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The integration of space and terrestrial networks results in a promising future network architecture, which exploits the high data rate and low latency of terrestrial networks as well as the wide-range coverage of satellite networks. However, spaceground integrated networks (SGINs) face some unprecedented challenges, including the rapidly fluctuating network topology, limited resources, intermittent connections, lossy links, asymmetric bandwidth allocation, and so on. The traditional end-to-end (E2E) transport protocols designed for reliable terrestrial networks exhibit inherent limitations in the context of dynamic SGIN. A promising solution is to decouple the E2E perfect reception confirmation into hop-by-hop acknowledgments, which results in prompt packet loss recovery and high transmission resilience in the face of high-dynamic topologies. Hence,in this paper we propose a reliable cache-enabled transport system, which enhances the efficiency of reliable hop-by-hop transmission, and supports multi-orbit breakpoint transmission, while at the same time facilitates the reliability of intra-satellite communication with a novel transport protocol. In addition to unveiling a compelling system-level design, we demonstrate the benefits of the proposed reliable transport system (RTS) in a real SGIN prototype relying on satellites having onboard processing capability. Our experimental results validate the feasibility of the proposed RTS in the face of lossy links, intermittent connections and intra-satellite transmission failure. Moreover, one of thesatellites has been launched in April 2021, while the other two will be launched to perform on-orbit test.

Frequent handover is a key challenge in 5G Ultra-Dense Networks (UDN). In this paper, we show the significance of configuring Neighbor Cell List (NCL) in handover procedure. To cope with the high dynamic of UDN, we propose an online-learning method, namely the Cost-aware Cascading Bandits NCL configuration (CCB-NCL) algorithm, which applies the cascading model and Multi-Armed Bandits (MAB) theory to configure the efficient Neighbor Cell List (eNCL) and improves the handover performance by assisting the User Equipment (UE) to choose the optimal target Base Station (BS). We provide rigorous proof of regret bound to show the asymptotic convergence of the proposed CCB-NCL algorithm. The robustness and efficiency of the proposed algorithm are both demonstrated in different network scenarios, where varies BS densities, BS dynamic and network heterogeneity are considered respectively. In the simulation work, we reproduce two existing methods of configuring NCL in handover management, named dynamic threshold based solution and received signal strength based solution. In comparison with the existing solutions, the proposed algorithm can reduce the overlarge signaling cost and unnecessary delay in the preparation phase of handover procedure by significantly shortening the length of NCLs and reducing the number of scanned BSs. Extensive simulations are conducted in different scenarios to validate the robustness of the proposed algorithm and the results show that the proposed CCB-NCL algorithm is a superior approach to efficient handover management.

Unmanned aerial vehicle (UAV) base station has been proposed as a promising solution in emergency communication and supplementary communication for terrestrial networks due to its flexible layout and good mobility support. However, the dense deployment of UAV base station and ground base station brings great challenges in the configuration of neighbor cell list (NCL) during handover process. This paper presents a Cascading Bandits based Mobility Management (CBMM) algorithm for NCL configuration in the low altitude heterogeneous networks, where online learning is used to exploiting the historical handover information. In addition to the received signal strength, the cell load of each base station is also considered in the handover procedure. We aim at optimizing the configuration of NCL, so as to improve handover performance by increasing the probability of selecting the best target base station while at the same time reducing the selection delay. It is proved that the signaling overhead can be effectively reduced, since the proposed CBMM algorithm can significantly cut down the number of candidate base stations in NCL. Moreover, by ranking the candidate base stations according to their historical performance, the number of measured base stations in handover preparation phase can be effectively reduced to avoid extra delay. The simulation results of the proposed algorithm and other two existing solutions are presented to illustrate that the CBMM algorithm can achieve efficient handover management.

To address the problems in end-to-end networks, researchers have proposed an information-centric network(ICN). In-network caching is one of the important features of ICN, which can greatly improve the efficiency of content distribution. However, the Internet Service Providers(ISP) only deploy Innetwork caching if there is some financial incentives. The existing ICN pricing mechanisms only study paid content but ignore free content in the network. In addition, the existing ICN economic models do not take into account ISP cooperating with Content Provider(CP) to deploy in-network caches. Therefore, the pricing mechanisms already in place cannot be applied in practice. In this paper, different from the existing models which based on the paid content, a new ICN pricing model with free content based on non-cooperative game theory was proposed for the first time and advertisers were effectively added to the ICN pricing model. After analyzing the behavioral relationships between entities within the network, the authors establish the utility function for each entity. The authors analyze the impact of caching and pricing on the revenues of all entities and solve the equilibrium point to develop win-win pricing strategies. Considering the case where paid content coexists with free content in real networks, the authors proposes a more realistic and integrated model. In this paper, many experimental analyses have been conducted in addition to the theoretical analysis, and the experimental results show that the new model is closer to reality than the existing models and can provide better theoretical guidance for network pricing.

In this work we analyze the performance of a full-duplex (FD) multi-cell network where Poisson point process (PPP) distributed half-duplex (HD) users are served by FD base stations (BSs). The use of FD BSs instead of traditional half-duplex (HD) ones results in a surge in the amount of interference present in the network. In order to address this challenge we, (a) adopt a self-interference (SI) cancellation scheme at each BS, (b) apply linear interference alignment (IA) in each cell to cancel out intra-cell interference, and (c) model the distribution of the BSs as a Matern hard-core point process (HCPP) to mitigate inter-cell interference. The performance of both downlink (DL) and uplink (UL) users is analyzed by deriving general expressions, and easily computable good approximations for the ergodic capacity of each type of user.

In this paper, we analyze the performance of a cloud radio access network (CRAN), consisting of multiple randomly distributed remote radio heads (RRHs) and a macro base station (MBS), each equipped with multiple antennas. To model the spatial distribution of RRHs and analyze its performance, we use stochastic geometry tools. In contrast to previous works on CRAN that consider Poisson Point Process (PPP) model for the spatial distribution of RRHs, we consider a more realistic Matern hard-core point process (MHCPP) model that imposes a certain minimal distance (referred to as hard-core distance) between the two RRHs so that the RRHs are not too close to each other. To compare system performance of CRAN when different transmission strategies are used, three RRH selection schemes are adopted including 1) the best RRH selection (BRS); 2) all RRHs participation (ARP); and 3) nearest RRH selection (NRS). Considering downlink transmission, the ergodic capacity, outage probability, and system throughput of CRAN are analytically characterized for different RRH selection schemes. The presented results demonstrate that compared to PPP model, the increase in hard-core distance will result in a higher outage probability and cause a negative impact on ergodic capacity. Furthermore, when the same total transmit power is consumed, BRS scheme provides the best outage performance while ARP scheme is the best RRH selection scheme when the same transmit SNR at each RRH is assumed. Moreover, it is shown that the hard-core distance has a more significant impact on systems with higher intensity of PPP distributed candidate points and in large hard-core distance regime increasing the intensity of candidate points can only provide a small improvement in outage performance. We extend our work to multiuser case with zero-forcing (ZF) precoding where it is proven that the results in multiuser case reduce to the derived results in this work by substituting K=1 for single-user.

In this paper, we analyse the performance of a millimeter wave (mmWave) cloud radio access network (CRAN), where remote radio heads (RRHs) are modelled as a homogeneous Poisson point process (PPP) and blockages are randomly distributed. In contrast to the previous works on CRAN that operate below 6GHz, we consider CRAN operating in mmWave range (30-300 GHz). Since blockages have a significant impact on mmWave communications, we adopt a distance-dependent line-of-sight (LOS) probability function and model the locations of the LOS and non-line-of-sight (NLOS) RRHs as two independent non-homogeneous PPP. The outage performance and ergodic capacity of the LOS and NLOS RRHs are analysed and compared. When the RRH with the best channel is selected for transmission, the expressions of outage probability and throughput are provided. The presented results show that due to the severe path loss in NLOS links, in low transmitted power regime, the best RRH (BR) is always LOS. However, in high transmitted power regime, NLOS RRHs can be BR.

In this paper, the performance of a cloud radio access network (CRAN) is analysed, which consists of multiple randomly distributed remote radio heads (RRHs) and a macro base station (MBS). Different from previous works on CRAN where Poisson Point Process (PPP) is used to model spatial distribution of RRHs, a more realistic Matern Hard-core point process (MHCPP) model is adopted in this work. To compare system performance of CRAN when different transmission strategies are used, two RRH selection schemes are adopted including 1) the best RRH selection (BRS) and 2) all RRHs participation (ARP). Considering downlink transmission, the outage probability and system throughput of CRAN are analytically characterized. The presented results demonstrate that compared to PPP model, the presence of hard-core distance will increase outage probability. Furthermore, the BRS scheme is more energy-efficient than the ARP scheme. Moreover, it is shown that the hard-core distance has a more significant impact on systems with higher intensity of PPP distributed candidate points and in large hard-core distance regime increasing the intensity of candidate points can only provide a small improvement in outage performance.

In this paper, the performance of cloud radio access networks (CRANs) where spatially distributed remote radio heads (RRHs) aid the macro base station (MBS) in transmission is analysed. In order to reflect a realistic scenario, the MBS and the RRHs are assumed to be equipped with multiple antennas and distributed according to a Poisson point process. Both, the MBS and the RRHs, are assumed to employ maximal ratio transmission (MRT) or transmit antenna selection (TAS). Considering downlink transmission, the outage performance of three schemes is studied; first is the selection transmission (ST) scheme, in which the MBS or the RRH with the best channel is selected for transmission. In the second scheme, all the RRHs participate (ARP) and transmit the signal to the user, whereas in the third scheme, a minimal number of RRHs, to attain a desired data-rate, participate in transmission (MRP). Exact closed-form expression for the outage probability is derived for the ST scheme. For the ARP and MRP schemes, analytical approximations of the outage probability are derived which are tight at high signal-to-noise ratios. In addition, for the MRP scheme, the minimal number of RRHs required to meet a target data rate is also calculated which can be useful in characterizing the system complexity. Furthermore, the derived expressions are validated through numerical simulation. It is shown that the average diversity gains of these schemes are independent of the intensity/number of RRHs and only depend on the number of antennas on the MBS. Furthermore, the ARP scheme outperforms the ST scheme when the MBS/RRHs transmit with maximum power. However, in case of a sum power constraint and equal power allocation, the ST scheme outperforms the ARP scheme.