A context-aware cognitive SIMO transceiver for increased LTE-HetNet system-level DL-throughput

In this paper, we design a new single-input multiple-output (SIMO) context-aware cognitive transceiver (CTR) that is able to switch to the best performing modem in terms of link-level throughput. On the top of conventional adaptive modulation and coding (AMC), we allow the context-aware CTR to make best selection among three different pilot-utilization modes: conventional decision-aided (DA) or pilot-assisted, non-DA (NDA) or blind, and NDA with pilot which is a newly proposed hybrid version between the DA and NDA modes. We also enable the CTR to make best selection between two different channel identification schemes: conventional least-square (LS) and newly developed maximum-likelihood (ML) estimators. Depending on whether pilot symbols can be properly exploited or not at the receiver, we further enable the CTR to make best selection among two data detection modes: coherent or differential. Owing to extensive and exhaustive simulations on the downlink (DL) of a long-term evolution (LTE) heterogeneous network (HetNet), we are able draw out the decision rules of the new CTR that identify the best combination triplet of pilot-use, channel-identification, and data-detection modes to achieve the best link-level throughput at any operating condition in terms of channel type, mobile speed, signal-to-noise ratio (SNR), and channel quality indicator (CQI). Realistic extensive simulations at the system level suggest that the new context-aware CTR outperforms the conventional transceiver (i.e., pilot-assisted LS-type channel estimation with coherent detection) by as much as 40 and 45% gains in average and cell-edge (i.e., 5-percentile) total throughput per macro-area with 10 pico-cells each, respectively.