# Research on Co-Channel Interference Cancellation for Underwater Acoustic MIMO Communications
## 3 Experimental Results  
### Experimental Setting  
The experiment was conducted in Wuyuan Bay, Xiamen, China. The water depth was about 10 m, and two transmitters were suspended at the depth of 4 m and 6 m, respectively. A vertical receiving array, which consisted of 8 hydrophones, was fixed on a boat with a uniform space of 1 m, as shown in Figure 2a. The transmitters located in 4 m and 6 m are denoted as transmitter 1 and transmitter 2, respectively. The range between transmitters and receivers was approximately 1000 m. The average SNR was 29.3 dB. Figure 2b shows the sound speed profile; from this figure, one may observe that the sound speed varies within 1 m/s. There is an obvious mixed layer above 2.3 m, and the sound speed shows a slight positive distribution.  
The parameters of the communication system are shown in Table 2. The bandwidth was 3200 symbols/s, and the quadrature phase shift keying (QPSK) mapping method was used.  
In the following section, the proposed CE-DFE receiver will be compared with some CE-DFE-based receivers and a DA-DFE-based receiver. In Ref. [12], the equalizers were compared. The RLS-based DA-DFE and IPNLMS-based DA-DFE achieved the best communication performance. Therefore, in this paper, we utilize the two kinds of DA-DFEs as the benchmark. We define some abbreviations to better describe this.  
1. **RLS_DADFE**. The receiver can be found in [9]. The filters were obtained by recursive least square.
2. **IPNLMS_DADFE**. The receiver can be found in [12]. This is an improved normalized least mean square equalizer.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Value** \\ \hline Sampling frequency & 96,000 symbols/s \\ Bandwidth & 3200 symbols/s \\ Constellation Mapping & QPSK \\ \hline \hline \end{tabular}
\end{table}
Table 2: Parameters setting.  
Figure 2: The diagram of deployment and the sound speed. (**a**) The diagram of deployment. (**b**) The sound-speed profile.  
**CE_NoIC+DFE_NoIC**. Channel estimation used a traditional model [23] with no interference cancellation. Channel equalization used the traditional CE-DFE [30]; the CE-DFE does not have IC filters.
**CE_IC+DFE_NoIC**. Channel estimation used the proposed channel model, which has the ability to eliminate interference, but channel equalization does not.
**CE_IC+DFE_NoIC**. This is the opposite case to CE_IC+DFE_NoIC. The channel estimation used interference cancellation method, but channel equalization does not.
**CE_IC+DFE_IC**. This is the proposed receiver. Both channel estimation and channel equalization can eliminate interference.  
In this paper, we utilize the output SNR to evaluate the communication performance of different kinds of receivers. The output SNR is defined as  
\[\rho_{m}=10*\log_{10}\frac{||\mathbf{x}_{m}||_{2}^{2}}{||\mathbf{x}_{m}- \mathbf{x}_{s_{m}}||_{2}^{2}}\,, \tag{34}\]  
where \(\mathbf{x}_{m}\) is the transmitter symbols from the \(m\)-th transmitter, and \(\mathbf{x}_{s_{m}}\) is the soft output from the \(m\)-th DFE branch. The higher output SNR indicates a better communication performance.