  This paper focuses on designing robust symbol-level precoding (SLP) in an
overlay cognitive radio (CR) network, where the primary and secondary networks
transmit signals concurrently. When the primary base station (PBS) shares data
and perfect channel state information (CSI) with the cognitive base station
(CBS), we derive an SLP approach that minimizes the CR transmission power and
satisfies symbol-wise Safety Margin (SM) constraints of both primary users
(PUs) and cognitive users (CUs). The resulting optimization has a quadratic
objective and linear inequality (LI) constraints, which can be solved by
standard convex methods. For the case of imperfect CSI from the PBS, we propose
robust SLP schemes. First, with a norm-bounded CSI error model to approximate
the uncertain channels, we adopt a max-min philosophy to conservatively achieve
robust SLP constraints. Second, we use the additive quantization noise model
(AQNM) to describe the quantized PBS CSI and employ a stochastic constraint to
formulate the problem. Both robust approaches also result in a quadratic
objective with LI constraints. Simulation results show that, rather than simply
trying to eliminate the network's cross-interference, the proposed robust SLP
schemes enable the primary and secondary networks to aid each other in meeting
their quality of service constraints.
