# Is Satellite Ahead of Terrestrial in Deploying NOMA for Massive Machine-Type Communications?
## 2 The S-MIM System
### Selected NOMA Solution  
Stimulated by the challenging requirements for the IoT use case, the European Space Agency (ESA) initiated investigations of advanced random access (RA) techniques able to satisfy the satellite operator's needs. Previous research on slotted RA solutions with collision resolution was not retained. The main drawback of slotted RA is related to the need to keep the terminal time synchronized, causing an unwanted level of signaling overhead, and increasing the terminal complexity. A comprehensive survey of satellite RA schemes is provided in [11]. For the new IoT protocol, the attention was rapidly turning to the E-SSA NOMA technology, as it was providing the best fit to the requirements listed in Section 2. In particular, E-SSA allows full asynchronous uncoordinated access with high packet delivery reliability, a low transmit peak power and high energy and spectral efficiency (three orders of magnitude higher than classical ALOHA [12]). In addition, the S-MIM standard provides a simple yet effective open loop power and packet transmission control technique,maximizing the successful transmission of packets, even in the presence of satellite mobile channel blockage and shadowing. E-SSA represents an evolution of the well-known Spread Spectrum ALOHA (SSA) random access protocol proposed by [PERSON] [12]. The main difference between E-SSA and SSA is related to the gateway demodulator processing. Instead of a single-packet demodulation/decoding SIC attempt, the E-SSA demodulation processing is based on a sliding window approach. The sliding window I-Q baseband signal, typically spanning the length of three packets, is repeatedly scanned, searching for detectable packets performing iterative SIC. The packet detection is based on a known preamble. Under loaded conditions, during the first SIC pass, only a subset of packets' preambles can be detected due to the high level of multiple access interference. However, this relatively small percentage of detected packets, if successfully decoded, is then reconstructed at the baseband and subtracted from the demodulator sliding window memory. To obtain an accurate baseband packet reconstruction, the full detected payload is used to perform a decision-directed channel estimation. Once the first pass and associated detection and successive interference cancellation (SIC) step is completed, the process is restarted, and more packets can be detected and demodulated thanks to the previous cancellation step. This process is repeated a number of times (iterations) until all packets are recovered. Then, the observation window (typically the length of three packets) is shifted by a fraction (e.g., \(1/3\)) of the packet duration, and the iSIC process repeated [2]. The E-SSA analysis and simulation results reported in [2] have shown that the packet loss ratio (PLR) rapidly falls to low values below a critical medium access control channel (MAC) normalized load (expressed in bits/chip). The throughput and PLR behavior of SSA and E-SSA with and without a packet power unbalance are reported in Figure 1. In particular, Figure 1a shows the normalized throughput expressed in bits/chip vs. the average medium access channel (MAC) normalized load, also expressed in bits/chip for both conventional SSA and E-SSA. Figure 1b provides the packet loss ratio (PLR) vs. the normalized MAC load. Results are obtained for the balanced and unbalanced power of the received packets. A lognormal packet power distribution is assumed with standard deviation of \(\sigma=0\) dB (balanced power) and \(\sigma=3\) dB (unbalanced power). Note that in the case of the power unbalance, the SSA throughput is heavily impacted by the well-known CDMA near-far effect, while the E-SSA performance is further boosted thanks to the SIC processing. The E-SSA PLR horizontal floor appearance for the lognormal packet power distribution is explained in [2], and it is fully predictable.