# Opportunities and Challenges for Error Control Schemes for Wireless Sensor Networks: A Review
## 5 Review on ECS Methods on WSN
### Adaptive Technique
#### 5.2.2 Multi-Hop Network  
[PERSON] et al. analyze trade-off between transmission and processing energy consumption in multi-hop sensor nodes (refer to Figure 9) using adaptive convolutional code combined with Stop-and-Wait ARQ [56]. [PERSON] et al. put forward adaptive convolutional code with optimized code complexity for each transmission hop. The encoder memory order is used to alter the complexity of code and error correcting capability. The adaptability of convolutional code is performed by selecting optimal memory order according to received SNR value. The paper claims that there is a significant energy saving while using proposed adaptive code when compared with the use of conventional convolutional code with fixed encoder order and uncoded system combined with Stop-and-Wait ARQ in the same setting. The paper does not outline feedback mechanism and channel estimation techniques for adaptation. In [35], [PERSON] et al. propose an adaptive error control scheme consisting of LDPC as FEC, ARQ and CRC for multi-hop scenarios. Source nodes encode data using LDPC encoding and then calculate CRC of the encoded data. Then, the transmitter sends the encoded packet to next node using Minimum Transmission Energy (MTE) (refer to Figure 8). At the intermediate node, CRC is used to verify the quality of the encoded packets. If there is no error during CRC check, the packet will be transmitted to the next node. If CRC check finds an error, the intermediate node decides either to decode using LDPC or re-transmit based on the distance between nodes. If the distance between nodes is less than crossover distance, retransmission will be performed; otherwise, decoding is performed using LDPC decoding. The paper advises that the distance between nodes is estimated using RSSI and also discusses theoretical aspects of crossover distance calculation for LOS and NLOS situation. However, how the distance between nodes is determined using RSSI and crossover distance in simulation settings is not clearly discussed. Another key weakness in this paper is total energy calculation while using LDPC code at the intermediate node. During energy calculation, energy consumption of LDPC code using an BP algorithm is used once, which is not accurate according the algorithm described. However, it is not clear how this energy consumption is used to evaluate total energy consumption in the proposed adaptive coding scheme using multi-hop scenarios. Additionally, the paper does not outline the code rate of LDPC code used in the proposed scheme and does not consider the effect of code rate in the energy consumption model. Therefore, there is an issue regarding how total energy is computed during the simulation. The paper claims that the approach optimizes both energy consumption and reliability of WSN, and the proposed adaptive ECS performs well in all settings. The authors present total energy consumption of WSN versus network lifetime in 50 m\({}^{2}\) and 200 m\({}^{2}\) areas with 50 homogenous sensor nodes, but there is no output or result from a reliability aspect. The results in the paper clearly show that uncoded scheme performance is best among all. Therefore, the claim is not clearly supported by results. In [37], [PERSON] et al. propose an adaptive error control scheme consisting of two error correction codes: LDPC and RS codes for multi-hop scenarios. The energy model for multi-hop WSN is estimated considering that the transmitter sends the encoded packet to the next node using the MTE algorithm. In the proposed scheme, a node needs to choose between LDPC and RS code according to the distance between nodes and crossover distance. There is a lack of clarity about code rate of LDPC and RS code. The key drawback of this paper is energy estimation. The estimation considers a one time decoding cost of LDPC and RS code instead of multiple decoding of codes involved in multi-hop scenarios. Therefore, the claim of efficiency and reliability of the proposed system can not be independently verified.