# Instantaneous Beam Prediction Scheme against Link Blockage in mmWave Communications
## 2 Related Work
### Beam Recovery Schemes Based on Beamforming Solutions  
Multiple studies rely on modifying beamforming designs to tackle the blockage problem. Table 1 briefly outlines key techniques, along with their advantages and limitations.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Reference** & **Algorithm** & **Advantages** & **Limitations** \\ \hline
[2] & Iterative codebook-based approaches. & Reduced complexity versus exhaustive beam reset scanning. & Poor directivity at initial codebook stages, prolonged recovery times (reset scanning). \\ \hline
[3,4] & Metaheuristic search schemes. & Reduced complexity versus conventional codebook schemes. & approximate solutions deficiency in estimating optimal beam directions. \\ \hline
[5,6] & Dual-beam methods that combine signal from adjacent directions. & Aggregates signal from other directions associated with the defected beam. & High power needs for continuous measurements at other beam directions. \\ \hline
[7] & Redundant beams. & Instantaneous beam recovery without scan resetting. & High power levels due to continuous scanning for prolonged time periods. \\ \hline
[8] & Self-handover scheme using secondary beam scanning. & Instantaneous recovery without the need for retransmissions. & Confinet upon availability of multiple BSs in MS proximity. Requires redundancy for transmitting back-up packets. \\ \hline
[9] & Signal measurements at proximity beams of the failed main beam. & Shorter recovery times as compared to codebook and metaheuristic approaches. & albeit at the prolonged test times that extent the recovery process and yield in session drops. \\ \hline
[10] & Data forwarding algorithm. & Reactive method for instantaneous recovery. & Requires intermediate nodes, prolonged times due to relaying, infrastructure cost. \\ \hline
[11] & Backup beam for link recovery. & Reactive method for instantaneous recovery. & High power consumption, limited to NSA standard, as backup beam direction is retrieved using microwave bands. \\ \hline
[12] & Machine learning for reliable mmWave systems. & Proactive approach enables fast beam switching times between BSs. & limited blockage parameters, marginal link improvements. \\ \hline
[13,14] & Situational awareness [13] and data-driven [14] prediction approaches. & Consideration for power at the beam index, high prediction precision. & Location awareness of MS to train the network, accuracy challenges. \\ \hline \hline \end{tabular}
\end{table}
Table 1: Existing research on beam recovery techniques based on beamforming solutions.  
First, an intuitive solution to beam blockage is to reset the beam scanning process, using either iterative codebook-based approaches [2] or metaheuristics search schemes [3; 4]. Other studies implement a dual-beam method [5] that simultaneously combines signals from two adjacent directions. Another approach, in [6], uses the equal gain combining (EGC) method to aggregate a received signal for the second and third beam directions that are associated with the defected (main) beam. A soft self-handover scheme is proposed in [7] that uses redundant beams for continuous beam scanning to maintain established communication sessions when blockage occurs, without the need to reset the beam search process. Overall, this scheme consumes a lot of power due to its continuous scanning for prolonged time periods. Moreover, the authors of [8] propose an instantaneous self-handover scheme using a secondary scanning beam. However, it is contingent on the availability of multiple BSs in the proximity of MS. Diversity coding is exploited here to recover data packets without the need for retransmissions. However, this scheme requires high link redundancy for transmitting back-up data packets.