Ruin Theory for Dynamic Spectrum Allocation in LTE-U Networks

LTE in the unlicensed band (LTE-U) is a promising solution to overcome the scarcity of the wireless spectrum. However, to reap the benefits of LTE-U, it is essential to maintain its effective coexistence with WiFi systems. Such a coexistence, hence, constitutes a major challenge for LTE-U deployment. In this paper, the problem of unlicensed spectrum sharing among WiFi and LTE-U system is studied. In particular, a fair time sharing model based on \emph{ruin theory} is proposed to share redundant spectral resources from the unlicensed band with LTE-U without jeopardizing the performance of the WiFi system. Fairness among both WiFi and LTE-U is maintained by applying the concept of the probability of ruin. In particular, the probability of ruin is used to perform efficient duty-cycle allocation in LTE-U, so as to provide fairness to the WiFi system and maintain certain WiFi performance. Simulation results show that the proposed ruin-based algorithm provides better fairness to the WiFi system as compared to equal duty-cycle sharing among WiFi and LTE-U.Comment: Accepted in IEEE Communications Letters (09-Dec 2018

Auction-Based Coopetition between LTE Unlicensed and Wi-Fi

Motivated by the recent efforts in extending LTE to the unlicensed spectrum, we propose a novel spectrum sharing framework for the coopetition (i.e., cooperation and competition) between LTE and Wi-Fi in the unlicensed band. Basically, the LTE network can choose to work in one of the two modes: in the competition mode, it randomly accesses an unlicensed channel, and interferes with the Wi-Fi access point using the same channel; in the cooperation mode, it delivers traffic for the Wi-Fi users in exchange for the exclusive access of the corresponding channel. Because the LTE network works in an interference-free manner in the cooperation mode, it can achieve a much larger data rate than that in the competition mode, which allows it to effectively serve both its own users and the Wi-Fi users. We design a second-price reverse auction mechanism, which enables the LTE provider and the Wi-Fi access point owners (APOs) to effectively negotiate the operation mode. Specifically, the LTE provider is the auctioneer (buyer), and the APOs are the bidders (sellers) who compete to sell their channel access opportunities to the LTE provider. In Stage I of the auction, the LTE provider announces a reserve rate. In Stage II of the auction, the APOs submit their bids. We show that the auction involves allocative externalities, i.e., the cooperation between the LTE provider and one APO benefits other APOs who are not directly involved in this cooperation. As a result, a particular APO's willingness to cooperate is affected by its belief about other APOs' willingness to cooperate. This makes our analysis much more challenging than that of the conventional second-price auction, where bidding truthfully is a weakly dominant strategy. We show that the APOs have a unique form of the equilibrium bidding strategies in Stage II, based on which we analyze the LTE provider's optimal reserve rate in Stage I.Comment: 32 page

Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization

A Survey of Resource Allocation Techniques for Cellular Network’s Operation in the Unlicensed Band

With an ever increasing demand for data, better and efficient spectrum operation has become crucial in cellular networks. In this paper, we present a detailed survey of various resource allocation schemes that have been considered for the cellular network’s operation in the unlicensed spectrum. The key channel access mechanisms for cellular network’s operation in the unlicensed bands are discussed. The various channel selection techniques are explored and their operation explained. The prime issue of fairness between cellular and Wi-Fi networks is discussed, along with suitable resource allocation techniques that help in achieving this fairness. We analyze the coverage, capacity, and impact of coordination in LTE-U systems. Furthermore, we study and discuss the impact and discussed the impact of various traffic type, environments, latency, handover, and scenarios on LTE-U’s performance. The new upcoming 5G New Radio and MulteFire is briefly described along with some of the critical aspects of LTE-U which require further research. © 2020 by the authors. Licensee MDPI, Basel, Switzerland

Energy efficient and fair resource allocation for LTE-unlicensed uplink networks: A two-sided matching approach with partial information

Long‐Term Evolution–unlicensed (LTE‐U) has recently attracted worldwide interest to meet the explosion in cellular traffic data. By using carrier aggregation, licensed and unlicensed bands are integrated to enhance transmission capacity while maintaining reliable and predictable performance. As there may exist other conventional unlicensed band users, such as WiFi users, LTE‐U users have to share the same unlicensed bands with them. Thus, an optimized resource allocation scheme to ensure the fairness between LTE‐U users and conventional unlicensed band users is critical for the deployment of LTE‐U networks. In this paper, we investigate an energy efficient resource allocation problem in LTE‐U coexisting with other wireless networks, which aims at guaranteeing fairness among the users of different radio access networks. We formulate the problem as a multiobjective optimization problem and propose a semidistributed matching framework with a partial information‐based algorithm to solve it. We demonstrate our contributions with simulations in which various network densities and traffic load levels are considered

Dynamic resource management for LTE-based hybrid access femtocell systems

Hybrid access femtocells for long term evolution (LTE)-based cellular networks provide a tradeoff between closed and open access femtocells whereby all subscribers are granted access albeit with priority given to closed access subscribers. Due to the need to accommodate both closed and open access subscribers, quality of service (QoS) provisioning for LTE-based hybrid access femtocells has become more challenging. This paper addresses this issue and proposes a new dynamic resource management scheme for such hybrid architectures. In particular, the proposed scheme first classifies and performs lexicographic admission control on the incoming traffic data flows using an optimal greedy algorithm. A suboptimal delay-bounded packet scheduling algorithm and a dual decomposition-based power allocation algorithm are developed to solve the non-convex maximization problem such that the weighted sum rate of each femtocell is maximized, subject to bounded packet delays and power constraints. Simulation results show that the proposed scheme can significantly outperform existing schemes in terms of QoS, throughput and fairness