Ubaid Ahmad

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Lattice Reduction (LR) is a promising technique to improve the performance of linear MIMO detectors. This paper proposes a Hybrid LR algorithm (HLR), which is a scal-able LR algorithm. HLR is specifically designed and op-timised to exploit ILP and DLP features offered by parallel programmable baseband architectures. Abundant vector-parallelism in HLR is(More)
—Worst-case design is one of the keys to practical engineering: create solutions that can withstand the most adverse possible conditions. Yet, the ever-growing need for higher energy efficiency suggest a grim outlook for worst-case design in the future. In this paper, we propose opportunistic run-time approximations to enable a continuous adaptation of the(More)
Lattice Reduction aided softoutput MIMO detectors have been demonstrated to offer a promising gain. However, computing Log-Likelihood ratios (LLR) for near-optimal MIMO detection, still poses a significant challenge for practical implementations. In this work, we present counter-ML bit-flipping algorithm for LLR generation. The proposed LLR generation(More)
Ove Edfors: Massive MIMO-Performance of low-complex linear precoding Spatial multiplexing using massive MIMO has been shown to have very promising properties, including low-complex linear precoding, large increases in spectral efficiency, and several orders of magnitude lower transmit powers-as compared to today's access schemes. These things have, however,(More)