## 6 Performance Evaluation  
This section discusses multiple findings that describe the performance of m-MIMO with systems. Specifically, this section provides comparison results between the rate of the state-of-the-art TS designs proposed in [36; 41] and the rate obtained using our proposed training solution. The comparison is conducted based on the scattering one-ring (OR) channel model and the Laplacian channel model. Table 1 contains the parameters used for the performance evaluation. In this study, we focus on a densely populated urban area where users are situated within a 200-meter range from the BS. The coherence block length values used in the simulation are \(\tau_{\mathrm{c}}=100\) and \(\tau_{\mathrm{c}}=50\), with a total of \(K=10\) users. The OR model and Laplacian model are employed with distinct angular spreads of \(\omega_{\mathrm{H}}=5^{\circ},15^{\circ}\), which indicate strong and poor spatial correlation in the channel, respectively. The other parameters are obtained by  
AoAs \(\theta_{k,H}\), angular spread \(\omega\), and spacing of the antenna \(D\), as specified in [36]. The power allocation should satisfy the total constraint with \(P_{\mathrm{d}}=1\). The training power \(\rho_{tr}\) is given as SNR in dB, which ranges from -15 dB to 20 dB. In our figures, every point depicted in the simulation is the average of 5000 independent channel realizations obtained through Monte Carlo simulation runs. The angle of arrivals is specified as \(\theta_{k,H}=-57.5^{\circ}\), \(-45^{\circ}\), \(-41.5^{\circ}\), \(-23^{\circ}\), \(-7.5^{\circ}\), \(7.5^{\circ}\), \(23.5^{\circ}\), \(41.5^{\circ}\), \(45^{\circ}\), \(57.5^{\circ}\), according to [36]. In real-world scenarios, the CCM based on the OR and Laplacian models is unlikely to have singular values equal to zero. To minimize the overhead during DL TS, the strong eigenvalues of the summation of transmit CCM are chosen in the design, while the remaining eigenvalues are disregarded. This implies that only the dominant dimensions of the effective channel, where most of the energy is concentrated, are used for precoding design and data transmission, whereas the other dimensions are not utilized. It is important to note that using orthogonal or random DL TS is not effective with FDD m-MIMO systems because these sequences might span all dimensional space and waste resources in the training phase. The proposed DL TS design is evaluated and compared to conventional designs based on achievable sum-rate maximization. Figure 2 examines the achievable sum rate using the Laplacian channel model comparing different training designs under a strong channel and relatively weak correlations. We select \(N=128\) and with very short CCT \(\tau_{\mathrm{c}}=50\). The results in Figure 2 show that the rate of the proposed design outperforms the state-of-the-art training designs. In addition, the results in Figure 2 indicate that a significant increase in the rate can be achieved with high correlation, i.e., \(\omega_{\mathrm{H}}=5^{\circ}\). Figure 3 investigates the rate using the Laplacian model when the CCT is increased, i.e., \(\tau_{\mathrm{c}}=100\). The results in Figure 3 demonstrate that the rate is increased when the CCT is increased, and the proposed TS design outperforms the existing methods. Figures 4 and 5 investigate the rate with Laplacian model when \(N=256\) and with very short and short CCT \(\tau_{\mathrm{c}}=50\) and \(\tau_{\mathrm{c}}=100\), respectively. The results in Figures 4 and 5 show that a considerable enhancement in the rate can be achieved using the proposed TS design in comparison to the existing methods. The results also indicate that with \(\omega_{\mathrm{H}}=15^{\circ}\), loss in the rate is observed in all the methods considered with around \(5\,\mathrm{bits/sec/Hz}\). Figures 6 and 7 show plots of the sum rate using OR channel model with \(N=128\) and with very short and short CCT \(\tau_{\mathrm{c}}=50\) and \(\tau_{\mathrm{c}}=100\), respectively.