A Novel Interference Alignment (IA) Method for Improving the Sum-Rate of the Hetnet Users
Communication between small and macro cells is cooperative to provide seamless access and to evade the issues caused due to open wireless interfaces. The major concern in these kinds of communication is the interference due to common channel exploitation. This article discusses a novel interference alignment (IA) method modeled using multi-objective least-square (MOLS) optimization. In this IA optimization, the received signal is classified using alignment vector boundary using least-square function. This helps to determine data and noise present in the signal. By deploying appropriate alignment vectors, using least-squares, the interference and data signal is classified at the receiver end. The integrated optimization method is efficient in classifying interference by mitigating the slope errors using alignment plots that help to reduce error rate. As the error is mitigated, the degree of freedom of the users is leveraged that improves the sum rate of the network.
KeywordsInterference alignment HetNets Lease-square measure Multi-objective optimization Signal classification
- 5.Jafar, S.A.: Interference Alignment—A New Look at Signal Dimensions in a Communication Network. Now Publishers Inc., Breda (2011)Google Scholar
- 10.Tresch, R., Guillaud, M.: Clustered interference alignment in large cellular networks. In: 2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications, pp. 1024–1028 (2009)Google Scholar