專任教師
主題一:
Near-Optimal Designs of Hybrid Precoding and Combining for Massive MIMO Systems from Lattice Decoding
We proposed near-optimal designs for hybrid massive MIMO communication systems. The designs consist of a pair of finite resolution analog precoder and combiner and a baseband encoder. For any configuration of hybrid MIMO systems, several powerful upper bounds on the maximal achievable rates are derived and are used as guidelines for the proposed designs. Armed with the insights of upper bounds, designing the coefficients for finite resolution analog precoders and combiners is then regarded as a lattice decoding problem, where low complexity lattice decoders and convex solvers are employed to yield optimal solutions with the best structure for partial connection. Simulation results show that the proposed design achieves within a negligible gap to the rate upper bound using phase shifters with low resolution, while reducing the number of required phase shifters by roughly 20% and significantly outperforming many existing designs at the same time.主題二:
SZFDPC-Based MIMO Downlink Communications with Fairness Considerations
We proposed new power allocation schemes taking both sum-rate and fairness into account for MIMO downlink communications employing successive zero-forcing dirty paper coding. Using a revised L1-norm fairness measure that allows for a more comprehensive consideration when users have an unequal number of receive antennas, we completely characterized the optimal tradeoff between sum-rate and fairness for MIMO downlink communications with arbitrary channel statistics. We also devised a novel stochastic power allocation scheme capable of achieving this optimal tradeoff. To put the optimal tradeoff into practical use, we designed an explicit rule for selecting operating sum-rate from the tradeoff. Simulation results show that the new scheme can yield higher sum-rate and better fairness at the same time.