# Novel Sparse-Coded Ambient Backscatter Communication for Massive IoT Connectivity
## 1 Introduction
### Proposed Sparse-Coded AmBC (SC-AmBC)  
On the other hand, non-orthogonal signaling in both modulation and detection is proposed recently. For example, sparse code multiple access (SCMA) proposed by Huawei (China) proved effective in a highly-overloaded network [32; 33]. In particular, sparse coding has three desirable properties that are suitable for massive connectivity:  
* **Grant-Free Uplink Transmission**: With sparse coding, RF tags can transmit data in the uplink based on a predefined sparse codebook. The codebook structure can accommodate massive and bursty uplink traffic without a request-grant procedure [34]. The property can lead to low-latency without scheduling and resource allocation in contrast to the cognitive radio based AmBC [27].
* **NOMA**: Sparse code encodes data in multi-dimensional complex codewords providing higher degrees of freedom than conventional two-dimensional AmBC modulators [2; 5; 6; 26]. As a result, sparse code can support concurrent RF transmissions and multiple-access interference (MAI) can be efficiently resolved by an iterative message passing algorithm (MPA) [32].
* **Projected \(M\)-ary Modulation**: In conventional AmBC modulators, _M_-ary modulation is only implemented by \(M\) distinct load impedances increasing form factors of RF devices for higher-order modulations [2; 8; 9]. On the other hand, with sparse coding, _M_-ary data can be represented by few constellation symbols using codeword projection/expansion method [35; 36]. Thus, _M_-ary modulation can be realized in AmBC without increasing form factors of RF devices.  
In addition, due to increasing network densification and delay spreads in multipath propagation, exploiting ISI can achieve better spectral properties than conventional detectors by removing CP [31]. Based on these observations, we propose sparse-coded AmBC (SC-AmBC) including design of modulators and detectors for DBC. Our main contributions can be summarized as follows:  
* Sparse-coded backscatter modulation algorithm (SC-BMA) supporting _M_-ary modulation for AmBC with small-form factors. The modulation can constitute multi-dimensional signal space,which can be easily implemented for passive RF tags without increasing form-factor and exempted from complex signal processing burdening low-cost RF tags.
* Dyadic channel estimation algorithm (D-CEA) fully capturing characteristics of DBC. The channel modeling includes both the effect of cascaded channel in AmBC and the effect of NOMA signaling and is distinguished from one-way Rayleigh and single-path fading channel without ISI.
* Dyadic MPA (D-MPA) based on dyadic factor graph exploiting the weighted-sum of ISI caused by DBC in information exchange process. The proposed MPA exploiting ISI instead of filtering it provides superior detection performance to traditional MPA designed for one-way channels.  
To the best of the authors' knowledge, implementing the sparse code for energy-constrained AmBC is not fully explored in literature. The rest of the paper is organized as follows. Section 2 describes SC-AmBC and motivating examples of our model therein. Section 3 presents the load modulation including a sparse coding algorithm and channel estimation algorithm, and an iterative detector based on DBC is proposed in Section 4. Simulation results are provided in Section 5. Finally, Section 6 concludes the paper.