Design, Modeling, and Performance Analysis of Multi-Antenna Heterogeneous Cellular Networks

This paper presents a stochastic geometry-based framework for the design and analysis of downlink multi-user multiple-input multiple-output (MIMO) heterogeneous cellular networks with linear zero-forcing transmit precoding and receive combining, assuming Rayleigh fading channels and perfect channel state information. The generalized tiers of base stations may differ in terms of their Poisson point process spatial density, number of transmit antennas, transmit power, artificial-biasing weight, and number of user equipments served per resource block. The spectral efficiency of a typical user equipped with multiple receive antennas is characterized using a non-direct moment-generating-function-based methodology with closed-form expressions of the useful received signal and aggregate network interference statistics systematically derived. In addition, the area spectral efficiency is formulated under different space-division multiple-access and single-user beamforming transmission schemes. We examine the impact of different cellular network deployments, propagation conditions, antenna configurations, and MIMO setups on the achievable performance through theoretical and simulation studies. Based on the state-of-the-art system parameters, the results highlight the inherent limitations of baseline single-input single-output transmission and conventional sparse macro-cell deployment, as well as the promising potential of multi-antenna communications and small-cell solution in interference-limited cellular environments

A Channel Quality-aware Scheduling and Resource Allocation Strategy for Downlink LTE Systems

[[abstract]]Today, the main purpose of a scheduler for Long Term Evolution (LTE) is to provide the best system performance. However, it may decrease the system performance to have latency and starvation of lower priority connections in a resource allocation phase. There has been little research performed on LTE downlink scheduling and resource allocation. This paper proposes an efficient algorithm that includes scheduling strategies and resource allocation mechanisms, to avoid the latency or starvation of lower priority connections and to maintain system performance in downlinks of LTE. The algorithm discusses five levels of bandwidth request situations to assign priority and to allocate the bandwidth for each connection. Therefore, we design an LTE downlink scheduling scheme and a resource allocation strategy that not only aims to achieve the system’s highest performance but also avoids latency and starvation problems. As shown in the results of simulations, the proposed algorithm can provide proportional fairness and high system performance in downlinks of LTE systems.[[notice]]補正完畢[[journaltype]]國外[[incitationindex]]EI[[ispeerreviewed]]Y[[booktype]]紙本[[countrycodes]]US

Joint QoS-Aware Scheduling and Precoding for Massive MIMO Systems via Deep Reinforcement Learning

The rapid development of mobile networks proliferates the demands of high data rate, low latency, and high-reliability applications for the fifth-generation (5G) and beyond (B5G) mobile networks. Concurrently, the massive multiple-input-multiple-output (MIMO) technology is essential to realize the vision and requires coordination with resource management functions for high user experiences. Though conventional cross-layer adaptation algorithms have been developed to schedule and allocate network resources, the complexity of resulting rules is high with diverse quality of service (QoS) requirements and B5G features. In this work, we consider a joint user scheduling, antenna allocation, and precoding problem in a massive MIMO system. Instead of directly assigning resources, such as the number of antennas, the allocation process is transformed into a deep reinforcement learning (DRL) based dynamic algorithm selection problem for efficient Markov decision process (MDP) modeling and policy training. Specifically, the proposed utility function integrates QoS requirements and constraints toward a long-term system-wide objective that matches the MDP return. The componentized action structure with action embedding further incorporates the resource management process into the model. Simulations show 7.2% and 12.5% more satisfied users against static algorithm selection and related works under demanding scenarios

Secrecy Energy Efficiency of MIMOME Wiretap Channels with Full-Duplex Jamming

Full-duplex (FD) jamming transceivers are recently shown to enhance the information security of wireless communication systems by simultaneously transmitting artificial noise (AN) while receiving information. In this work, we investigate if FD jamming can also improve the systems secrecy energy efficiency (SEE) in terms of securely communicated bits-per- Joule, when considering the additional power used for jamming and self-interference (SI) cancellation. Moreover, the degrading effect of the residual SI is also taken into account. In this regard, we formulate a set of SEE maximization problems for a FD multiple-input-multiple-output multiple-antenna eavesdropper (MIMOME) wiretap channel, considering both cases where exact or statistical channel state information (CSI) is available. Due to the intractable problem structure, we propose iterative solutions in each case with a proven convergence to a stationary point. Numerical simulations indicate only a marginal SEE gain, through the utilization of FD jamming, for a wide range of system conditions. However, when SI can efficiently be mitigated, the observed gain is considerable for scenarios with a small distance between the FD node and the eavesdropper, a high Signal-to-noise ratio (SNR), or for a bidirectional FD communication setup.Comment: IEEE Transactions on Communication

Efficient radio resource management for future 6G mobile networks: A Cell-Less Approach

Existing mobile communication systems are unable to support ultra high system capacity and high reliability for the edge users of future 6G systems, which are envisioned to guarantee the desired quality of experience. Recently, cell-less radio access networks (RAN) are exploited to boost the system capacity. Therefore, in this letter we propose a cell-less networking approach with an efficient radio resource optimization mechanism to improve the system capacity of the future 6G networks. The simulation results illustrate that the proposed cell-less NG-RAN design provides significant system capacity improvement over the legacy cellular solutions.This work was supported by the European Union H2020 Research and Innovation Programme funded Marie Skłodowska-Curie ITN TeamUp5G Project under Grant 813391

Link adaptation for energy-efficient uplink coordinated multi-point receptions

We investigate link adaptation methods for energy-efficient uplink coordinated multi-point receptions. A system model for practical cellular networks is introduced, in which only a subset of base stations participates in cooperative link adaptation and cooperative decoding for uplink transmissions. To cope with channel-state-information (CSI) mismatch incurred from the system model, link adaptation controllers implementing rate back-off from the maximum achievable rate calculated with the mismatched CSI is introduced. From analytical and simulation results, it is concluded that under a certain condition, the rate back-off does not help to improve energy efficiency, where, for example, the condition holds when the CSI errors are modeled as additive Gaussian random variables. Furthermore, energy efficiency of multi-user spatial-division-multiple-access uplink transmissions is studied in isolated cooperative cellular networks. In this scenario, an analytical expression for the optimal link adaptation achieving maximum energy efficiency is obtained

Design, Modeling, and Performance Analysis of Multi-Antenna Heterogeneous Cellular Networks

Abstract This paper presents a stochastic geometry-based framework for the design and analysis of downlink multi-user multipleinput multiple-output (MIMO) heterogeneous cellular networks (HetNets) with linear zero-forcing (ZF) transmit precoding and receive combining, assuming Rayleigh fading channels and perfect channel state information (CSI). The generalized tiers of base stations (BSs) may differ in terms of their Poisson point process (PPP) spatial density, number of transmit antennas, transmit power, artificial-biasing weight, and number of user equipments (UEs) served per resource block. The spectral efficiency of a typical user equipped with multiple receive antennas is characterized using a non-direct moment-generating-function (MGF)-based methodology with closed-form expressions of the useful received signal and aggregate network interference statistics systematically derived. In addition, the area spectral efficiency is formulated under different space-division multiple-access (SDMA) and single-user beamforming (SUBF) transmission schemes. We examine the impact of different cellular network deployments, propagation conditions, antenna configurations, and MIMO setups on the achievable performance through theoretical and simulation studies. Based on state-of-the-art system parameters, the results highlight the inherent limitations of baseline single-input singleoutput (SISO) transmission and conventional sparse macro-cell deployment, as well as the promising potential of multi-antenna communications and small-cell solution in interference-limited cellular environments. Index Terms Multi-antenna communications, downlink heterogeneous cellular networks, stochastic geometry theory