低延遲虛擬細胞車用通信網路下行鏈路多用戶檢測技術之研究

Abstract

To achieve ultra-low latency mobile networking, recent efforts to integrate virtual cell with open-loop communications and proactive network association suggest the facilitation of new technological paradigm, but the interference from different co-locating virtual cells is hard to handle. Open-loop transmissions make beam-forming/interference alignment (IA) infeasible due to the need of channel state information (CSI) feedback. Multiuser detection (MUD) is therefore employed to address downlink interference. We note that the bit error rate (BER) of maximum-likelihood MUD (ML-MUD) is sensitive to the modulation of interference. As the interferer uses low-order modulation, the BER of desired signal can approach the ideal case without interference. But if the interferer adopts high-order modulation, the resultant BER is signi ficantly degraded. Our study shows that such modulation sensitivity can be eased by multi-antenna technique. We also propose two methods to reduce the notorious computational complexity of MUD, particularly involving higher-order modulations. The first scheme is termed reduced-computation ML-MUD (R-ML-MUD) that exploits the characteristic of downlink to shrink the ML solution space, consequently leading to lower detection complexity. The second scheme is a new projection receiver, called generalized linear minimum mean square error equalizer (GLMMSE) resulting in notable signal-to-noise ratio (SNR) gain over the conventional projection method. Nevertheless, losing perfect synchronization creates difficulty in tackling multiple access interference (MAI). Multiple carrier frequency offsets (CFOs) due to different oscillators at different access points (APs) incur serious inter-carrier interference (ICI) to complicate downlink MAI. Asynchronous MUD with ICI-Whitening was shown leading to satisfactory performance, but the whitening scheme needs the covariance matrix of ICI that is practically hard to obtain for downlink receivers. We therefore develop a two-stage ICI suppression method to resolve this challenge. The first-stage processing is Pseudo-ICI-Whitening (P-ICI-W), which does not rely on the estimation of ICI covariance and is suitable for asynchronous downlink. In terms of post-processing signal-to-interference-plus-noise ratio (SINR) and BER, our proposed mechanism can approach ICI-Whitening. The second-stage processing is based on GLMMSE to further cancel some ICI terms. We also apply our scheme to space-time-block-coded signals, considering Alamouti coding and Complex Interleaved Orthogonal Design. Finally, we assume that APs can coordinately allocate radio resource for the served vehicles and enforce frequency-domain cooperative data encoding. Our analysis shows that CFOs will still noticeably worsen the BER, even if ICI is well-addressed. Such problem can be resolved by indexing APs according to the order of CFOs. Furthermore, we propose a robust encoding scheme that achieves satisfactory performance and allows random AP indexing, thus CFO feedback can be avoided.