A survey on 5G

The rapidly increasing number of mobile devices, voluminous data, and higher data rate are pushing to rethink the current generation of the cellular mobile communication The next or fifth generation (5G) cellular networks are expected to meet high-end requirements The 5G networks are broadly characterized by three unique features: ubiquitous connectivity, extremely low latency, and very high-speed data transfer The 5G networks would provide novel architectures and technologies beyond state-of-the-art architectures and technologies In this paper, our intent is to find an answer to the question: "what will be done by 5G and how?" We investigate and discuss serious limitations of the fourth generation (4G) cellular networks and corresponding new features of 5G networks We identify challenges in 5G networks, new technologies for 5G networks, and present a comparative study of the proposed architectures that can be categorized on the basis of energy-efficiency, network hierarchy, and network types Interestingly, the implementation issues, eg, interference, QoS, handoff, security-privacy, channel access, and load balancing, hugely effect the realization of 5G networks Furthermore, our illustrations highlight the feasibility of these models through an evaluation of existing real-experiments and testbeds

A Survey on 5G: The Next Generation of Mobile Communication

Driven by the explosive data traffic and new quality of service requirement of mobile users, the communication industry has been experiencing a new evolution by means of network infrastructure densification. With the increase of the density as well as the variety of access points (APs), the network benefits from proximal transmissions and increased spatial reuse of system resources, thus introducing a new paradigm named ultra-dense networks (UDNs). Since the limited available resources are shared by ubiquitous APs in UDNs, the demand for efficient resource allocation schemes becomes even more compelling. However, the large scale of UDNs impedes the exploration of effective resource allocation approaches particularly on the computational complexity and significance overhead or feedback. In this paper, we provide a survey-style introduction to resource allocation approaches in UDNs. Specifically, we first present some common scenarios of UDNs with the relevant special issues. Second, we provide a taxonomy to classify the resource allocation methods in the existing literatures. Then, to alleviate the main difficulties of UDNs, some prevailing and feasible solutions are elaborated. Next, we present some emerging technologies thriving UDNs with special RA features discussed. Additionally, the challenges and open research directions are outlined in this field.

Resource Allocation for Ultra-Dense Networks: A Survey, Some Research Issues and Challenges

Mahmut C. Selekoglu, Adana Cimento, Turkey, presents a reminder of the basic considerations in approaching energy-efficient processes.

How to be Energy Efficient

A survey on energy efficient 5G green network with a planned multi-tier architecture

In this paper, we consider the energy-efficient power allocation in the downlink of a large-scale multiple-input multiple-output (MIMO) system under both quality of service (QoS) constraints and maximum transmit power constraints. With these two constraints satisfied, the resource allocation strategies are proposed, which aim to maximize the energy-efficiency defined as the successfully delivered information bits per Joule energy consumed (in bits/Joule). Moreover, the power consumption consists of both transmit power and circuit power. In our work, the original problem which is nonconvex in nature is first transformed into a new convex problem. Then it is demonstrated the existence of a unique globally optimal power allocation using Lagrange multiplier method. Finally, numerical simulation results show that the number of transmit antennas plays an important role in increasing the energy efficiency, namely, we can obtain an optimal value of transmit antennas. It is revealed that the number of users and the QoS requirement have an effect on the energy efficiency.

http://ieeexplore.ieee.org/iel7/6971896/6992003/06992089.pdf

QoS-aware energy-efficient optimization for massive MIMO systems in 5G

We consider the downlink of a multi-cell network where neighboring base stations with large scale antennas share the spectrum and collaborate with each other to improve the overall network performance. This paper utilizes the zero-forcing (ZF) transmit beamformer, which has been proven as the simplest and optimal form for high SNR in large scale antennas system. The objective of the coordination is to minimize the total transmit power and meanwhile satisfy the quality-of-service (QoS) requirements with the minimum total transmit power. Based on the properties of large scale MIMO and sparse approximate inverse preconditioners (AINV), we propose the approximately optimal algorithm and AINV based algorithm. Numerical simulations demonstrate the performance of proposed strategies.

Multi-cell coordinated beamforming and power allocation with large scale MIMO

—The focus of this letter is on the reduction of the large pilot overhead in orthogonal frequency division multi- plexing (OFDM) based massive multiple-input multiple-output (MIMO) systems. We propose a novel joint channel estimation and equalization technique that requires only one pilot subcarrier, reducing the pilot overhead by orders of magnitude. We take advantage of the coherent bandwidth spanning over multiple subcarrier bands. This allows for a band of subcarriers to be equalized with the channel frequency response (CFR) at a single subcarrier. Subsequently, the detected data symbols are considered as virtual pilots, and their CFRs are updated without additional pilot overhead. Thereafter, the remaining channel estimation and equalization can be performed in a sliding manner. With this approach, we use multiple channel estimates to equalize the data at each subcarrier. This allows us to take advantage of frequency diversity and improve the detection performance. Finally, we corroborate the above claims through extensive numerical analysis, showing the superior performance of our proposed technique compared to conventional methods.

pdf/joint-channel-estimation-and-equalization-in-massive-mimo-1qa8fs06.pdf

Joint Channel Estimation and Equalization in Massive MIMO Using a Single Pilot Subcarrier

In this paper, we study the optimal pilot design problem and CSI feedback method in a massive MIMO system. We get the asymptotically optimal solution for pilot design based on minimizing the Mean Square Error (MSE) of channel estimation with both the Sum Power Constraint (SPC) and the Per Antenna Power constraint (PAPC) utilizing a t-norm approximation method. To further improve the transmission efficiency and reduce the computation load, we propose a CSI estimation feedback method with pilot weight to gradually discover the CSI. The CSI fed back to the BS is collected to design beamforming matric for different users aiming at improving users' achievable rate. Simulation results validate that the method can provide an acceptable achievable rate consuming much less transmission and computation resources.

Optimal pilot design with CSI feedback in massive MIMO systems

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Papers

QoS-aware energy-efficient optimization for massive MIMO systems in 5G

Multi-cell coordinated beamforming and power allocation with large scale MIMO

Joint Channel Estimation and Equalization in Massive MIMO Using a Single Pilot Subcarrier

Optimal pilot design with CSI feedback in massive MIMO systems