Potentials for Application of Millimeter Wave Communications in Cellular Networks

Future 5G cellular networks will need to deliver significantly increased system capacity and user data rates. This expected growth along with today’s shortage of spectrum raises the need for new frequency allocations. Millimeter wave spectrum is emerging as a suitable candidate with a vast amount of available bandwidth (around 60 GHz). Extending cellular networks communications on millimeter wave frequencies requires extensive measurement campaigns and analysis of signals propagation characteristics. This paper gives an overview of recent measurement studies and results used for modeling millimeter wave channel behavior in different propagation environments. Also , the paper provides a preliminary simulation analysis of a hybrid LTE-millimeter wave heterogeneous network, which suggests that Gbps user data rates are achievable with sufficient beamforming gains. However, the millimeter wave cellular extensions will require architectural changes to address the technical issues spanning from the transceivers design to the operational procedures in both access and backhaul network parts.     

Smart Backhauling for 5G Heterogeneous Network with Millimeter Wave Backhaul Links to Perform Switching Off,Interference Management and Backhaul Routing

Developments made in the fifth generation (5G) and the cellular networks have greatly influenced the lifestyle of the wireless users. Increased demand on higher data rates has also increased the network traffic. In the viewpoint of cellular networks, several Small Cells (SCs) are combined together with the help of microwave communications and millimeter wave communication models, in order to support the heterogeneous environments. In this paper, we have proposed a hybrid communication framework which can efficiently support the interference management, routings in backhaul links and the joint issue during on/off status of the mobile using 5G mmWave backhaul links. A novel cache-enabled technology is designed to develop backhaul links using heuristic search models. Along with that, an effective data access framework is also formulated using distance based cluster head selection that resolves the interference issues. Without modifying the content of the mobile users, the services are offered to the uses associated with backhaul links. Since a fast iterative model is developed, the throughput rate and the energy savings are maximized. A simulation analysis is carried out with a static number of mobile nodes which has proved the efficiency of the proposed framework.

     

Decentralized beamforming design and power allocation for limited coordinated multi-cell network

Multi-cell processing （MCP） is capable of providing significant performance gain, but this improvement is accompanied by dramatic signaling overhead between cooperative base stations. Therefore, balancing the performance gain and overhead growth is crucial for a practical multi-base cooperation scheme. In this paper, we propose a decentralized algorithm to jointly optimize the power allocation and beamforming vector with the goal of maximizing the system performance under the constraint of limited overhead signal and backhaul link capacity. In particular, combined with calculating the transmission beamforming vector according to the local channel state information, an adaptive power allocation is presented based on the result of sum capacity estimation. Furthermore, by utilizing the concept of cell clustering, the proposed framework can be implemented in a practical cellular system without major modification of network architecture. Simulation results demonstrate that the proposed scheme improves the system performance in terms of the sum capacity and cell-edge capacity.     

On multicell cooperative transmission in backhaul-constrained cellular systems

Recent work has shown that multicell cooperative signal processing in cellular networks can significantly increase system capacity and fairness. For example, multicell joint transmission and joint detection can be performed to combat intercell interference, often mentioned in the context of distributed antenna systems. Most publications in this field assume that an infinite amount of information can be exchanged between the cooperating base stations, neglecting the main downside of such systems, namely, the need for an additional network backhaul. In recent publications, we have thus proposed an optimization framework and algorithm that applies multicell signal processing to only a carefully selected subset of users for cellular systems with a strongly constrained backhaul. In this paper, we consider the cellular downlink and provide a comprehensive summary and extension of our previous and current work. We compare the performance obtained through centralized or decentralized optimization approaches, or through optimal or suboptimal calculation of precoding matrices, and identify reasonable performance–complexity trade-offs. It is shown that even low-complexity optimization approaches for cellular systems with a strongly constrained backhaul can yield major performance improvements over conventional systems.     

Joint backhaul bandwidth and power allocation in heterogeneous cellular networks: A two‐level approach

We investigate the problem of joint downlink wireless backhaul bandwidth (WBB) and power allocation in heterogeneous cellular networks (HCNs). A WBB partitioning scheme is considered, which allocates the whole bandwidth between the macrocell and small cells for data transmission and backhauling. We formulate an optimization problem to maximize the weighted sum logarithmic utility function by jointly optimizing WBB portion and fronthaul power allocation of each base station with consideration of the backhaul capacity limitation on each small cell. In order to solve this joint optimization problem, we propose a hierarchical two‐level approach and decompose the original problem into two independent subproblems: the WBB allocation at the macrocell base station (MBS) and the power allocation at both the MBS and small cell base stations (SBSs). Accordingly, the optimal WBB portion and power allocation solutions are obtained, respectively. Furthermore, we develop a distributed algorithm to implement the joint WBB and power allocation. Numerical results verify the effectiveness of the proposed approach and analyze the impact of the weighted coefficient and backhaul capacity limitation on the network performance. In addition, significant performance gains can be achieved by the proposed approach over the benchmark.     

Efficient user selection for multi-cell multi-user MIMO systems with limited backhaul

Multi-cell multi-user multiple-input multiple-output (MC-MU-MIMO) is a promising technique to eliminate inter-user interference and inter-cell cochannel interference in wireless telecommunication syste...     

光移动回程小蜂窝面临的挑战及解决方案

随着移动宽带服务需求不断增加,需要运营商提供更多的无线接入网络功能。LTE和小蜂窝可提供解决无限覆盖和容量的方案。然而,回程技术在CAPEX方面昂贵,运营成本及传统的解决方案无法提供必要的结合能力和成本效率。文中定义了一个Q带点对多点的回程架构,重点介绍了在构建移动回程和无线接入网络框架中提出的萨拉班德结构,其是一种具有成本效益的网络结构,可提供多千兆能结合在Q带传输一个点对多点毫米波传输技术。此外,文中除了给出网络结构的定义外,还描述了节点的密钥类型,包括萨拉班德具体结构。     

Local Base Station Cooperation Via Finite-Capacity Links for the Uplink of Linear Cellular Networks

Cooperative decoding at the base stations (or access points) of an infrastructure wireless network is currently well recognized as a promising approach for intercell interference mitigation, thus enabling high frequency reuse. Deployment of cooperative multicell decoding depends critically on the tolopology and quality of the available backhaul links connecting the base stations. This work studies a scenario where base stations are connected only if in adjacent cells, and via finite-capacity links. Relying on a linear Wyner-type cellular model with no fading, achievable rates are derived for the two scenarios where base stations are endowed only with the codebooks of local (in-cell) mobile stations, or also with the codebooks used in adjacent cells. Moreover, both uni- and bidirectional backhaul links are considered. The analysis sheds light on the impact of codebook information, decoding delay, and network planning (frequency reuse) on the performance of multicell decoding as enabled by local and finite-capacity backhaul links. Analysis in the high-signal-to-noise ratio (SNR) regime and numerical results validate the main conclusions.      

The Role of Adaptivity in MIMO Line-of-Sight Systems for High Capacity Backhauling

Spectrally efficient backhaul networks are one of the key-factors for the deployment of next generation wireless cellular systems. The ambitious capacity requirements for future broadband wireless networks and the high infrastructure costs for new cell sites pose new challenges in the design of high capacity point-to-point (PtP) wireless microwave links. In this paper we present a study on PtP links that utilize a peculiar form of multiple-input multiple-output configuration, in which a capacity doubling is obtained by exploiting the geometric characteristics of the Line-of-Sight link. The impact of adaptivity on the maximum achievable transmission distance in presence of the main electronic impairments, for typical physical parameters, is discussed in order to reveal the feasibility and the advantages of this class of solutions.     

Dynamic Cooperative Base Station Selection Scheme for Downlink CoMP in LTE-Advanced Networks

Coordinated Multi-Point (CoMP) transmission is a technique proposed to enhance the spectral efficiency and system throughput in an interference limited cellular networks. In CoMP joint processing (JP) scheme multiple base stations (BSs) are coordinately transmit data streams to each user. As more than two base stations are involved, abundant spatial resources are exploited and more backhaul spectrum for JP cooperation is required. The backhaul architecture for CoMP JP is crucial to provide low latency, unlimited capacity, less power consumption, and perfect synchronization among the BSs. However, satisfying all these constraints is impossible as the number of cooperative BSs increases for each user. In this paper, a dynamic cooperative base station selection scheme is proposed to reduce the backhaul load for CoMP user by selecting the appropriate number of coordinated BSs from the CoMP cluster to ensure the certain quality of service (QoS). In particular, for cell edge user the number of cooperative BSs per user has been selected in order to achieve reduced overhead and the allocation of backhaul capacity is performed under the max–min fairness criterion. Simulation results show that the proposed selection scheme achieves significant performance improvement than other transmission modes in terms of the average sum rate per backhaul use and minimal total power consumption.     

Downlink energy efficiency modeling and optimization with backhaul awareness and interference price in ultra cellular HetNet

The cellular heterogeneous network(HetNet) with ultra dense small cells is called ultra cellular HetNet.The energy efficiency for this network is very important for future green wireless communications.The data rates and power consumptions for three parts(i.e.,macro cells,small cells,and mixed backhaul links) in ultra cellular HetNet are jointly formulated to model downlink energy efficiency considering the active base stations(BSs) and inactive BSs.Then,in order to decrease the downlink co-channel interference,the interference price functions are also jointly set up for the three parts in ultra cellular HetNet.Next,energy efficiency optimization iterative algorithm scheme using the fractional programming and Lagrangian multiplier with constraints for density of ultra dense small cells and fraction of mixed backhaul links is presented with interference pricing.The convergence and computation complexity are also proved in this scheme.The numerical simulations finally demonstrate convergence behavior of the proposed algorithm.By comparison,some conclusion can be drawn.Maximizing energy efficiency of system is lower as the density of small cell is high.The effect on maximizing energy efficiency with interference price outperforms that without interference price.And the energy efficiency increases as the fraction of mixed backhaul links is higher because of more power consumption in the microwave backhaul links.     

Multipath multihop mmWave backhaul in ultra-dense small-cell network

Ultra-Dense Network (UDN) is considered to be the key enabler for realizing capacity goals set by 5G. The major concern in UDN deployment is the backhaul network, which should be scalable, cost-effective, and have sufficient capacity to support massive small cell traffic. Otherwise, the backhaul can become the bottleneck of the network. In this paper, we propose a wireless backhaul solution for UDN deployment by considering MultiPath-MultiHop (MPMH) backhaul architecture in mmWave frequency band. In addition, we propose a distributed routing scheme to forward the backhaul traffic over the multihop network. Backhaul capacity and line-of-sight probability of the proposed backhaul architecture for various picocell densities were compared with direct, multiple-association, and multihop backhaul schemes under interference limited scenarios in outdoor and indoor small cell deployments. The simulation results indicate that the MPMH mmWave backhaul is the most cost-effective and scalable solution for UDN deployment.     

Stochastic Models for Multistage Cell Classification Systems

Probabilistic models for multistage cell classification systems are described. A simple finite Markov chain models classification events which occur as a cell passes through the system. The state space consists of various identities assigned to the cell, including true celi type and identities assigned by classifiers. Effects of throughput rate, data buffer capacity, and classifier processing rate on system performance are predicted by another model composed of a network of single server queues. Markov and queue models are interrelated in that classification events at one processor (modeled by the Markov chain) govern arrival rates of other processors. In turn, the queue model predicts the probability that a cell wili be missed due to fmite data buffer capacity. The miss event is modeled by the Markov chain as a possible classification outcome. Application of the models is illustrated for a multistage gynecologic flow prescreening system with slit-scan processing in the first stage and two dimensional image processing in the second. Results predict system sensitivity as a function of first stage false alann rate and abnormal cell occurrence rate.     

Iterative multiuser detection, macrodiversity combining, anddecoding for the TDMA cellular uplink

A soft-input soft-output (SISO) multiuser detector (MUD) suitable for inclusion in iterative processing architectures is presented and applied to the detection of the coded time division multiple access (TDMA) cellular uplink. A SISO-MUD processor is located at each base station in the network, and adjacent base stations share information concerning the mobiles they serve. Because the MUD outputs are soft, they are suitable for postdetection macrodiversity combining. The combined signals are then passed to a SISO forward error correction (FEC) decoder, and the soft outputs are fed back to the multiuser detectors. Processing continues in an iterative fashion in accordance with the turbo principle. Simulation results are presented that indicate that use of such a scheme enables cellular systems to be overloaded with more than just one cochannel user per cell at the price of a minimal loss in signal-to-noise ratio (SNR). The proposed implementation assumes the availability of both perfect channel state information and a high capacity backhaul     

Stochastic Properties of Mobility Models in Mobile Ad Hoc Networks

The stochastic model assumed to govern the mobility of nodes in a mobile ad hoc network has been shown to significantly affect the network's coverage, maximum throughput, and achievable throughput-delay trade-offs. In this paper, we compare several mobility models, including the random walk, random waypoint, and Manhattan models on the basis of the number of states visited in a fixed time, the time to visit every state in a region, and the effect of the number of wandering nodes on the time to first enter a set of states. These metrics for a mobility model are useful for assessing the achievable event detection rates in surveillance applications where wireless-sensor-equipped vehicles are used to detect events of interest in a city. We also consider mobility models based on Correlated Random Walks, which can account for time dependency, geographical restrictions, and nonzero drift. We demonstrate that these models are analytically tractable by using a matrix-analytic approach to derive new, closed-form results in both the time and transform-domains for the probability that a node is at any location at any time for both semi-infinite and finite 1D lattices. We also derive first entrance time distributions for these walks. We find that a correlated random walk 1) covers more ground in a given amount of time and takes a smaller amount of time to cover an area completely than a random walk with the same average transition rate, 2) has a smaller first entrance time to small sets of states than the random waypoint and random walk models, and 3) leads to a uniform distribution of nodes (except at the boundaries) in steady state.     

Toward Distributed Robust Power Allocation of Wireless Backhaul Links in Vehicular Small Cells

The vehicular small cell (VSC) is a new paradigm that has been recently proposed to be a potential technology for 5G cellular systems. Briefly, VSC concept lies in using the small cell technology inside vehicles such as buses and private cars to provide better coverage and good internet experience while on the move where the wireless backhaul link is inevitable. However, in order to increase the spectral efficiency, co-channel deployment of VSCs on the wireless backhaul link is preferred. Thus, managing the variable interference on the wireless backhaul and its power allocation requirement seem to be serious challenges in implementing the VSCs. Motivated by the simplicity and practically of the power allocation based on pilot power and received signal strength index (RSSI) information, this paper proposes an evolutionary approach and robust to the interference fluctuations in which, taking the limited dynamic range of transmitted power using linear mapping into account, the signal to interference plus noise ratio (SINR) balancing of the vehicular small base stations in their home macro base station and maximum capacity on the backhaul link are achieved at the cost of exchanging some power level information among both macro and small base stations. Finally, simulation results prove aforementioned potential advantages attained from the presented schemes.     

Capacity regions and optimal power allocation for CDMA cellular radio

The capacity region of code-division multiple access (CDMA) is determined by the set of transmission rates combined with quality-of-service (QoS) requirements which allow for a feasible power allocation scheme for n mobiles in a cellular network. The geometrical and topological properties of the capacity region are investigated in the present paper for the case of unlimited and limited power, respectively. As a central result, we show that the capacity region is convex by breaking the complicated topological structure into characteristic properties of its boundary and interior points, each of interest in itself. Based on these results, we furthermore investigate optimal power assignment schemes in the case that the demand of a community of users is infeasible. Weighted minimax and Bayes solutions are explicitly determined as appropriate means to share the capacity of a cellular network in a reasonable and fair way.     

Performance Analysis of Cooperative Wireless Backhaul Networks Operating at Extremely High Frequencies

Extremely high frequency (EHF) bands above 50 GHz have been proposed to be used as backhaul links of modern cellular mobile networks. They provide interconnectivity between the base stations and the core network. In this paper, we propose the employment of cooperative techniques in backhaul networks. More specifically, the outage performance analysis of a simple cooperative diversity system operating at EHF bands is presented. The destination node combines the direct link with the signal received through a regenerative relay using selection combining. A combined statiform and convective model of rainfall rate for the rain attenuation prediction is considered. The correlation properties and the joint statistics among the microwave paths are also calculated. Numerical results present the impact of the geometrical parameters and the climatic conditions on the outage performance.     

AI Based Network and Radio Resource Management in 5G HetNets

The demand for pervasive wireless access and high data rate services are expected to grow significantly in the near future. In this context, the deployment of Heterogeneous Networks (HetNets) will enable important capabilities, such as high data rates and traffic offloading, providing dedicated capacity to homes, enterprises, and urban hotspots. Despite HetNet technology will be beneficial for future wireless systems in many ways, the massive cells diffusion has as a consequence an exponential increase of the backhaul traffic that can create congestion and collapse the backhaul network. Virtualization of networks and radio access allows the implementation of complex and efficient decisional processes for radio and network resource optimization, but the interaction between lower and upper layers during resource allocation decisions is still mostly unexplored. In this paper we propose an artificial intelligence based approach, with two interdependent decisional cores exchanging information, one aware of physical layer aspects and the other controlling pure network resources. The two iterative procedures aim at jointly optimizing the distribution of the traffic in the backhaul network and the users cell association, with the goals of minimizing the unsatisfied users data rate requests and minimizing the energy consumption reducing the number of activated cells, respectively.     

On the Capacity of Cluster-Based Cooperative MIMO Cellular System with Universal or Fractional Frequency Reuse

The information-theoretic capacity for the cluster-based multicell cooperative processing (MCP) network with inter-cluster interference is investigated in this paper. An upper bound for the ergodic capacity is derived by the QR decomposition of the channel matrix, which is concisely expressed and close to the results from numerical simulations. Capacity results for the universal frequency reuse (UFR) network show that the cluster-based MCP system has great advantages over the non-cooperated system, and the capacity gain depends mainly on the size of the cooperative cluster, the radius of the cell and the path loss exponent (PLE). However, the cluster-based UFR system is still interference limited, whose capacity declines sharply due to the inter-cluster interference. Therefore, a cluster-based fractional frequency reuse (FFR) network is proposed to improve the system capacity, simulation results show that the cluster-based FFR system can outperform the UFR system, especially for the cases of small radius of cell or small PLE.