A survey on fronthaul signaling of user-centric cell-free massive MIMO networks

Due to the new characteristics of ultra-dense networks (UDN), such as high dense deployment of wireless access points (APs), complicated handover signaling processes and irregular coverage, how to achieve mobility support and reduce user's interrupt ratio remain a difficult problem. To address these issues, based on the presented user-centric APs clustering (UCC) network architecture in UDN, a UCC method is proposed. In the scheme, with dynamic refreshment of the UCC member, a user equipment (UE) moves as if it is surrounded by the connected APs and the AP-to-AP handover is concealed. In order to provide UE with satisfactory services, the UCC is formulated based on the joint transmission benefit. Additionally, UCC member refreshing algorithm is designed to facilitate seamless connectivity with new APs. Finally, performance analysis is done. Compared to the anchor-based scheme, we simulate our scheme from three aspects, including interrupt ratio, spectral efficiency and user average rate.

The ultra-dense network (UDN) is one of the most promising technologies in the fifth generation (5G) to address the network system capacity issue. However, it is a new challenge that the user equipment (UE) secure access UDN composed of the access points (APs) which characterized with autonomy, temporary, and dynamic. In 5G UDN, the APs are independent and equal. The UDN can be regarded as a decentralized access network. Compared with the traditional base station, the AP has a smaller coverage. There has an issue that the interaction between the UE and APs will be more frequent when UE moves. However, the existing 4G authentication and key agreement algorithm cannot adapt to this fast and frequent authentication requirement. If the UE moves smoothly in a trusted APs group (APG) without frequent authentication, this problem will be solved very well. In order to achieve this goal, we propose a security authentication scheme of 5G UDN based on the block chaining technologies. In this paper, an APG-PBFT algorithm based on the block chaining technology with Byzantine fault tolerance (PBFT) consensus algorithm is proposed. In the algorithm, the consensus mechanism will be optimized and a new reverse screening method will be embedded. In our solution, a trusted chain APG can be generated with APs by APG-PBFT algorithm, and the authentication results can be shared in the APG using the blockchain message propagation mechanism. The principle of fast authentication with APG-PBFT algorithm is present in this paper. The scheme can reduce the authentication frequency when UE moves among the APs and improve the access efficiency. Finally, we analyze the performance of APG-PBFT algorithm and compare it with the traditional PBFT algorithm. The simulation results show that the APG-PBFT algorithm can improve the APG generation efficiency and reduce the authentication frequency of UE, which will be valuably applied to the UDN environment.

Ultra-dense network (UDN) has been considered as one of the advanced technologies in 5G. With the increasing requirements on quality of service (QoS), large numbers of connections and very high area throughput density, various access points (APs) are deployed densely to provide desired services to user terminals. Then how to choose the optimal AP among neighbor candidate APs for accessing to the network is an interesting problem. Meanwhile, some research work has pointed out that the backhaul capability may become the bottleneck for UDN. Therefore, the backhaul links should be considered when making the accessing decision. However, there is few well recognized solution so far. In this paper, we investigate the energy-efficient access scheme in UDN, with joint consideration on backhauling capability. On the basis of the proposed UDN architecture, an access evaluation model is set up with flexible weight adjustment on delay and power consumption of the candidate AP's backhaul links. Then, the resource allocation problem is formulated with joint scheduling on time slot, subchannel and power to optimize system energy efficiency. Simulation results have proven that compared with traditional access algorithm, our proposed scheme has obvious improvement in the performance.

The amorphous multi-connected networks have e-merged as a new trend to meet the fast increasing wireless capacity and coverage demands of future 5G networks. To realize such amorphous networks, ultra dense network (UDN) technology is expected as a promising candidate for its flexible network architecture and abundant radio resources. Yet, the multi-connection optimization for UDN is still left as an open problem nowadays. This motivates us to explore how many and which access points (APs) should be accessed in multi-connected amorphous UDNs. To solve this problem, we introduce a new definition of the maximum number of accessed APs for help, and propose two algorithms to identify this number and handle the AP selection respectively. Monte Carlo simulations testify the validity of our scheme and prove that our strategy can guarantee the soft handover and overcome the “ping-pong effect” efficiently in various kinds of networks with high sum-rate performance.

Chapter 2 - High data rates in mobile communication

SummarySmall cell networks can fulfill the increasing demandfor the high data rate of wireless applications. Energy efficiency is an important design parameter of the ultra dense small cell network (UDSCN). The sleeping strategy of small base stations (s‐BSs) is used to enhance the network's energy efficiency. An efficient sleeping strategy of s‐BSs is required while preserving users' quality of service (QoS). The idle s‐BSs can be switched to sleep mode. This paper proposes a blockchain‐enabled solution for the sleeping strategy of s‐BSs. Here, a blockchain‐enabled small cell network is created between the s‐BSs. The network is decentralized, which eliminates the workload of the macro base station (MBS). The proposed network architecture is enabled as a decentralized network through blockchain. The blockchain provides distributed control over the s‐BS operations through a smart contract. Here, smart contracts act as distributed self organizing network features to handle self‐transactions among small cells for switching off s‐BSs in the network. All the software logic required to perform s‐BS operations is written in a smart contract using Ethereum. The proposed solution improves energy efficiency and enables the ultra dense small cell network to be decentralized.

This paper propose an iterative inter-cell interference coordination strategy to meet the requirements of the next generation mobile communication systems, which are higher data rate, broader coverage, especially more stringent demand on cell edge spectral efficiency. Sector cooperation is introduced in MU MIMO (multi-user multiple input multiple output) systems. In the aspect of user pairing, both the system capacity and fairness among users are taken into consideration through pairing center and edge users. As for the inter-cell interference coordination, iterative sector cooperation on selecting pre-coders from code books is implemented, in order to avoid inter-cell interference and improve cell edge performance. Theoretical analysis and simulation results demonstrate that the proposed strategy can significantly improve cell edge throughput while guaranteeing the performance of average cell spectrum efficiency.

Within the foreseeable future, the growing number of mobile devices, and their diversity, will challenge the current network architecture. Furthermore, users will expect greater data rates, lower latency, lower packet drop rates, etc. in future wireless networks. Ultra Dense Networks (UDN), considered to be one of the best ways to meet user expectations and support future wireless network deployment, will face multiple significant hurdles, including interference, mobility, and cost. In this paper, we review existing research efforts toward addressing those challenges and present future avenues for research. We first develop a taxonomy to review and describe existing research efforts. Next, we focus on inter-cell interference, handover performance, and energy efficiency as the key techniques to addressing the most pressing challenges. Finally, we present several future research directions, including emergent Internet-of-Things (IoT) applications, security and privacy, modeling and realistic simulations, and relevant techniques.

Solving the main optimization problem, including a large number of access points and user equipment in ultra-dense networks (UDNs) using the Munkres algorithm, is a time-consuming solution. In this paper, we propose two new ideas for selecting the appropriate access points (APs) in UDNs that reduce the complexity order and find the suboptimum solution efficiently. Applying the first idea, all user equipment (UE) that are out of access points' service area and all access points that cannot find any user equipment in their service area are removed. In this case, the solutions of the conventional and proposed version of the Munkres algorithm are the same, which offers a high total sum value of the signal to noise ratios (SNRs). Still, it does not guarantee minimum interference. Hence, as the second idea, we consider estimation of the signal to interference plus noise ratio (SINR), entitled by average-SINR and random-SINR, and solve the optimization problem, including a large number of access points and a variable number of user equipment densely distributed. The simulation results show the effectiveness of the proposed algorithms in the view of sum-rate, the number of successful user equipment, and computational complexity for an area, including 250 APs and a variable number of UEs.

LTE uses single carrier-frequency division multiple access (SC-FDMA) scheme for the uplink transmission which limits the flexibility of the allocation process as the sub carriers assigned to a single user have to be contiguous. We propose an LTE uplink interference-aware search-tree based scheduling scheme using the high interference indicator (HII) and the overload indicator (OI) messages that are exchanged over the X2-interface. HII indicates the potential uplink inter-cell interference (ICI) to other cells while OI indicates the detection of low, medium or high uplink ICI from other cells. The exchanged HII and OI messages are used to scale down the proportional-fair (PF) scheduling metric before being processed by the search-tree scheduler to make interfered physical resource blocks (PRBs) less favorable to cell-edge (CE) UEs. Unlike previous work which handles these problems separately, the proposed integrated RRM framework jointly takes into account 1) interference information exchanged between neighbor eNBs, 2) constraints on max power per UE and equal power on different PRBs, and 3) constraints on the contiguity in PRBs allocation due to SC-FDMA mechanism. It is also fully integrated with the LTE uplink open and closed-loop fractional power control for proper power allocation. The proposed interference-aware scheduler reduces the effect of the generated ICI mainly on CE users and also manages to provide fair resource sharing between CE and cell-center (CC) users. Simulation results show that the proposed framework improves CE users' throughput by around 5% compared to soft frequency reuse (SFR). It also reduces the probability of not being served to 1% -- compared to 10% in SFR.

Due to the high splitting-gain of dense small cells, Ultra-Dense Network (UDN) is widely regarded as a promising networking technology to achieve high data rate and low latency in 5G mobile communications. In UDNs, user association is an open NP-hard problem due to the high computational complexity. In this paper, we study the user association problem from a deep learning perspective. We propose a U-Net based deep learning scheme aimed at intelligently associating user equipments(UE) to the competing Macro Base Stations (MBS) and small Base Stations (SBS). We formulate the user association problem as a constrained combinatorial optimization problem and employ a cross-entropy algorithm to obtain its asymptotically optimal solution for labelling in supervised learning. We define a differentiable loss function by combining the Mean Squared Errors(MSE) criterion and the fairness and load balancing constraints for the supervised deep learning framework. We first train the U-Net based learning model and then evaluate the accuracy of the proposed scheme. Simulation results show that the proposed U-Net scheme approaches the asymptotically optimum Genetic Algorithm (GA) scheme in terms of minimum rate gain and sum rate gain, whereas outperforms the latter with significantly reduced computation time and robustness to network scales.

A survey on user-centric cell-free massive MIMO systems

In ultra dense WiFi networks, access points are deployed with high density in order to support Internet access for large amount of mobile users at the same time. Since the mobile users may not be uniformly distributed in the network, the heavy loaded access points and the interference among different access points would cause the network throughput degradation. Further, although increasing transmission power levels of access points could enhance network throughput, the energy efficiency would be low. Energy consumption is an increasingly important issue today so that the network performance needs to be improved in an energy efficient manner. Under this condition, we propose a distributed power adjustment scheme to intelligently maximize the throughput of the entire network without increasing transmission power in the presence of dynamic distributed mobile users. To validate the performance of our proposed scheme, we simulate various network conditions and the results show that our proposed scheme can sustain throughput with less energy consumption with less than 200 iterations.

Introduction. The Russian telecommunications industry is on the threshold of introducing 5G/IMT-2020 (5G) mobile communications. The expected technological innovations of the new generation standard will lead to an increase in the capacity of mobile operators ‘ networks, data transfer speeds, the emergence of new scenarios for the use of mobile communications and the development of innovative digital services. This will contribute to economic growth by increasing labour productivity, automation and introducing new technologies in various economy and human activity areas. At the same time, the electromagnetic environment (EMO) in the areas where people stay will also change. The purpose of the study is to consider the unique features of the architecture of the 5G network to predict the impact on the population of electromagnetic fields (EMF) of the radio frequency (RF) range. Material and methods. The study is analytical. The information base of the research was Russian strategic documents on the development of 5G technologies, articles published in domestic and foreign journals. Results. The primary input data for the construction of 5G networks are presented, allowing us to evaluate EMO and identify the new technology features that are significant in terms of the impact of RF electromagnetic fields on the population. The 5G network uses previously unused RF bands and new types of antennas. With the introduction of 5G, the density of base stations (BS) and access points will significantly increase, the heights of BS antennas will decrease, and the spatial and temporal characteristics of electromagnetic radiation will change substantially. Conclusion. The architecture of the 5G network differs significantly from the mobile communication standards of previous generations. The introduction of 5G networks will lead to a significant change in the electromagnetic background in the environment. An urgent task is to develop a theory of hygienic regulation of RF EMF for the population in a complex electromagnetic environment with simultaneous operation of 5G networks and previous generations and new approaches to determining the levels of EMF in the environment by computational and instrumental methods.

Interference management has been a key concept for designing future high data-rate wireless systems that are required to employ dense reuse of spectrum. Static or semi-static interference coordination based schemes provide enhanced cell-edge performance but with severe penalty to the overall cell throughput. Furthermore, static resource planning makes these schemes unsuitable for applications in which frequency planning is difficult, such as femtocell networks. In this paper, we present a novel dynamic interference avoidance scheme that makes use of inter-cell coordination in order to prevent excessive inter-cell interference, especially for cell or sector edge users that are most affected by inter-cell interference, with minimal or no impact on the network throughput. The proposed scheme is comprised of a two-level algorithm - one at the base station level and the other at a central controller to which a group of neighboring base stations are connected. Simulation results show that the proposed scheme outperforms the reference schemes, in which either coordination is not employed (reuse of 1) or employed in a static manner (reuse of 3 and fractional frequency reuse), in terms of cell edge throughput with a minimal impact on the network throughput and with some increase in complexity.