Joint Dynamic Resource Allocation Research Articles

Joint Resource Optimization for IRS-Assisted Mmwave MIMO Under QoS Constraints

This paper focuses on the non-convex joint optimization with a dynamic resource of multi-user for an intelligent reflecting surface-enhanced mmWave system, where all users have individual rates or quality of service requirements. Firstly, the objective function of the above non-linear problem is converted into a quadratic programming form under the quality of service constraints. Further, a multi-blocks alternating optimization framework with dynamic power allocation is proposed to obtain the maximum sum-rate, where the relaxed ADMM algorithm is adopted to tackle the optimal full-digital precoder and the corresponding passive reflecting matrix is obtained by the gradient-projection. The numerical results verify that beam optimization should be emphasized in high SNR, but joint dynamic resource allocation can further improve system performance even if the hardware dimensions reaches the limit.

Joint dynamic resource allocation and load balancing-cell selection in LTE-A HetNet scenarios based on Type 1 inband relay deployments

In LTE-A (long term evolution-advanced) networks, relaying is seen as a cost-effective solution to increase coverage and improve system capacity. Relays are deployed on the coverage of existing macrocells, so the resource sharing among different nodes and links and the inter-cell interference coordination (ICIC) are challenging issues that need to be addressed. In real scenarios, users are not uniformly distributed on cells, so the resource allocation has to adapt to changes in the traffic load distribution. This paper focuses on Type 1 half-duplex inband relaying. We propose a dynamic resource allocation scheme to adjust the frequency partitions to heterogeneous load conditions. In addition, we also propose a cell selection method which tries to connect users to the node that entails a better use of frequency resources, and at the same time, to guarantee the QoS requirements of users.

Dynamic Resource Allocation for Cooperative Spectrum Sharing in LTE Networks

Conventional spectrum sharing approaches assume that an unlicensed user accessing a licensed spectrum band autonomously operates by sensing (or detecting) the presence of the primary user, which is licensed to use the given band, with minimal coordination from the primary user. However, in this case, incorrect sensing decisions and resource allocation on the unlicensed secondary users' (SU) part can lead to undesired degradation of the primary users' performance. Therefore, there has been a recent paradigm shift to enable cooperative spectrum sharing, in which interaction is allowed between the primary and the secondary network for efficient spectrum utilization while limiting the interference experienced by a primary user. In this paper, we consider a cooperative spectrum sharing architecture in which the SU is assumed to be a cellular network. We then propose a novel fractional-frequency-reuse-based dynamic resource allocation (DRA) algorithm at the secondary (cellular) network. The joint DRA optimization involves simultaneous spectrum allocation across different base stations and then across users within a base station. It is an NP-hard problem and is prohibitively complex to solve for a large cellular network. Therefore, to reduce the complexity of the joint problem and offer a tractable solution, we formulate layered scheduling algorithms for cross-layer resource allocation. Furthermore, the feedback overhead between the layers is kept minimal. Finally, using simulations, we compare our proposed DRA scheme with other resource allocation schemes for sum system throughput, as well as for fairness in allocation. We also present the result for the case when the available primary spectrum varies over time and locations of SUs.

FHQA JDRA Schemes for Reliability and Energy Efficiency - Soft-DF-based OR-Assisted SC-FDMA

paper, we exploit the benefits of the diversity gains that arise from a cluster of opportunistic relays (ORs) and from the independently fading subcarriers of multiple users. Our goal is to improve the energy efficiency of the decodeand- forward-based OR-assisted single-carrier frequency-division multiple-access (SC-FDMA) uplink, where the direct transmission (DT) link is unavailable. We proposed two joint dynamic resource allocation (JDRA) schemes by assuming that the pilotaided channel-quality information (CQI) of all the users may be exchanged. Furthermore, we take the following two main aspects into account: 1) first-hop quality awareness (FHQA) for JDRA-aided OR and 2) buffering delay awareness in the context of interleaver-aided channel- coded systems. In addition, frequency-domain turbo equalizers are employed in both the relay and BS's receivers. Our results demonstrate that, compared to the DT benchmarker, the proposed FHQA JDRA schemes can achieve an energy reduction gain of 91% for a single-antenna base station (BS) receiver and up to 7.4% for a multiantenna BS when considering the energy consumption due to CQI exchange among relays.

Energy-Efficient Dynamic Resource Allocation for Opportunistic-Relaying-Assisted SC-FDMA Using Turbo-Equalizer-Aided Soft Decode-and-Forward

In this paper, we exploit the benefits of the diversity gains that arise from a cluster of opportunistic relays (ORs) and from the independently fading subcarriers of multiple users. Our goal is to improve the energy efficiency of the decode-and-forward-based OR-assisted single-carrier frequency-division multiple-access (SC-FDMA) uplink, where the direct transmission (DT) link is unavailable. We proposed two joint dynamic resource allocation (JDRA) schemes by assuming that the pilot-aided channel-quality information (CQI) of all the users may be exchanged. Furthermore, we take the following two main aspects into account: 1) “first-hop quality awareness” (FHQA) for JDRA-aided OR and 2) “buffering delay awareness” in the context of interleaver-aided channel-coded systems. In addition, frequency-domain turbo equalizers are employed in both the relay and BS's receivers. Our results demonstrate that, compared to the DT benchmarker, the proposed FHQA JDRA schemes can achieve an energy reduction gain of 91% for a single-antenna base station (BS) receiver and up to 7.4% for a multiantenna BS when considering the energy consumption due to CQI exchange among relays.

Joint Dynamic Resource Allocation and Waveform Adaptation for Cognitive Networks

This paper investigates the issue of dynamic resource allocation (DRA) in the context of multi-user cognitive radio networks. We present a general framework adopting generalized signal expansion functions for representation of physical-layer radio resources as well as for synthesis of transmitter and receiver waveforms, which allow us to join DRA with waveform adaptation, two procedures that are currently carried out separately. Based on the signal expansion framework, we develop noncooperative games for distributed DRA, which seek to improve the spectrum utilization on a per-user basis under both transmit power and cognitive spectral mask constraints. The proposed DRA games can handle many radio platforms such as frequency, time or code division multiplexing (FDM, TDM, CDM), and even agile platforms with combinations of different types of expansion functions. To avoid the complications of having too many active expansion functions after optimization, we also propose to combine DRA with sparsity constraints. Generally, the sparsity-constrained DRA approach improves convergence of distributed games at little performance loss, since the effective resources required by a cognitive radio are in fact sparse. Finally, to acquire the channel and interference parameters needed for DRA, we develop compressed sensing techniques that capitalize on the sparse properties of the wideband signals to reduce the number of samples used for sensing and hence the sensing time.

Wireless Heterogeneous Networks and Next Generation Internet

The recent advances in wireless access technologies as well as the increasing number of mobile applications have made Wireless Internet a reality. A wide variety of bandwidth demanding services including high speed data delivery and multimedia communication have been materialized through the convergence of the next generation Internet and heterogeneous wireless networks. However, providing even higher bandwidth and richer applications necessitates a fundamental understanding of wireless Internet architecture and the interactions between heterogeneous users. Consequently, fundamental advances in many concepts of the wireless Internet are required for the ultimate goal of communication anytime anywhere. This special issue of the ACM Mobile Networks and Applications Journal is dedicated to the recent advances in the area of Wireless Internet. We accepted 10 papers out of 59 submissions from all over the world with a 17% acceptance rate. Papers describing management schemes, protocols, models, evaluation methods, and experimental studies of Wireless Internet are included in this special issue to provide a broad view of recent advances in this field. In the first paper, R. Yu, Y. Zhang, M. Huang, and S. Xie address the call admission control (CAC) problem in cognitive radio networks in their work titled “Cross-Layer Optimized Call Admission Control in Cognitive Radio Networks.” In addition to traditional CAC challenges, they also consider the presence of sensing errors that may mislead the CAC strategy to make an inefficient or even incorrect decision. To this end, the parameters of CAC strategy and spectrum sensing scheme are simultaneously tuned to minimize the dropping rate while satisfying the requirements of both blocking rate and interference threshold by the developed optimization framework. The crosslayer optimization is modeled as a non-linear programming problem after introducing a multiple-stair Markov model to approximate the non-memoryless state transitions. Accordingly, the dropping rate is shown to be reduced while still meeting the blocking rate and the interference probability constraints. In their paper titled “Joint Dynamic Resource Allocation for QoS Provisioning in Multi-Access and Multi-Service Wireless Systems,” D. Calabuig, J. F. Monserrat, D. Martin-Sacristan and N. Cardona analyze the resource allocation problem in multi-access wireless systems. The joint dynamic resource allocation (JDRA) algorithm simultaneously allocates the best-suited Radio Access Technology (RAT) and the amount of resources to all the users active in a multi-access wireless system. The Quality of Service (QoS) requirements of different users in terms of delay and bit rate are guaranteed through an optimization formalization based on a Hopfield Neural Network (HNN) formulation. The analysis and simulations highlight the advantages of joint decision approach compared to a twostep procedure and show that JDRA can address different levels of congestion and load distribution among RATs compared to the state-of-the-art. In the paper titled “LAMA/CA: A Load-Adaptive MAC Protocol for Short Packets”, Z. Noar develops a load adaptive medium access control protocol with collision avoidance. The protocol design is based on the fact that very often the Internet access messages, such as HTTP E. Ekici Ohio State University, Columbus, OH, USA e-mail: ekici@ece.osu.edu

Joint Dynamic Resource Allocation for QoS Provisioning in Multi-Access and Multi-Service Wireless Systems

This paper proposes a Joint Dynamic Resource Allocation (JDRA) algorithm that allocates simultaneously the best-suited Radio Access Technologies (RATs) and amount of resources to all the users active in a multi-access wireless system. Both distributions are performed at the same time so as to make the most of the heterogeneous network. In this scenario users can connect to several RATs but not simultaneously and, therefore, the JDRA algorithm is able to consider the required handover time in the decision making. Moreover, the algorithm guarantees the Quality of Service (QoS) provision in terms of delay and bit rate in a multi-service scenario where different users may have different QoS requirements. Such a complex optimization problem has been tackled using a Hopfield Neural Network (HNN) formulation. These neural networks have fast response times once hardware implemented, which is very significant since current and future wireless networks must rapidly adapt to changing circumstances in wireless environment and traffic. Results prove the benefits achieved by the usage of the HNN-based JDRA algorithm. Firstly, the joint decision outperforms a two-steps procedure in which, after the RAT selection, the same uni-RAT DRA algorithm is applied. Secondly, the proposed algorithm can deal with different levels of congestion and load distribution among RATs in a much better way that other reference algorithms specifically designed for multi-service scenarios.