The integration of sub-6 GHz and millimeter wave (mmWave) bands has a great potential to enable both reliable coverage and high data rate in future vehicular networks. Nevertheless, during mmWave vehicle-to-infrastructure (V2I) handovers, the coverage blindness of directional beams makes it a significant challenge to discover target mmWave remote radio units (mmW-RRUs) whose active beams may radiate somewhere that the handover vehicles are not in. Besides, fast and soft handovers are also urgently needed in vehicular networks. Based on these observations, to solve the target discovery problem, we utilize channel state information (CSI) of sub-6 GHz bands and Kernel-based machine learning (ML) algorithms to predict vehicles' positions and then use them to pre-activate target mmW-RRUs. Considering that the regular movement of vehicles on almost linearly paved roads with finite corner turns will generate some regularity in handovers, to accelerate handovers, we propose to use historical handover data and K-nearest neighbor (KNN) ML algorithms to predict handover decisions without involving time-consuming target selection and beam training processes. To achieve soft handovers, we propose to

In this paper, performance of hybrid automatic repeat request with incremental redundancy (HARQ-IR) over Rayleigh fading channels is investigated. Different from prior analysis, time correlation in the channels is considered. Under time-correlated fading channels, the mutual information in multiple HARQ transmissions is correlated, making the analysis challenging. By using polynomial fitting technique, probability distribution function of the accumulated mutual information is derived. Three meaningful performance metrics including outage probability, average number of transmissions and long term average throughput (LTAT) are then derived in closed-forms. Moreover, diversity order of HARQ-IR is also investigated. It is proved that full diversity can be achieved by HARQ-IR, i.e., the diversity order is equal to the number of transmissions, even under time-correlated fading channels. These analytical results are verified by simulations and enable the evaluation of the impact of various system parameters on the performance. Particularly, the results unveil the negative impact of time correlation on the outage and throughput performance. The results also show that although more transmissions would improve the outage performance, they may not be beneficial to the LTAT when time correlation is high. Optimal rate design to maximize the LTAT is finally discussed and significant LTAT improvement is demonstrated.

This paper analyzes the performance of cooperative hybrid automatic repeat request with incremental redundancy (HARQ-IR) and proposes a new approach of outage probability approximation for performance analysis. A general timecorrelated Nakagami fading channel covering fast fading and Rayleigh fading as special cases is considered here. An efficient inverse moment matching method is proposed to approximate the outage probability in closed-form. The effect of approximation degree is theoretically analyzed to ease its selection. Moreover, diversity order of cooperative HARQ-IR is analyzed. It is proved that diversity order is irrelevant to the time correlation coefficient ρ as long as ρ < 1 and full diversity from both spatial and time domains can be achieved by cooperative HARQ-IR under time-correlated fading channels. The accuracy of the analytical results is verified by computer simulations and the results reveal that cooperative HARQ-IR scheme can benefit from high fading order and low channel time correlation. Optimal rate selection to maximize the long term average throughput given a maximum allowable outage probability is finally discussed as one application of the analytical results.

Cognitive radio technologies enable users to opportunistically access unused licensed spectrum and are viewed as a promising way to deal with the current spectrum cri-sis. Over the last 15 years, cognitive radio technologies have been extensively studied from algorithmic design to practical implementation. One pressing and fundamental problem is how to integrate cognitive radios into current wireless networks to enhance network capacity and improve users' experience. Unfortunately, existing solutions to cognitive radio networks (CRNs) suffer from many practical design issues. To foster further research activities in this direction, we attempt to provide a tutorial for CRN architecture design. Noticing that an effec-tive architecture for CRNs is still lacking, in this tutorial, we systematically summarize the principles for CRN architecture design and present a novel flexible network architecture, termed cognitive capacity harvesting network (CCHN), to elaborate on how a CRN architecture can be designed. Unlike existing architectures, we introduce a new network entity, called secondary service provider, and deploy cognitive radio capability enabled routers, called cognitive radio routers, in order to effectively and efficiently manage resource harvesting and mobile traf-fic while enabling users without cognitive radios to access and

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In D2D-enabled cellular networks, data communications between user equipments (UEs) can be completed by two modes: the cellular mode and the D2D mode where UEs bypass the base station and directly communicate with each other. Usually the transmission mode is selected based on the distance between the UEs. In this paper, the feasible D2D communication distance, i.e., the maximum allowable distance for D2D communications, in a D2D-enabled cellular network is analyzed. To proceed, the coverage probabilities of the cellular and the D2D modes are first derived in closed-forms. Different from prior studies, both the uplink and the downlink transmissions are considered when analyzing the coverage probability of the cellular mode and multi-cell interference is also taken into account in the analysis. Based on the analytical results on the coverage probabilities, the maximum allowable distance for D2D communications is then given in closed-form. The impacts of various system parameters on the maximum allowable distance for D2D communications are finally discussed. The analytical result theoretically justifies the traffic offloading function of D2D communications and shows that D2D communications is applicable especially for modern cellular communication networks where base stations are densely deployed. It also provides an effective guidance on mode selection in D2D-enabled cellular networks. I. INTRODUCTIOND2D communications has attracted much attention recently due to its potential of increasing the network's spectrum and energy efficiency. Its effectiveness has been demonstrated in various works [1]- [3]. Data transmission in D2D-enabled cellular networks can be conducted in two different modes: cellular mode and D2D mode. When operating in the cellular mode, the data is relayed through the cellular network, while in D2D mode the data is directly transmitted to the intended user without the relaying by the base station [4], [5]. In order to enhance the network throughput, the transmission mode should be properly selected [4], [5]. Generally speaking, when two users are close to each other, direct communications between them might offer higher throughput and lower latency than the relaying communications via base stations. A proper selection between the cellular and D2D modes could offer a notable throughput enhancement and the feasible D2D communication distance, i.e., the maximum allowable distance for D2D communications, is vital to the identification of potential D2D pairs and the mode selection [3]- [5]. Despite its importance, till now, unfortunately, the analysis of the feasible D2D communication distance is still lacking.

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