We provide a comprehensive energy efficiency (EE) analysis of the full-duplex (FD) and half-duplex (HD) amplify-and-forward (AF) relay-assisted 60-GHz dual-hop indoor wireless systems, aiming to answer the question of which relaying mode is greener (more energy efficient) and to address the issue of EE optimization. We develop an opportunistic relaying mode selection scheme, where FD relaying with one-stage self-interference cancellation (passive suppression) or two-stage self-interference cancellation (passive suppression + analog cancellation) or HD relaying is opportunistically selected, together with transmission power adaptation, to maximize the EE with given channel gains. A low-complexity joint mode selection and EE optimization algorithm are proposed. We show a counter-intuitive finding that with a relatively loose maximum transmission power constraint, FD relaying with two-stage self-interference cancellation is preferable to both FD relaying with one-stage self-interference cancellation and HD relaying, resulting in a higher optimized EE. A full range of power consumption sources is considered to rationalize our analysis. The effects of imperfect self-interference cancellation at relay, drain efficiency, and static circuit power on EE are investigated. Simulation results verify our theoretical analysis.

Both information age and delay are critical performance metrics of emerging time-sensitive applications. However, their inherent correlation in the finite block length (FBL) regime has remained uninvestigated as it is affected by block length and update rate in a complex manner. In this paper, closed-form expressions for average age of information (AoI), peak AoI (PAoI) and delay are derived for an FBL Last-Come First-Served system with retransmission and non-preemption policies, based on which a comprehensive analysis of the relationship among the three metrics in the FBL regime is presented. It is proved that there exists a strong tradeoff between delay and AoI/PAoI given a block length, and that AoI, PAoI and delay have positive correlation given an update rate, regardless of the weight. With the goal of minimizing delay and AoI simultaneously, the weighted sum of delay and PAoI (upper bound on AoI) is formulated and proved to be convex with respect to block length and update rate. A low-complexity optimization algorithm is developed with a closed-form expression of the optimal update rate, whose performance approaches the Pareto boundaries of the PAoI-delay and the AoI-delay regions, at much lower complexity than exhaustive search.

We consider a multi-cell non-orthogonal multiple access (NOMA) system with coordinated base stations and investigate its downlink user coordination mode selection and resource allocation to green the system while maintaining high spectral efficiency, in the presence of inter-cell interference. To the best of our knowledge, this is the first work to consider multiple criteria in user coordination mode selection for coordinated NOMA systems, and a fuzzy logic (FL) based approach is proposed to balance among multiple criteria to achieve higher robustness against the combined effect of shadowing, fading and inter-cell interference, compared to the previous single-criterion-based user coordination mode selection methods. This is also the first known effort to investigate multi-subchannel resource allocation for coordinated NOMA where the previous work on coordinated orthogonal multiple access is not applicable. Two resource allocation algorithms are proposed: first, a serving channel gain based subchannel allocation (SCG-SA) algorithm, based on the theoretical proof that the total transmission power is mono-decreasing with respect to the SCG of the non-coordinated user in each cell with the highest channel gain on the shared subchannel; second, a low-complexity FL user ranking order based joint resource allocation algorithm, which requires no separate user ranking process in subchannel allocation, thanks to the FL ranking list generated from user coordination mode selection. Also, the effects of imperfect channel state information and successive interference cancellation are considered. Numerical results show that the proposed multi-criterion based schemes significantly outperform the previous schemes based on single-criterion user coordination mode selection, in terms of transmission power and energy efficiency, contributing to a greener system.

Age of information (AoI) is an effective measure of the information freshness for wireless networked control systems (WNCSs). However, the AoI performance for a closed loop of WNCS with two-way delays has remained unexplored, especially in the finite blocklength (FBL) regime. In this paper, we investigate the peak age of loop (PAoL) performances, including the average, variance and outage probability of PAoL, for WNCSs with FBL over fading channels. Their closed-form expressions are respectively derived regarding the blocklength and the maximum number of allowable transmissions. We prove that the average PAoL is less than the sum of the average peak AoI in uplink (UL) and downlink (DL) due to the coupling between UL and DL. We also show that there is a tradeoff between the average PAoL and the variance/outage probability of PAoL. Based on the comprehensive performance analysis, we study a PAoL-oriented communication and control co-design with an adaptation scheme for transmission power, blocklength and the maximum number of allowable transmissions. Simulation results verify the correctness of the analytical results and show that the proposed PAoL-oriented scheme significantly outperforms the UL only and DL only optimization schemes, with an up to 8-fold reduction in the average control cost.

The full-duplex (FD) cooperative nonorthogonal multiple access (NOMA) achieves a superior throughput over the conventional half-duplex (HD) cooperative NOMA, wherein the strong users (SUs) with good channel conditions can act as an FD relay node for the weak users with poor channel conditions. However, the energy efficiency (EE) of a cooperative NOMA may be degraded due to the additional power consumption incurred at the SUs. We are, therefore, motivated to investigate the EE maximization problem of an FD cooperative NOMA system. More importantly, we investigate the “signal-to-inference-noise ratio gap reversal” problem of cooperative NOMA systems, which imposes successive interference cancellation (SIC) performance degradation at the SUs. This problem has not been documented in the existing cooperative NOMA literature. A low-complexity algorithm is proposed for maximizing the system's EE while guaranteeing a successful SIC operation. Our numerical results show that the proposed algorithm achieves both a higher EE and throughput over the existing HD cooperative NOMA and nonadaptive FD cooperative NOMA. More importantly, the proposed scheme guarantees a successful SIC operation at the SUs.

Age of information (AoI) is an effective performance metric for time-critical industrial Internet of things (IIoT) applications. We investigate status prediction and data aggregation with prediction error awareness, to enhance the AoI performance for short-packet transmission (SPT) in time-critical IIoT. A predict-compare (PredComp) transmission scheme is proposed, where proactive transmission termination is employed in case of prediction error, by comparing the predicted and real updates at source. It is proved to achieve a significant average AoI performance gain over the case without prediction, even under high prediction error probability. In addition, a predict-aggregate-compare (PredAggComp) transmission scheme is proposed, where two status updates are predicted with different prediction horizons and aggregated by utilizing their time correlation. That allows a good tradeoff between the prediction accuracy and the transmission error probability. A closed-form threshold that the PredAggComp scheme outperforms the PredComp scheme is derived. Moreover, prediction horizon adaptation is conducted to minimize the average AoI of the proposed transmission schemes. Simulation results verify the analytical results and show the superiority of the proposed PredComp and PredAggComp schemes, with an average AoI reduction of up to 64% over the case without prediction.