A selective soft-message-forward (SSMF) cooperation with new threshold decision (TD)-based detection is presented to improve the bit error ratio (BER) performance and power efficiency in two-way physical-layer network-coded multiple-input-multiple-output (MIMO) Internet of Things (IoT) systems. First, the SSMF-based physical-layer network coding (PNC) is proposed by selecting appropriate received signals for soft decoding at relay nodes for better BER performance and low complexity. The signals least affected by noises after zero forcing detection are mapped into log-likelihood ratio metrics for most reservation of the soft messages. Second, a new TD-based detection is obtained by classifying the amplified received signals into different processing regions to reduce false decoding for better performance. Finally, an adaptive power allocation (APA) for the SSMF-based PNC is given to further improve power efficiency. By adaptively allocating the transmitting power in source nodes, the amplitudes of two received signals are similar at the relay and thus efficiently eliminate the near-far effect. Simulation results indicate that the SSMF-based PNC surpasses the existing PNC with a binary phase-shift keying (BPSK) modulation. At BER of$10^{-3}$, the SSMF-based PNC outperforms the selective decode-and-forward (DF), SMF, and DF schemes by approximately 0.6, 1.0, and 1.7 dB, respectively. At BER of$10^{-3}$, the APA scheme outperforms the equal power allocation one by about 2 dB. Therefore, it can be efficiently used in two-way integrated satellite and ground wireless MIMO IoT systems.

To solve low-resource utilization, complex storage, and busy traffic in space–air–ground integrated networks (SAGINs), a new multilayered decentralized coded caching (ML-DCC) scheme is proposed in hierarchical networks with nonuniform file popularity and multilevel cache capacity. First, a file popularity prediction is performed by a random forest model with grid search. Second, a multipopularity coded caching (MPCC) strategy by grouping files is executed in a two-hop network with fixed cache size. Finally, a new ML-DCC scheme is proposed to adopt nonuniform file popularity and multilevel cache capacity with both block-coded caching and zero-bit padding to obtain high-resource utilization and efficient file exchange in file transmissions. The innovations are random forest classifier with bagging integration and grid search to improve network traffic and link load, decentralized coded caching to reduce average transferred files, and coded caching and grouping files by popularity to improve network load. Simulation results show that the data payload of the proposed scheme is significantly improved by about 1.88, 1.18, 1.38, 3.53, and 4.39 times, when compared with those of the shared cache, multilevel popularity, hierarchical coded caching, MPCC, and uncoded caching schemes, respectively. Under the expected load of$R=211.57F$bits of the shared link, the cache size used by the proposed ML-DCC is only 1/42.85 and 1/24.39 of those of the highest popularity first (HPF) and nonuniform cache schemes, respectively.

To both eliminate interference from unrequested subfiles and improve sum degree-of-freedom (DoF) in multirelay Internet of vehicles (IoV) systems, a new decentralized multi-subsystem weighted interference cancellation (DMS-WIC) scheme with coded caching is proposed. It divides the transmission into two stages with optimized parameters to minimize link load. It also improves the sum DoF by jointly combining the weighted interference cancellation, orthogonal unicast, and decentralized coded multicast together. Given the number of interference-free subfiles larger than that of users, traditional interference cancellation wastes cache capacities of both users and relays by ignoring partial cache capacities and thus it fails to achieve a balance between the number of both users and interference cancellation subfiles. The DMS-WIC achieves additional DoF by adopting orthogonal unicast and subsequently dividing cache of both users and relays compared with those of traditional interference cancellation. In other cases, the weighted requested subfiles are transmitted by combining physical layer file division and network layer coding delivery together to achieve interference alignment and cancellation gains. The DMS-WIC adaptively adjusts files and subsystem partition parameters by perceiving systematical parameters. Besides, a multirelay cooperative coded caching is introduced to further reduce transmission and complexity. Given the number of relays larger than that of users, the relays deliver coded subfiles with different user sets. Otherwise, a relay skips the fix of the user number units, until all user sets are taken after the completion of a transmission. Simulation results show that the proposed DMS-WIC with coded caching achieves more than 10.6% sum DoF gain compared with that of traditional interference cancellation.

Information-centric networking (ICN) can efficiently utilize bandwidth resources and reduce network data transmission latency, but coded multicast gains are not considered. A novel multiple-subsystem nested coding caching (MSNCC) is then proposed in hierarchical multirelay wireless sensor space-air-ground integrated network (SAGIN) with distinct sensor cache capacities and coded caching for potential coded caching gains. The group-based and zero-bit padding coded caching schemes are tightly coupled with two divided subsystems: 1) network layer placement and 2) physical-layer delivery. Through decentralized caching status (DCSs) aware coded caching optimization, the first subsystem achieves caching gains between adjacent layers, and the second subsystem directly exploits coded multicast gains between a server and several sensors. In situation I of the number of sensors larger than that of files, the MSNCC adopts the group-based decentralized caching to transmit coded subfiles between relays and sensors. In situation II of the remaining scenarios, the zero-bit padding coded caching improves link rate and system complexity. The innovation is the MSNCC with distinct sensor cache capacities by combining group-based decentralized, zero-bit padding, and hierarchical caching together. It effectively improves the link load in the worst circumstance by exploiting potential coded multicast opportunities among relays for different transmissions. Simulation results indicate that, in situation I, the MSNCC obtains approximately 38.5% and 26.5% reduction in delivery rate compared with those of uncoded caching and zero-bit padding coded caching, respectively. It also achieves about 33.3% rate gains compared with that of the uncoded caching.

Optimized polar-coded cooperation with an approximate prior probability-based threshold decision is proposed to improve the reliability and complexity in selective decode-and-forward (SDF) cooperation of multiple satellite constellation systems. First, an SDF scheme with polar coding is adopted in cooperative communications for efficient code construction and relay forwarding. Second, in the logarithmic belief propagation (BP) polar decoding, the variable iterative threshold is derived with independent and variable signal-to-noise ratio (SNR)-based approximate prior probability. This threshold reduces complexity by eliminating active nodes with high reliability in each decoding iteration. Third, the information detection factor is introduced to evaluate the accuracy of decoded bits, thereby limiting the average decoding iterations to improve decoding efficiency. Simulation results show that the proposed polar-coded SDF cooperation obtains 1.5 dB performance gain at a bit error rate (BER) of 10−3compared with that of existing LDPC-related schemes. The complexity of the optimized logarithmic BP decoding is reduced by 25%–50% compared with that of the traditional BP decoding. Therefore, the proposed scheme has good BER performance and low complexity in cooperative communications of multisatellite and wireless integrated systems.

An incremental selection hybrid decode-amplify forward (ISHDAF) scheme for the two-hop single relay systems and a relay selection strategy based on the hybrid decode-amplify-and-forward (HDAF) scheme for the multirelay systems are proposed along with an optimized power allocation for the Internet of Thing (IoT). Given total power as the constraint and outage probability as an objective function, the proposed scheme possesses good power efficiency better than the equal power allocation. By the ISHDAF scheme and HDAF relay selection strategy, an optimized power allocation for both the source and relay nodes is obtained, as well as an effective reduction of outage probability. In addition, the optimal relay location for maximizing the gain of the proposed algorithm is also investigated and designed. Simulation results show that, in both single relay and multirelay selection systems, some outage probability gains by the proposed scheme can be obtained. In the comparison of the optimized power allocation scheme with the equal power allocation one, nearly 0.1695 gains are obtained in the ISHDAF single relay network at a total power of 2 dB, and about 0.083 gains are obtained in the HDAF relay selection system with 2 relays at a total power of 2 dB.