# Intelligent Transmission Control Scheme for 5G mmWave Networks Employing Hybrid Beamforming
## 4 Proposed Work
### Accurate Channel Estimation for mmWave Systems
#### 4.2.3 RSSI-Based Association Strategy for Channel Selection  
When the TBU link experiences \"non-line-of-sight (NLOS)\" propagation, IRSs are used to improve the performance of blocked users by offering \"line-of-sight (LOS)\" transmission and reflection gain [37]. In this scenario, we use a criterion based on RSSI for association, where the user is connected to the IRS with the highest long-term average received power. Ideally, the IRS can manipulate the reflection angle of the incoming signal to adjust the orientation of the intended user. Yet, in reality, the IRS needs complete channel state information to achieve this outcome, making it a challenging task. Hence, we investigate a scenario in which IRSs are limited in adjusting the reflection angle and are only able to offer a set reflection direction. Additionally, we assume that the main lobe beam's reflection direction from each IRS is randomly and uniformly distributed, while the BS can align its beam direction towards the serving IRS. According to the prior conversation, the serving IRS must make sure that the combination of reflection gain and path loss for the RU link is at its highest possible value [35]. This situation is shown in the following equation:  
\[Y_{q_{0}}=agrmx\;H_{q_{0}}\|Y_{q}-Y_{0}\|^{-\alpha A} \tag{23}\] \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Method** & **Parameter** & **Memory Overhead** & **Capability** \\ \hline All shared & \(W_{1}=\left\{Q_{l,1},X_{l,1},\alpha_{i_{1}}\right\}_{l=1}^{L}\) & Low & Low \\ \hline None shared & \(W_{1}=\left\{Q_{l,1},X_{l,1},\alpha_{i_{1}}\right\}_{l=1}^{L}\) & High & High \\  & \(W_{1}=\left\{Q_{d,d},X_{l,d},\alpha_{i_{1}}\right\}_{l=1}^{L}\) & & \\ \hline Separate \(\alpha\) & \(W_{1}=\left\{Q_{l,1},X_{l,1},\alpha_{i_{1}}\right\}_{l=1}^{L}\) & Low & Medium \\  & \(W_{d}=\left\{\alpha_{i,d}\right\}_{l=1}^{L}\) & & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Various weight-sharing approaches. where \(H_{q_{0}}\) represents the gain of the reflection array from \(Y_{q}\) to \(Y_{0}\) in a specific reflection beam direction, and \(\alpha\) is the path loss exponent. The _SINR_ of the typical user at the position \(Y_{0}\) with an IRS at \(Y_{q_{0}}\) is provided in the following scenario:  
\[SINR_{2}=\frac{\mu H_{Bm}\,H_{q_{0}}l_{q}\big{(}Y_{q_{0}}Y_{0}\big{)}\,G_{qU}}{ N_{0}W+\sum_{Y_{B}\in\Phi_{B\setminus Y_{q_{0}}}}\mu G_{B}(\varphi_{b})l_{B} \big{(}Y_{q},Y_{0}\big{)}G_{BU}} \tag{24}\]  
where \(SINR_{2}\) represents the signal-to-interference-plus-noise ratio for the typical user position \(Y_{0}\) with IRS assistance, \(\mu\) denotes the transmit power or power scaling factor, \(H_{Bm}\) is the channel gain among the base station and the mobile station, \(H_{q_{0}}\) represents the reflection gained from the ISR at \(Y_{q_{0}}\) to the user at \(Y_{0}\) in a specific beam direction, \(l_{q}\big{(}Y_{q_{0}}Y_{0}\big{)}\) denotes the path loss among the IRS at \(Y_{q_{0}}\) to the user at \(Y_{0}\), \(G_{qU}\) is the beamforming gain at the user from the IRS, \(N_{0}\) denotes noise power spectral density, \(W\) denotes bandwidth, \(\Phi_{B\setminus Y_{q_{0}}}\) are the set of interfering base stations excluding the serving IRS at \(Y_{q_{0}}\), \(G_{B}(\varphi_{b})\) represents the beamforming gain at the interfering BS for angle \(\varphi_{b}\), \(l_{B}\big{(}Y_{q},Y_{0}\big{)}\) represents the path loss among the interfering BS at \(Y_{q}\) and the user at \(Y_{0}\), and \(G_{BU}\) denotes the beamforming gain at the user from the interfering BS. The _SINR_ of the typical user at position k in an IRS-assisted mmWave network is given by Equation (24). It accounts for the revised signal strength, interference, and noise, providing a comprehensive view of network performance. The equation allows us to consider the influence of the position of the IRS and the reflection angles on the network performance and coverage. _SINR_ represents the ratio of the desired signal's power to the combined interference and noise power, assessing signal quality.