In wireless communication systems, nonlinearity is the root cause of many undesired effects. In order to compensate these effects, the nonlinearity must be estimated accurately. This article deals with nonlinearity estimation methods and especially focuses on sequences that are optimized for that purpose. Based on the Cramér-Rao bound of the nonlinearity estimator, we derive an objective function for sequence optimization. An algorithm is proposed to solve this optimization problem while satisfying constraints on the sequence format to produce sequences that are compatible to current wireless LAN standards. The obtained sequences are thoroughly analyzed and compared against sequences defined in IEEE 802.11ax. Their superiority confirms that dedicated sequences for nonlinearity estimation are valuable in future communication standards. Moreover, we provide an analysis of estimation error components to show that an optimal number of estimated polynomial coefficients can be found that minimizes estimation error. To further show the benefits of optimized sequences in the context of an application, a method for digital nonlinear self-interference cancellation suited for frequency-division duplex systems is proposed and evaluated. With that, we demonstrate that cancellation performance is significantly enhanced using optimized estimation sequences.

Nonlinear characteristics in a wireless transmitter can cause various undesired effects like spectral regrowth or signal quality degradation. To compensate these effects, e.g., via digital predistortion, an accurate estimation of the nonlinear characteristic is required. This work focuses on methods and sequences that allow accurate and robust estimation of a non-linearity. Based on the Cramér- Rao bound of the nonlinearity estimator, we derive an objective function for sequence optimization. An algorithm is proposed to solve this optimization problem while satisfying constraints on the sequence format to obtain sequences that are compatible to current wireless LAN standards. The performance of the optimized sequences is evaluated using a power amplifier measurement. Results show that the optimized sequences are superior to conventional estimation sequences defined in the IEEE 802.11ax standard. Thus, dedicated sequences for nonlinearity estimation should be considered in future communication standards. Moreover, we show that depending on the noise power an optimal number of estimated polynomial coefficients can be found that minimizes estimation error.

We consider a frequency division duplex (FDD) scheme in which two wireless communication devices simultaneously transmit and receive on adjacent channels. Inevitable out-of-band (OOB) emissions caused by the transmission on one channel induce self-interference on the adjacent channel. As a result, receiver sensitivity severely degrades by self-interference from the transmitter of the same device. Therefore, we propose a novel self-interference cancellation (SIC) method, that has a lower complexity compared to existing approaches. It comprises digital linear SIC in frequency domain and power amplifier backoff adaption to mitigate both linear and nonlinear components. We further present and evaluate an OOB emission model of a transmitter which is subsequently used to analyze the performance of the proposed SIC method. Our simulation results highlight capabilities and limitations of the proposed SIC method in different scenarios. It turns out that the proposed method can significantly reduce the error vector magnitude of a received signal in FDD operation. Prerequisites of the cancellation method and impact to protocol design are thoroughly discussed.