Backscatter communications, an emerging low-cost and low-consumption green communication paradigm, has received significant attention in both industry and academia. In recent years, multiple-input multiple-output (MIMO) technology has also been integrated into backscatter communications to meet the requirements of transmission performance in IoT scenarios. However, due to the hardware limitations of backscatter tags, one of the main challenges for multi-antenna backscatter tags is to reduce the circuit complexity of space-time block codes (STBC) while maintaining transmission performance. Although low-complexity STBC for dual-antenna tags has been explored, to the best of our knowledge, research on high-performance, low-complexity STBC for four-antenna tags remains in its infancy. In this paper, we propose a 2×4 extended Alamouti code (EAC) with full-rate capability for MIMO backscatter communications. The results show that the required impedance of the proposed EAC on the backscatter tag is less than half of that of the conventional orthogonal STBC (OSTBC), which considerably reduces the complexity of the tag circuit. Additionally, we also derive the asymptotic closed form expression of the symbol error rate (SER) of the proposed EAC to obtain the system insights. The derivation results show that the achievable diversity order of the proposed EAC in 1×4×N backscatter channel is 2×min(2,N), which indicates that the proposed EAC can achieve the same diversity performance as the conventional OSTBC by setting an appropriate number of receiver antennas. Finally, numerical simulations are performed to validate the accuracy of our analysis and the superiority of the proposed EAC in SER.

Clustering protocols are potential solutions to address the severe energy constraints faced by cognitive radio sensor networks (CRSNs). To further exploit the potential of clustering protocols in reducing node energy consumption, active reconfigurable intelligent surface (RIS) is for the first time incorporated into clustered CRSNs to assist the uplink data transmission toward the sink. To minimize the total node energy consumed by uplink data transmission, we formulate the problem of maximizing the normalized energy efficiency improvement ratio for all nodes in active RIS-assisted clustered CRSNs compared to conventional clustered CRSNs and solve it by jointly optimizing the active RIS beamforming and transmit power of CRSNs nodes. Specifically, by considering the physical and electromagnetic properties of the active RIS, we redefine the conditions for successful information transmission under deterministic channels. Analytical expressions for the optimal reflection coefficients of the active reflecting elements (REs), as well as semiclosed-form solutions for the transmit power of CRSNs nodes are derived. Moreover, the optimal configurations of key parameters, such as the number of active REs, total power budget for the active RIS, wavelength of transmitted signal, and physical dimensions of REs are theoretically derived and validated through numerical simulations, thereby offering design guidance for future active RIS-assisted clustered CRSNs. Simulation results indicate that the proposed mechanism significantly outperforms its baseline counterparts and is suitable for CRSNs nodes with severe computational and energy constraints.

Due to dynamic channel availability in cognitive radio sensor networks (CRSNs), clustering protocols are significantly affected. This letter proposes energy coverage efficiency (ECE) metric specifically for clustering protocols in CRSNs, in which network lifetime and effective surveillance capability are for the first time integrated. Simulation results show that ECE can provide a comprehensive evaluation for clustering protocols in CRSNs.