In legacy long term evolution (LTE) networks, multiple transmission modes are defined to cater to diverse wireless environment and improve the spectrum utilization. However, constrained by user equipment (UE) processing capability on blind detection of downlink control information (DCI), two transmission modes are allowed to be configured to UE simultaneously. In recent 5G standardization, the polar codes have supplanted the tail biting convolution codes (TBCC), becoming the channel coding scheme for downlink control information (DCI). Motivated by its successive decoding property, a novel design of DCI encoding and decoding is proposed in this paper. The proposed scheme could support dynamic configuration of transmission modes with decreasing the complexity of blind detection. Evaluation results from link level simulations show that the performance loss compared to conventional encoding/decoding scheme is generally negligible and the proposed scheme can comply with the false alarm rate (FAR) target of 5G standardization.

Massive multiple-input and multiple-output (MIMO) systems have draw a lot of attention, due to its outstanding performance in energy saving and spectrum efficiency [1]. In massive MIMO systems, the intra-cell interference, uncorrelated noise and fast fading nearly vanish. Further study reveals that for multi-cell massive MIMO systems the performance will be limited by so-called pilot contamination (inter-cell interference) [2], where the transmitted CSI at one BS includes the channel coefficients from all the users using the same pilot. However, the analysis in [2] ignores a fact that the spatial/temporal characters of channel coefficients of different users are different such that they are distinguishable in certain extends. In practice, utterly isolating the user channels is extremely hard or even not feasible in certain cases. This paper firstly presents a practical temporal domain based method against pilot contamination without coordination, which just remains the strongest channel impulse responses (CIR) as the effective channel information. Simulation results show the outperformance of the proposed method with low complexity.

In this letter, we investigate multiple-input multiple-output (MIMO) communications under energy harvesting (EH) constraints. In our considered EH system, there is one information transmitting (ITx) node, one traditional information receiving (IRx) node and multiple EH nodes. EH nodes can transform the received electromagnetic waves into energy to enlarge the network operation life. When the ITx node sends signals to the destination, it should also optimize the beamforming/precoder matrix to charge the EH nodes efficiently simultaneously. Additionally, the charged energy should be larger than a predefined threshold. Under the EH constraints, in our work both minimum mean-square-error (MMSE) and mutual information are taken as the performance metrics for the beamforming designs at the ITx node. In order to make the proposed algorithms suitable for practical implementation and have affordable overhead, our work focuses on the beamforming designs with partial CSI and this is the distinct contribution of our work. Finally, numerical results are given to show the performance advantages of the proposed algorithms.