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To accommodate the explosive growth of the Internet-of-Things (IoT),incorporating interference alignment (IA) into existing multiple access (MA)schemes is under investigation. However, when it is applied in MIMO networks toimprove the system compacity, the incoming problem regarding information delayarises which does not meet the requirement of low-latency. Therefore, in thispaper, we first propose a new metric, degree of delay (DoD), to quantify theissue of information delay, and characterize DoD for three typical transmissionschemes, i.e., TDMA, beamforming based TDMA (BD-TDMA), and retrospectiveinterference alignment (RIA). By analyzing DoD in these schemes, its valuemainly depends on three factors, i.e., delay sensitive factor, size of dataset, and queueing delay slot. The first two reflect the relationship betweenquality of service (QoS) and information delay sensitivity, and normalize timecost for each symbol, respectively. These two factors are independent of thetransmission schemes, and thus we aim to reduce the queueing delay slot toimprove DoD. Herein, three novel joint IA schemes are proposed for MIMOdownlink networks with different number of users. That is, hybrid antenna arraybased partial interference elimination and retrospective interferenceregeneration scheme (HAA-PIE-RIR), HAA based improved PIE and RIR scheme(HAA-IPIE-RIR), and HAA based cyclic interference elimination and RIR scheme(HAA-CIE-RIR). Based on the first scheme, the second scheme extends theapplication scenarios from $2$-user to $K$-user while causing heavycomputational burden. The third scheme relieves such computational burden,though it has certain degree of freedom (DoF) loss due to insufficientutilization of space resources.

Retrospective Interference Regeneration Schemes for Relay-Aided K-user MIMO Downlink Networks