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Non-Orthogonal Multiple Access (NOMA) and Fractional Frequency Reuse (FFR) were touted as two key techniques of the millimetre wave cellular system to derive spectrum efficiency and user performance improvement. By combining the NOMA and FFR techniques, this paper proposes a system to improve the performance of the NOMA user that utilises the NOMA-power domain technique to reuse an occupied Resource Block (RB). Besides following the power allocation policy of the NOMA technique, the resource allocation algorithm for the NOMA user is based on the FFR technique. Particularly, if the downlink Signal-to-Interference-plus-Noise ratio (SINR) of the NOMA user is greater than the threshold, it is allocated the Cell-Edge RB with a high interference level. Otherwise, it is served on the Cell-Center RB with a low interference level. The analytical and simulation results state that the proposed system can increase the coverage probability of the NOMA user up to 250%. [ABSTRACT FROM AUTHOR]

In ultra dense networks (UDNs), a large number of small-cell base stations (SBSs) are densely deployed in hotspots, e.g., office buildings, residential apartments, shopping malls, etc. Thus, SBSs have more serious interference between them in UDNs than they have in heterogeneous networks (HetNets) and it is a crucial issue to assign subchannels with consideration of the interference to satisfy the demands of small-cell user equipments (SUEs) for UDNs. In this paper, I propose a novel dynamic channel assignment (DCA) scheme named fairness based dynamic channel assignment (FDCA) to improve the system capacity of SUEs with guaranteeing the fairness for the downlink of in-building UDNs based on orthogonal frequency division multiple access-frequency division duplex. In the proposed FDCA scheme, a network controller unit first generates an interference matrix using channel state information from SUEs in UDNs and then it fairly assigns different numbers of subchannels to SUEs through their serving SBSs based on the interference matrix and optimal values of the signal to interference plus noise ratio threshold. Through simulation results, I show that the proposed FDCA scheme outperforms other DCA schemes using graph coloring algorithm in terms of the fairness with the reduced mean SUE capacity slightly. That is, the mean SUE capacity of the proposed FDCA scheme decreases 1 ∼ 5% than that of other schemes while the fairness index of it increases 16 ∼ 21% when the numbers of SBSs and SUEs are 25 and 100, respectively. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Jiangsu University (Natural Science Edition) / Jiangsu Daxue Xuebao (Ziran Kexue Ban) is the property of Editorial Department of Journal of Jiangsu University (Natural Science Edition) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This letter proposes a method for gradually calibrating channel non-reciprocity in an ultra-dense cell-free massive multiple-input multiple-output (MIMO) system. Many studies assume perfect channel reciprocity in time division duplex (TDD) systems. However, reciprocity is not valid in actual channels. Therefore, determining the reciprocity-calibrated precoding matrix is important for the performance of the network. In a cell-free massive MIMO system, user equipment (UE) is served by many access nodes (ANs). Since there are many nodes, it is difficult to calibrate the matrix simultaneously. Using the proposed method, the network sequentially calibrates the precoding matrix in order of influence. Thus, the proposed method can obtain a large gain compared to a system without calibration by performing only minimal channel calibration. To show the capacity gain of the proposed method, a simulation was performed considering the overhead required for channel calibration. [ABSTRACT FROM AUTHOR]

With the increasing development of communication technology, ultra-dense network (UDN) becomes to be the key technology in the fifth generation (5G) communication. More and more small cells appear in the UDN, which leads to serious interference to harm network performance. To solve this problem, this paper proposes a novel scheme with clustered priority-based user-centered interference coordination (CPUCIC). User performance is improved with base station collaboration and interference nulling in the respective cluster area. Numerical results show that related performances with CPUCIC scheme can be improved with respect to signal to interference plus noise ratio (SINR) and spectrum efficiency (SE). Furthermore, its performance improvement is greater than bandwidth cost in most cases, which metrics is user bandwidth gain-to-loss ratio (UBGLR). [ABSTRACT FROM AUTHOR]

Ultra Dense Networks with flexible heterogeneous technologies (HetUDN) for the Radio Access Network (RAN) are prospective candidate architectures that promise to bring the required network flexibility and to support the transition to 5G networks. In the same time, Multi-access Edge Computing (MEC) is a recent paradigm shift that pushes the main focal point of mobile systems from centralized Mobile Cloud Computing (MCC) towards the network edge. Network softwarization enables the operation of new computational elements such as base stations and access points at the MEC, whereas edge computing, network control and storage promise to enable computation-intensive and latency-critical applications for resource constrained mobile devices. In this paper, we employ a novel disaggregated 5G architecture and apply a semantic-based coordination approach from the network edge. We consider semantics as the key enabling principle for the implementation of spectrum coordination schemes addressing the coexistence of heterogeneous technologies at the edge of 5G HetUDN wireless networks. A Semantic-based Framework for dynamic Spectrum Coordination (SFSC) deployed according to the MEC approach is proposed dealing with agile complex system resource management. Practical experimental evidence evaluated on a networking testbed is provided, proving that a semantic MEC middleware is capable of delivering novel advanced computation communication paradigms as needed for 5G networks. [ABSTRACT FROM AUTHOR]

Copyright of Journal on Communication / Tongxin Xuebao is the property of Journal on Communications Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cache-enabled small cells can be an effective solution to deliver contents to mobile users with much lower power and latency. While the trend for getting smaller and denser cells is clear, interference will soon become unmanageable and an obstacle when the number of content requests is massive. Moreover, content request is seldom a spatially homogeneous process due to physical impediments (e.g., buidings) and social activities, which makes resource allocation for content delivery more challenging. In this paper, we consider an ultra-dense network (UDN) in which content requests are served by cache-enabled access nodes which can either be active for delivering contents to users, or inactive to reduce interference and network energy consumption. Our aim is to devise an approach that can locally adapt the caching node density and content caching probabilities to accommodate any arbitrary user density and content request for maximizing the network’s successful content delivery probability (SCDP). With a non-homogeneous spatial distribution for user equipments (UEs), we find that user-load, a parameter at the access node, plays a major role in the overall optimization. Simulation results illustrate that the proposed method can obtain superior performance against the considered benchmarks, with up to 150-160% increase, and our optimized solutions effectively adapt to the spatial-dependent user density. [ABSTRACT FROM AUTHOR]

Two radio air interfaces, Evolved-LTE and New Radio, coexist in new 5G systems. New Radio operates in the millimeter band and provides a better bandwidth, but the higher frequencies also imply worse radio conditions. Multi-connectivity, a feature of 5G that allows users to connect to more than one base station simultaneously, can offer the advantages of both interfaces. In this paper, we investigate how multi-connectivity can improve user reliability and the system's energy efficiency. Five algorithms for secondary cell association are presented and evaluated. We show a decrease in the radio link failure rate of up to 50% at high speeds and improvements of the energy efficiency of up to 20% at low speeds. [ABSTRACT FROM AUTHOR]

Copyright of Journal on Communication / Tongxin Xuebao is the property of Journal on Communications Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An ultra-dense network is an economical and efficient solution for the high-capacity requirements of 5G mobile networks. However, the rapid changes in received signals of its users will inevitably result in mobility challenges. Fortunately, in multi-connectivity, reasonable management of the serving cell enables improvement not only in throughput but also in mobility robustness. In this letter, we propose a dynamic serving cell select scheme, which allows a user to dynamically adjust the active set based on channel state information and cell load. Our simulation results show that the proposed scheme can significantly improve system throughput and can effectively reduce the probability of radio link failure. [ABSTRACT FROM AUTHOR]

In this paper, we study the impact of the base station (BS) idle mode capacity (IMC) on the network performance of multi-tier and dense heterogeneous cellular networks (HCNs) with both line-of-sight (LoS) and non-line-of-sight transmissions. Different from most existing works that investigated network scenarios with an infinite number of user equipments (UEs), we consider a more practical set-up with a finite number of UEs in our analysis. Moreover, in our model, the small BSs (SBSs) apply a positive power bias in the cell association procedure, so that macrocell UEs are actively encouraged to use the more lightly loaded SBSs. In addition, to address the severe interference that these cell range expanded UEs may suffer, the macro BSs (MBSs) apply enhanced inter-cell interference coordination, in the form of almost blank subframe (ABS) mechanism. For this model, we derive the coverage probability and the rate of a typical UE in the whole network or a certain tier. The impact of the IMC on the performance of the network is shown to be significant. In particular, it is important to note that there will be a surplus of BSs when the BS density exceeds the UE density, and thus a large number of BSs switch off. As a result, the overall coverage probability, as well as the area spectral efficiency, will continuously increase with the BS density, addressing the network outage that occurs when all BSs are active and the interference becomes LoS dominated. Finally, the optimal ABS factors are investigated in different BS density regions. One of major findings is that MBSs should give up all resources in favor of the SBSs when the small cell networks go ultra-dense. This reinforces the need for orthogonal deployments, shedding new light on the design and deployment of the future 5G dense HCNs. [ABSTRACT FROM AUTHOR]

On the basic of traditional macro cellular networks, ultra dense networks deploy plenty of low-power nodes working with maximum power, which provide superior communication quality and produce more energy consumption in networks. Aiming at the problem of wasting network resources caused by low-power nodes during low-load period in ultra dense networks, we study a kind of base station sleeping mechanism based on user connections. When the network loads are low, the connections between users and base stations (BSs) are sensed by environment awareness technology. Then, the connection relationship is used to establish a connection matrix. After that we use the established connection matrix to build a weighted bipartite graph. Taking the users’ QoS and the load of BSs into account, we build a weight matrix by weighting the two as the weights of the bipartite graph. We get the optimal connection between users and base stations by constantly optimizing the value of the connection matrix. By modeling, we transform the optimization problem into a 0-1 integer programming problem and get the optimal connection by Particle Swarm Optimization algorithm. Finally, the sleeping mechanism is executed according to this connection matrix, and we achieve the goal of energy conservation by closing low-load BSs. [ABSTRACT FROM AUTHOR]

In this paper, a novel approach for joint power control and user scheduling is proposed for optimizing energy efficiency (EE), in terms of bits per unit energy, in ultra dense small cell networks (UDNs). Due to severe coupling in interference, this problem is formulated as a dynamic stochastic game (DSG) between small cell base stations (SBSs). This game enables capturing the dynamics of both the queues and channel states of the system. To solve this game, assuming a large homogeneous UDN deployment, the problem is cast as a mean-field game (MFG) in which the MFG equilibrium is analyzed with the aid of low-complexity tractable partial differential equations. Exploiting the stochastic nature of the problem, user scheduling is formulated as a stochastic optimization problem and solved using the drift plus penalty (DPP) approach in the framework of Lyapunov optimization. Remarkably, it is shown that by weaving notions from Lyapunov optimization and mean-field theory, the proposed solution yields an equilibrium control policy per SBS, which maximizes the network utility while ensuring users’ quality-of-service. Simulation results show that the proposed approach achieves up to 70.7% gains in EE and 99.5% reductions in the network’s outage probabilities compared to a baseline model, which focuses on improving EE while attempting to satisfy the users’ instantaneous quality-of-service requirements. [ABSTRACT FROM AUTHOR]

Due to the high splitting-gain of dense small cells, Ultra-Dense Network (UDN) is regarded as a promising networking technology to achieve high data rate and low latency in 5G mobile communications. In UDNs, each User Equipment (UE) may receive signals from multiple Base Stations (BSs), which impose severe interference in the networks and in turn motivates the possibility of using Coordinated Multi-Point (CoMP) transmissions to further enhance network capacity. In CoMP-based Ultra-Dense Networks, a great challenge is to tradeoff between the gain of network throughput and the worsening backhaul latency. Caching popular files on BSs has been identified as a promising method to reduce the backhaul traffic load. In this paper, we investigated content placement strategies and user association algorithms for the proactive caching ultra dense networks. The problem has been formulated to maximize network throughput of cell edge UEs under the consideration of backhaul load, which is a constrained non-convex combinatorial optimization problem. To decrease the complexity, the problem is decomposed into two suboptimal problems. We first solved the content placement algorithm based on the cross-entropy (CE) method to minimize the backhaul load of the network. Then, a user association algorithm based on the CE method was employed to pursue larger network throughput of cell edge UEs. Simulation were conducted to validate the performance of the proposed cross-entropy based schemes in terms of network throughput and backhaul load. The simulation results show that the proposed cross-entropy based content placement scheme significantly outperform the conventional random and Most Popular Content placement schemes, with with 50% and 20% backhaul load decrease respectively. Furthermore, the proposed cross-entropy based user association scheme can achieve 30% and 23% throughput gain, compared with the conventional N-best, No-CoMP, and Threshold based user association schemes. [ABSTRACT FROM AUTHOR]