*4.2.2. Scenario 2: MU-MIMO with Multi Cell Processing (MCP)*

**Figure 6.** Shows The Compression of The Un-coded BER Performance for PA-SLNR-FKT, SLNR-GSVD and SLNR-GEVD

**Figure 7.** Shows The Comparison of The Output SINR Outage Performance of The PA-SLNR-FKT, SLNR-GSVD and

SLNR-GEVD Precoding Methods Under System Configuration of *B* =3, *Mk* =4, *NT* =12, and 2 dB Input SNR.

Precoding Methods Under System Configuration of *B* =3, *Mk* =4, *NT* =14, 4QAM Modulated Signal.

24 Selected Topics in WiMAX

To appreciate the importance of precoding to cancel inter-cell interference in the MCP configuration, geometrically we consider three cooperating BSs as illustrated in figure 9. Basically we consider micro-cellular setup of BS to BS distance equal to 1000 m. As shown in figure 9. we also consider a simplified as well as an extreme case where there are three users at the edges of the three cooperating cells, so that we just allow each user to uniformly position within the last 50 m of its anchor BS. In each transmission, a WiMAX standard channel model is used. Thus each entry of the *kth* user MIMO channel matrix is generated according to prespecified wireless communication channel model which include mean path loss, shadowing and slow fading discrete components as follows.

$$\mathbf{H}\_e^k = (\phi\_1 \phi\_2)^{1/2} \mathbf{\ddot{H}}\_e^k \tag{45}$$

where **H ↔** *e <sup>k</sup>* ∈**C** *NRk* <sup>×</sup>*NT <sup>e</sup>* represent the fast fading channel discrete component between the *kth* user and the *eth* BS and in this system simulation we use the WiMAX discrete channel values as given in [72] and *ϕ*1 denotes the channel path loss component while *ϕ*2 is the lognormal shadowing fadingcomponent.Ineachstepofsimulationfixedleastsquarefilterisusedtodecodethereceived data and unless specified otherwise, the following values listed in table 2. are used.

we also consider the case of no cooperation denoted as NO-MCP. The simulated configuration is for *E* =3.*B* =3, *NT* =5, *N***<sup>R</sup>** =4, with 1000 WiMAX discrete channel realizations. It is also clearly shown that without MCP there is no valuable rate for the cell edge user. Partially these results also support the claim that the proposed method has better performance than the related works at 18dB input SNR, there is approximately 0.5 bits/s/Hz sum rate gain over SLNR-GSVD.

On MU-MIMO Precoding Techniques for WiMAX

http://dx.doi.org/10.5772/56034

27

**Figure 10.** Average Cell Edge User Rate Performance of MCP Precoding Methods for the Configuration

As shown before, the simulation result reveals the unique opportunities arising from MU-MIMO transmission optimization of antenna spatial multiplexing/ spatial diversity techniques with Multi-cell Processing (Inter-cell interference cancelation). Furthermore, it also clearly indicates that MU-MIMO precoding approaches provide significant multiplexing (on the order of the number of antennas used at the transmitter) and diversity gains while resolving some of the issues associated with conventional cellular systems. Particularly, it brings precoding

To conclude, this chapter has introduced the principles of MIMO techniques, reviewed various MU-MIMO precoding methods, and extended the knowledge by proposing a new method that outperformed the methods available in the literature. The results as shown in in fig‐ ure10, demonstrated conclusively the significant role of precoding in inter-cell interference cancelation in MCP scenario. There are still some interesting open issues and topics for future

(*E* =3, *NT* =5, *N***<sup>R</sup>** =4, *B* =3), WiMAX Channel Model Precoding for Multi-cell Processing (Networked MIMO)

robustness with MU-MIMO gain and turn the inter-cell interference into diversity.

**5. Conclusion and future research directions**

**Figure 9.** Example of Tidy Three Multi-cells Cooperation (Exchanging Both the Data and the CSI)


**Table 2.** System Simulation Parameters.

Figure 10. shows the simulated average user rate performance for the MU-MIMO MCP. In this figure, the proposed algorithm result is denoted by PA-SLNR-FK-MCP and the conventional precoding methods of PU-SLNR-GEVD-MCP and PU-SLNR-GSVD-MCP and as a benchmark we also consider the case of no cooperation denoted as NO-MCP. The simulated configuration is for *E* =3.*B* =3, *NT* =5, *N***<sup>R</sup>** =4, with 1000 WiMAX discrete channel realizations. It is also clearly shown that without MCP there is no valuable rate for the cell edge user. Partially these results also support the claim that the proposed method has better performance than the related works at 18dB input SNR, there is approximately 0.5 bits/s/Hz sum rate gain over SLNR-GSVD.

**Figure 10.** Average Cell Edge User Rate Performance of MCP Precoding Methods for the Configuration (*E* =3, *NT* =5, *N***<sup>R</sup>** =4, *B* =3), WiMAX Channel Model Precoding for Multi-cell Processing (Networked MIMO)

As shown before, the simulation result reveals the unique opportunities arising from MU-MIMO transmission optimization of antenna spatial multiplexing/ spatial diversity techniques with Multi-cell Processing (Inter-cell interference cancelation). Furthermore, it also clearly indicates that MU-MIMO precoding approaches provide significant multiplexing (on the order of the number of antennas used at the transmitter) and diversity gains while resolving some of the issues associated with conventional cellular systems. Particularly, it brings precoding robustness with MU-MIMO gain and turn the inter-cell interference into diversity.
