan and Dey, Subhrakanti (2013) Weighted sum rate maximization for cognitive MISO broadcast channel: Large system analysis. In: 2013 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, pp. 4873-4877. ISBN 9781479903566

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    Abstract

    This paper considers the ergodic weighted sum rate (WSR) maximization problem for an underlay cognitive radio MISO broadcast channel, where a secondary network, consisting of a base-station with M transmit antennas and K single-antenna secondary users (SUs), is allowed to share the same spectrum with a primary user (PU), under an average transmit sum power (ATTP) constraint P av and an average interference power (AIP) constraint on the PU. We show that the ATTP constraint is always active, and as P av → ∞, the ergodic WSR approaches infinity similar to the conventional non-CR network case. A low-complexity suboptimal beamforming scheme (called partially-projected regularized zero-forcing beamforming `PP-RZFBF') with a closed-form beamformer is proposed. Due to the non-convexity of PP-RZFBF scheme, a large system analysis is conducted in the limit as M and K approach infinity with a fixed finite ratio r = K/M. We derive deterministic limiting approximations for the PP-RZFBF problem which enables us to determine asymptotically optimal beamformers for PP-RZFBF. Numerical simulations illustrate that the asymptotically optimal beamformers turn out to be quite effective even for small M, K.

    Item Type: Book Section
    Additional Information: Cite as: Y. He and S. Dey, "Weighted sum rate maximization for cognitive MISO broadcast channel: Large system analysis," 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013, pp. 4873-4877, doi: 10.1109/ICASSP.2013.6638587.
    Keywords: Weighted sum rate; maximization; cognitive; MISO broadcast channel; Large system analysis;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 14504
    Identification Number: https://doi.org/10.1109/ICASSP.2013.6638587
    Depositing User: Subhrakanti Dey
    Date Deposited: 03 Jun 2021 14:51
    Publisher: IEEE
    Refereed: Yes
    URI:

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