Multicast and Unicast Superposition Transmission in MIMO OFDMA Systems with Statistical CSIT

05/25/2023
by   Yong Jin Daniel Kim, et al.
0

We consider a downlink multicast and unicast superposition transmission in muti-layer Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiple Access (OFDMA) systems when only the statistical channel state information is available at the transmitter (CSIT). Multiple users can be scheduled by using the time/frequency resources in OFDMA, while for each scheduled user MIMO spatial multiplexing is used to transmit multiple information layers, i.e., single user (SU)-MIMO. The users only need to feedback to the base-station the rank-indicator and the long-term average channel signal-to-noise ratio, to indicate a suitable number of transmission layers, a suitable modulation and coding scheme and allow the base-station to perform user scheduling. This approach is especially relevant for the delivery of common (e.g., popular live event) and independent (e.g., user personalized) content to a high number of users in deployments in the lower frequency bands operating in Frequency-Division-Duplex (FDD) mode, e.g., sub-1 GHz. We show that the optimal resource allocation that maximizes the ergodic sum-rate involves greedy user selection per OFDM subchannel and superposition transmission of one multicast signal across all subchannels and single unicast signal per subchannel. Degree-of-freedom (DoF) analysis shows that while the lack of instantaneous CSI limits DoF of unicast messages to the minimum number of transmit antennas and receiver antennas, the multicast message obtains full DoF that increases linearly with the number of users. We present resource allocation algorithms consisting of user selection and power allocation between multicast and unicast signals in each OFDM subchannel. System level simulations in 5G rural macro-cell scenarios show overall network throughput gains in realistic network environments by superposition transmission of multicast and unicast signals.

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