Peak power minimization in symbol-level precoding for cognitive MISO downlink channels

Abstract

This paper proposes a new symbol-level precoding scheme at the cognitive transmitter that jointly utilizes the data and channel information to reduce the effect of nonlinear amplifiers, by reducing the maximum antenna power under quality of service constraint at the cognitive receivers. In practice, each transmit antenna has a separate amplifier with individual characteristics. In the proposed approach, the precoding design is optimized in order to control the instantaneous power transmitted by the antennas, and more specifically to limit the power peaks, while guaranteeing some specific target signal-to-noise ratios at the receivers and respecting the interference temperature constraint imposed by the primary system. Numerical results show the effectiveness of the proposed scheme, which outperforms the existing state of the art techniques in terms of reduction of the power peaks.

Symbol-Level and Multicast Precoding for Multiuser Multiantenna Downlink: A State-of-the-Art, Classification, and Challenges

“…The relation to physical-layer multicasting is established for any modulation in [109]. A per-antenna consideration is thoroughly discussed in [110]- [111]. In [111], novel strategies based on the minimization of the power peaks amongst the transmitting antennas and the reduction of the instantaneous power imbalances across the different transmitted streams is investigated.…”

“…The applications of symbol-level precoding span different research areas in wireless communications: underlay cognitive radio system [99], [101], [103], [110], coordinated multicell MIMO systems [115], physical-layer security [95], [96], [128], [129] and simultaneous wireless information and power transfer(SWIPT) [130]. For more details about the applications of symbol-level precoding, please look at Table II. Finally, symbol-leevel precoding and directional modulation is conceptually the same with the following main differences: directional modulation is driven by implementational aspects, assuming an analogue architecture with less emphasis on formulating criteria that optimizes the actual precoding weights.…”

Symbol-Level Precoding for the Nonlinear Multiuser MISO Downlink Channel

“…The properties (18) and (19) come straightforwardly from (14). In order to prove (20) and 21, we derive hereafter the gradient of f (x) andf (x, z) with respect to x and x * , based on [39]:…”

“…The main novelty of the proposed techniques with respect to the state of the art on symbol-level precoding [7]- [13] is their ability to exploit the potential of the symbol-level design for producing more robust waveforms to the harmful effects of non-linear channels. It should be noted that a symbol-level precoding scheme accounting for the channel non-linearities has already been proposed by the authors in [19], [20]. Nevertheless, the scheme therein proposed performs just a peak power minimization, without imposing any lower bound nor optimizing the SPAPR.…”

“…On the other hand, the techniques proposed herein directly aim at a reduction of the power imbalances across the different antennas, therefore they are able to tackle the problem of differential phase shift and to achieve enhanced performance. The scheme of [19], [20] is considered as a benchmark in the numerical evaluation of the proposed techniques, in Section V-C, in order to quantify the relative gains.…”