# Interference Alignment for Cognitive Radio Communications and Networks: A Survey
## 3 Interference Alignment in Cognitive Radio: First Paradigm
### Techniques For IA in CR Networks
#### 3.2.5 Other Endeavours  
There are also other research endeavours that do not fall within the confines of the more general IA techniques, but are equally significant and obviously worth mentioning. One of such endeavours is the work done in ref. [101], which researches a unique underlay MIMO CR system, in which the geometric or immediate CSI to the PU-Rx of the interfering channels is totally unknown to the CR. This paper initially shows that minimal ranked CR interference is desirable for increasing the efficiency of the PUs in comparison to spreading a lesser amount of power over additional transmit signal dimensions, followed by a water-filling solution (most of which will be discussed in the second IA in CR paradigm) that uses a negligible sum of power to attain the rate limitation with a low-rank transfer of covariance matrix. A combination of a rank minimization, CR transmission strategy as well as an analysis of the interference temperature at the PU-Rx is presented, the results showing higher PU sum rates with a trade-off of higher interference temperature compared with the likes of say refs. [101; 102]. Of more significance is the work done in ref. [103], which successfully applies IA in a practical network setting, leading to a dramatic reduction in message transmission times. By using a vehicular traffic scenario, this work successfully analyzes optimal times to undertake local spectrum sensing and how to ensure correct packet receptions among the multiple base stations (BS) and CR vehicles.  
Inadvertently, the sum rates of the SUs in a CR networks fall short particularly in low SNR conditions. The work in ref. [104] in order to further improve its performance considered power distribution in IA-based CR networks. While each SU is trying to decode its own signal by choosing appropriate transmit precoder and interference receiving matrices, three separate PA algorithms are proposed to also increase the energy efficiency, throughput of the SUs, as well as the requirements of SUs of the system, while maintaining the goal of maintaining an adequate interference level to the PU within the specified limit. As for the PU, a transmission-mode adaptation (TMA) scheme is proposed to further improve its performance to cater for low SNR conditions. The combined PA and TMA algorithms show the effectiveness of these algorithms for IA-based CR networks. Another performance metric that usually falls short of theoretical expectation is the signal-to-interference-plus-noise ratio (SINR) of the desired signal. To improve this situation, the work in ref. [105] proposed an IA scheme based on antenna selection (AS). In the proposed scheme, multiple antennas at each SU-Rx are selected to achieve optimal performance. Furthermore a CSI filtering scheme is proposed to counter the effects of imperfect CSI. Given the huge computational complexity of the IA-AS scheme, an optimization algorithm is introduced that can simultaneously converge with the precoding matrices to improve performance.