Cognitive Internet of Vehicles (CIoV) is an intelligent vehicle network envisioned to opportunistically access spectrum licensed to primary users (PUs) on the premise of not interrupting their normal communications. Dynamic spectrum access enables the CIoV to choose the best possible spectrum for communications based on the outcomes of spectrum data sensing, which can improve the spectrum access performance effectively. In this paper, we enable the CIoV to adapt to various spectrum states through: a) a collaborative big spectrum data sensing scheme to sense a massive amount of spectrum data; and b) a reinforcement learning (RL) based dynamic spectrum access scheme to optimize spectrum selection strategies. Q-learning, which is a popular RL approach, is proposed for underlay, overlay, and collaborative spectrum access modes to allocate spectrum resources to the CIoV intelligently. The Q-learning models, which include the spectrum state vector, the action vector of CIoV, and the spectrum access reward received in different spectrum situations, are defined for the spectrum access modes. A Q-learning based spectrum access algorithm is proposed to improve the communication performance of the CIoV in different spectrum access modes. Simulation results indicate that the collaborative spectrum access mode can achieve higher average throughput, lower interference power and lower communication outage compared with the underlay and overlay spectrum access modes.

The cognitive industrial Internet of Things (CIIoT) can improve transmission performance by utilizing the spectrum licensed to a primary user (PU), providing that the normal communication of the PU is not disturbed. However, the traditional spectrum access schemes for the CIIoT are difficult to adapt to the various communication environments. In this article,$Q$-learning-based dynamic spectrum access is proposed for the CIIoT to intelligently utilize the spectrum resources in three access scenarios: orthogonal multiple access (OMA), underlay spectrum access, and nonorthogonal multiple access (NOMA). In the OMA scheme, the CIIoT learns to access the idle channels to avoid distributing the PUs, but its communication continuity cannot be guaranteed when most of the channels are occupied by the PUs. In the underlay scheme, the CIIoT learns to utilize the busy channels to ensure the communication continuity by limiting its transmit power within the tolerance of the PU. However, the interference to the PU cannot be eliminated, which will decrease the PU’s throughput. In the NOMA scheme, however, the CIIoT can utilize the busy channels by canceling the interference to the PU with successive interference cancellation, which will guarantee the transmission performance of both the CIIoT and the PU. A$Q$-learning-based spectrum access algorithm is proposed to improve the transmission performance of the CIIoT in the three schemes. The simulation results have shown the advantages of the$Q$-learning-based NOMA scheme in terms of guaranteeing the throughput of the CIIoT nodes and decreasing the interference to the PUs.

With the rapid increase of industrial systems, industrial spectrum is stepping into the era of big data, and at the same time spectrum resources are facing serious shortage. Cognitive industrial system (CIS) based on cognitive radio can improve spectrum utilization by accessing the idle spectrum licensed to primary user. However, the CIS must find enough idle channels by performing spectrum sensing. In this article, a reinforcement learning-based multislot double-threshold spectrum sensing with Bayesian fusion is proposed to sense industrial big spectrum data, which can find required idle channels faster while guaranteeing spectrum sensing performance. Double thresholds are set to guarantee both high detection probability and spectrum access probability, and weighed energy detection is proposed to maximize detection probability when the energy statistic falls into the confusion area between the double thresholds. Bayesian fusion is proposed to get a final decision on the channel availability by combining the local sensing decisions of all the time slots. A prediction and selection algorithm for idle channels is proposed to predict the idle probability of each channel and find required idle channels from the sorted channel set. From simulation results, the proposed spectrum sensing scheme outperforms cooperative spectrum sensing and energy detection, which can predict idle channels accurately and get needed idle channels with fewer sensing operations.

A distributed interference coordination scheme is proposed to alleviate cross‐tier and inner‐tier interference in heterogeneous network (HetNet), consisting of a power control strategy based on game theory to acquire both Nash equilibrium among femtocells and Stackelberg equilibrium between femtocells and macrocells. Component carrier assignment is the other interference coordination dimension for HetNet with carrier aggregation. The proposed method is a two‐dimensional interference coordination scheme combining power control and component carrier assignment. The simulation results demonstrate the effectiveness and improvement of the proposed scheme.

In this paper, we study energy efficient orthogonal frequency division multiplexing (OFDM) relay system, where two source nodes communicate with each other via a half-duplex amplify-and-forward relay node. We aim to maximize the energy efficiency (EE), where both the transmit and circuit power consumptions are taken into consideration. To this end, we optimize the active number of subcarriers and the number of bits to each subcarrier at the two source nodes. The optimal solution turns out to be a bidirectional water-filling bit allocation to minimize the overall transmit power, and a subcarrier reduction algorithm to balance the transmit and circuit power consumptions. When the data amounts at the two source nodes are unequal, the bidirectional water-filling leads to a hybrid one- and two-way relaying strategy, which employs one-way relaying on some subcarriers and two-way relaying on some of the other subcarriers. Simulation results demonstrate that the hybrid one- and two-way relaying with subcarrier reduction, which is optimized towards EE, is more energy efficient than that without subcarrier reduction, which only minimizes the transmit power.

In this paper, we design energy efficient relay transmission strategy in a system where two source nodes transmit to each other assisted by an amplify-and-forward relay node. We first compare the energy efficiencies (EEs) between one-way relay transmission (OWRT) and two-way relay transmission (TWRT), which shows that when the bidirectional data amounts are equal, TWRT performs better, otherwise, OWRT may offer higher EE. To achieve the maximal EE in various settings, we propose hybrid relay transmission (HRT) that transmits partial messages with OWRT and the remaining messages with TWRT, and jointly optimize the data amounts and transmission time allocated to the OWRT and TWRT parts. Simulation results show the superiority of the HRT over both OWRT and TWRT.

In this paper, we compare the energy efficiencies (EEs) of direct transmission (DT), one-way relay transmission (OWRT) and two-way relay transmission (TWRT) in a system where two sourcie nodes transmit to each other and may be assisted by an amplify-and-forward relay node. We first find the maximum EEs of DT, OWRT and TWRT by jointly optimizing the transmission time and the transmit powers at each node. Then we compare the maximum EEs of the three strategies, and analyze the impact of circuit powers and bidirectional data amounts. Analytical and simulation results show that relaying is not always more energy efficient than DT. The EE of TWRT is higher than those of DT and OWRT when the bidirectional data amounts are equal. Otherwise, the advantage of TWRT diminishes, while either DT or OWRT may provide higher EE.

In this paper, we design energy efficient relay transmission strategy for an orthogonal frequency division multiplexing (OFDM) system, where two source nodes exchange information with each other via an amplify-and-forward relay node. To maximize the energy efficiency (EE), which is defined as the number of transmitted bits per unit of energy, we jointly optimize the bidirectional bit allocation, which leads to a hybrid one- and two-way relay scheme. In particular, we propose a bit allocation algorithm to balance the transmit and circuit power consumptions of the hybrid relay in order to minimize the overall power consumption. Simulation results show that the proposed algorithm achieves much higher EE than the approach that only minimizes the transmit power, and the hybrid relay is more energy efficient than the pure one- and two-way relay.

In this paper, we design interference free transceivers for multi-user two-way relay systems, where a multi-antenna base station (BS) simultaneously exchanges information with multiple single-antenna users via a multi-antenna amplify-and-forward relay station (RS). To offer a performance benchmark and provide useful insight into the transceiver structure, we employ alternating optimization to find optimal transceivers at the BS and RS that maximizes the bidirectional sum rate. We then propose a low complexity scheme, where the BS transceiver is the zero-forcing precoder and detector, and the RS transceiver is designed to balance the uplink and downlink sum rates. Simulation results demonstrate that the proposed scheme is superior to the existing zero forcing and signal alignment schemes, and the performance gap between the proposed scheme and the alternating optimization is minor.

Two-way relay transmission (TWRT) is more spectral efficient than direct transmission (DT) and one-way relay transmission (OWRT). In this paper, we try to find out if TWRT is also more energy efficient in practice. To this end, we first derive and compare the energy efficiency of DT, OWRT and TWRT systems, when either the receiver processing power consumption is taken into account or not. We then compare the maximal energy efficiency achieved by TWRT and OWRT, as well as the corresponding spectral efficiency. Both analytical and simulation results show that TWRT is not always more energy efficient than DT and OWRT, depending on the channel condition, processing power consumption and the bidirectional date rate requirements. Generally speaking, in high spectral efficiency and large path loss attenuation region, the TWRT provides high energy efficiency.

In this paper, we study a multi-user multi-antenna two-way relay system, where a multi-antenna base station (BS) exchanges uplink and downlink signals with multiple users via a multi-antenna amplify-and-forward relay station (RS). We jointly design the BS and RS transceivers, aiming to maximize the system bidirectional sum rate under inter-user interference free constraint. Since the optimization problem is non-convex, we employ alternating optimization algorithm to design the transmit and receive weighting matrices at the BS and RS. Simulation results show that the proposed solution offers higher bidirectional sum rate than existing schemes.

In this paper, we design transceivers in a multi-user multi-antenna two-way relay system, where a single multi-antenna base station exchanges information with multiple users via a single multi-antenna relay station. We consider the half-duplex amplify-and-forward relay protocol. We aim to maximize the bidirectional sum rate under the constraint of no interference among different users. Suboptimal solutions to the problem that respectively maximizing the uplink and downlink rates are derived. We then introduce a threshold to balance the uplink and downlink rates so as to maximize the bidirectional sum rate. Simulation results show that the proposed scheme achieves considerably higher bidirectional sum rate than existing schemes.