[month] [year]

European Conference on Networks and Communications (EuCNC 2020)

Varun Chhangani (Research Student working under the supervision of Prof. Vineet Gandhi), Rangeet Mitra (ETS Montreal, Canada) and Vimal Bhatia (IIT Indore) presented a paper on RFF Based Parallel Detection for Massive MIMO at the 29th and first on-line edition of the European Conference on Networks and Communications (EuCNC 2020) from 16 – 17 June.

The EuCNC is the key event to showcase the excellence of European research and innovation in communication technologies. This year the organisers turned it into an on-line event as the Covid-19 pandemic did not allow them to hold the conference in Dubrovnik as initially planned.

Research work as explained by Varun Chhangani: 

Multi user massive multiple input multiple output (MU-m-MIMO) has emerged as a viable technology for scaling up existing communication systems, and in serving increasing number of users for the next-generation communication systems. Several signal processing algorithms exist for mitigating the performance-limiting artefacts encountered in MU-m-MIMO systems (like inter-symbol interference, inter-channel interference, and device nonlinearities), among which, reproducing kernel Hilbert space (RKHS) based approaches have emerged to provide effective solutions. However, most of the existing RKHS based detectors for MU-m-MIMO are dictionary-based, which makes it difficult to gauge the memory requirements beforehand, and are prone to error in the presence of noisy observations. Hence, to reduce the computational complexity, a Random Fourier Features (RFF) based parallel detection algorithm is proposed for MU-m-MIMO, that uses decomposed blocks of high dimensional observations, and makes the proposed detector scalable for parallel computation using modern multi-core compute-units at the receivers (which is possible today due to advances in computing). Further, the RFF based explicit feature map to RKHS alleviates the requirement of a dictionary, and facilitates ease of practical implementation. Simulations are performed over realistic MU-m-MIMO systems, which indicates that the proposed approach delivers an acceptable uncoded BER performance, whilst maintaining a finite implementation budget, which makes the proposed approach attractive for implementation. Lastly, the error-rate analysis of the proposed detector is performed, and validated through simulations.