Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Coordinated precoding based on interference alignment is a promising technique for improving the throughputs in future wireless multicell networks. In small networks, all base stations can typically jointly coordinate their precoding. In large networks, hover, base station clustering is necessary due to the otherwise overwhelmingly high channel state information (CSI) acquisition overhead. In this work,  provide a branch and bound algorithm for finding the globally optimal base station clustering. The algorithm is mainly intended for benchmarking existing suboptimal clustering schemes.  propose a general model for the user throughputs, which only depends on the long-term CSI statistics. The model assumes intracluster interference alignment and is able to account for the CSI acquisition overhead. By enumerating a search tree using a best-first search and pruning sub-trees in which the optimal solution provably cannot be, the proposed method converges to the optimal solution. The pruning is done using specifically derived bounds, which exploit some assumed structure in the throughput model. It is empirically shown that the proposed method has an average complexity that is orders of magnitude lor than that of exhaustive search.
['Rasmus Brandt', 'Rami Mochaourab', 'Mats Bengtsson']
I am writing a research paper on a idea Globally Optimal Base Station Clustering in Interference Alignment-Based Multicell Networks
[{"from": "human", "value": "I am writing a research paper on a idea Globally Optimal Base Station Clustering in Interference Alignment-Based Multicell Networks"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Coordinated precoding based on interference alignment is a promising technique for improving the throughputs in future wireless multicell networks. In small networks, all base stations can typically jointly coordinate their precoding. In large networks, hover, base station clustering is necessary due to the otherwise overwhelmingly high channel state information (CSI)\u00a0acquisition overhead. In this work,  provide a branch and bound algorithm for finding the globally optimal base station clustering. The algorithm is mainly intended for benchmarking existing suboptimal clustering schemes.  propose a general model for the user throughputs, which only depends on the long-term CSI statistics. The model assumes intracluster interference alignment and is able to account for the CSI acquisition overhead. By enumerating a search tree using a best-first search and pruning sub-trees in which the optimal solution provably cannot be, the proposed method converges to the optimal solution. The pruning is done using specifically derived bounds, which exploit some assumed structure in the throughput model. It is empirically shown that the proposed method has an average complexity that is orders of magnitude lor than that of exhaustive search."}]