A Novel Optimal Joint Resource Allocation Method in Cooperative Multicarrier Networks: Theory and Practice

Abstract

With the increasing demands for better transmission speed and robust quality of service (QoS), the capacity constrained backhaul gradually becomes a bottleneck in cooperative wireless networks, e.g., in the Internet of Things (IoT) scenario in joint processing mode of LTE-Advanced Pro. This paper focuses on resource allocation within capacity constrained backhaul in uplink cooperative wireless networks, where two base stations (BSs) equipped with single antennae serve multiple single-antennae users via multi-carrier transmission mode. In this work, we propose a novel cooperative transmission scheme based on compress-and-forward with user pairing to solve the joint mixed integer programming problem. To maximize the system capacity under the limited backhaul, we formulate the joint optimization problem of user sorting, subcarrier mapping and backhaul resource sharing among different pairs (subcarriers for users). A novel robust and efficient centralized algorithm based on alternating optimization strategy and perfect mapping is proposed. Simulations show that our novel method can improve the system capacity significantly under the constraint of the backhaul resource compared with the blind alternatives.

QoS-Driven Energy-Efficient Resource Allocation in Multiuser Amplify-and-Forward Relay Networks

“…Unlike the previous existing research works [14]- [19], wherein the throughput in OFDM network was maximized by optimizing either of the following: i) subcarrier allocation among different users, ii) subcarrier pairing at relay node, where the signal received at relay over one subcarrier is retransmitted on a different subcarrier, iii) power allocation over different subcarriers at each transmitting node; or iv) power allocation and subcarrier assignment, and [20]- [26], in this paper, we propose a unified energy-efficient resource allocation scheme by considering subcarrier permutation, power optimization, and subcarrier allocation all together and believe that we have made significant contribution in designing of energyefficient subcarrier pairing, subcarrier and power allocation in multi-user multicarrier AF relaying networks. This is the first work that investigates the energy-efficient resource allocation algorithm through the concept of "network price", which enables us to strike a balance between the achievable sum rate and the total power consumption in the relay networks.…”

“…The optimal power allocation scheme that maximizes the ergodic achievable rates was investigated in [13] for a multipair massive MIMO two-way AF relaying with imperfect channel state information (CSI). In [14], the problem of the joint resource allocation for uplink coordinated multipoint transmission/reception (CoMP) with limited backhaul link was studied under the compress-and-forward scheme, wherein a central backhaul node processes user pairing and subcarrier mapping, but this work is limited to uplink multiple access (MA) phase only, and thus it cannot be directly applied to multi-hop scenarios specially when a set of users are active in uplink MA phase while other set of users are active in downlink broadcast (BC) phase, whilst the users of the MA phase are willing to communicate with the corresponding users in the BC phase through an AF relay node that can also be considered as a low power base station (BS). The power allocation strategies with subcarrier pairing were proposed in [15]- [19] for the relay systems.…”

Online Distributed User Association for Heterogeneous Radio Access Network

“…Hence, a scheme having decentralized implementation with low-signaling overhead is desirable [28]. Distributed controls [17,19,20,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43] can be further divided into the static/offline and dynamic/online environment, and are guaranteed to be the simple and low-complexity alternative to centralized controls. In a distributed control, the UEs select the BSs based on the received signal strength and information received, such as load information, from BSs in range.…”

“…Authors in Refs. [17,31,32,33,34,35,37,38,39,40,41,42,43] considered a static environment, where the channel condition does not change. A q-learning-based BS selection game was applied in Ref.…”

Satellite Space Information Network: Application and Prospect

“…Spatial Information Network is a space motion platform (including satellites, airships and aircraft) as the carrier, real-time access, network transmission and processing spatial information, can support up deep space exploration [1], down to support applications such as earth observation, which will human sciences, culture and production activities to expand the space, far from the sea, and even deep space, is a global hotspot [2].…”