Deep Reinforcement Learning-Assisted Optimization for Resource Allocation in Downlink OFDMA Cooperative Systems

Orthogonal Frequency-Division Multiple Access (OFDMA) systems have attracted considerable attention through technologies such as 3GPP Long Term Evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX). OFDMA is a flexible multiple-access technique that can accommodate many users with widely varying applications, data rates, and Quality of Service (QoS) requirements. OFDMA has the advantages of handling lower data rates and bursty traffic at a reduced power compared to single-user OFDM or its Time Division Multiple Access (TDMA) or Carrier Sense Multiple Access (CSMA) counterparts. In our work, we propose a Particle Swarm Optimization based resource allocation and scheduling scheme (PSORAS) with improved quality of service for OFDMA Systems. Simulation results indicate a clear reduction in delay compared to the Frequency Division Multiple Access (FDMA) scheme for resource allocation, at almost the same throughput and fairness. This makes our scheme absolutely suitable for handling real time traffic such real time video-on demand.

Deployment of relay nodes (RNs) in cellular orthogonal frequency division multiple access (OFDMA) systems provides an effective solution to increase high data rate coverage and improve cell throughput. However, a challenging issue is that additional interferences caused by RNs may substantially compromise the performance gain if no measure is taken. In this study, the authors address the problem of interference coordination in relay-aided cellular OFDMA systems, aiming at exploiting the benefits of RNs while minimising the negative effects of interferences introduced. The authors first analyse the possible interference scenarios in multi-cell systems. Based on the insights into their analysis, the authors propose resource allocation with interference coordination (RAIC) scheme for cellular OFDMA systems. RAIC selectively perform one of three resource allocation algorithms according to the offered traffic load in the system, to mitigate interferences and thus enhance system throughput. The authors conduct intensive simulation experiments based on the model with realistic broadband channel propagation conditions. Numerical results demonstrate that their proposed RAIC can effectively improve system throughput compared with the resource allocation schemes without appropriate interference coordination.

In orthogonal frequency division multiple access (OFDMA) systems, efficient resource allocation is very important to improve the performance of the OFDMA system. The general principle of resource allocation in an OFDMA system is to assign each subcarrier to the user with the best channel condition for that subcarrier. However, in delay tolerant traffic, current work did not consider that packets on retransmissions may have different allocation criteria from those on their first transmissions. In this paper, the resource allocation scheme is investigated by considering different criterions to packets on first transmissions and on retransmissions. Under a bit error rate (BER) constraint, the objective is to maximize the throughput of packets on first transmissions, meanwhile decreasing the longest packet delay caused by retransmitted packets and guaranteeing all packets on retransmissions to be sent out. A low-complexity suboptimal algorithm that separates allocation for packets on retransmissions and on first transmissions is proposed. Adaptive modulation scheme is adopted to guarantee the BER constraint, except the modulation for each retransmitted packet remains the same. In order to improve retransmission liability, the retransmitted packets are combined with its failed packets in previous transmission.

In this paper, resource allocation for energy efficient communication in multi-cell orthogonal frequency division multiple access (OFDMA) downlink networks with cooperative base stations (BSs) is studied. The considered problem is formulated as a non-convex optimization problem which takes into account the circuit power consumption, the limited backhaul capacity, and the minimum required data rate for joint BS zero-forcing beamforming (ZFBF) transmission. By exploiting the properties of fractional programming, the considered non-convex optimization problem in fractional form is transformed into an equivalent optimization problem in subtractive form, which enables the derivation of an efficient iterative resource allocation algorithm. For each iteration, the optimal power allocation solution is derived with a low complexity suboptimal subcarrier allocation policy for maximization of the energy efficiency of data transmission (bit/Joule delivered to the users). Simulation results illustrate that the proposed iterative resource allocation algorithm converges in a small number of iterations, and unveil the trade-off between energy efficiency and network capacity.

We consider the adaptive resource allocation problem in downlink Orthogonal Frequency Division Multiple Access (OFDMA) system with strict packet delay constraints in the range of . In this range of delay constraints, resource optimization has to be simultaneously performed over multiple time slots. Thus optimal allocation decisions require future Channel State Information (CSI) and packet arrival rate information. The causal nature of CSI combined with the increase in the number of optimization variables makes it a very challenging problem. We propose a two-step solution by separating scheduling from subcarrier and power allocation. Our proposed causal scheduler ensures delay guarantees by deriving a minimum data rate out of the user queues while minimizing transmit power in every time slot. The output rates are fed to the resource allocation block and the problem is formulated as a convex optimization problem. The subcarrier and power allocation decisions are made in order to satisfy the demanded rates within the peak power constraint. We address the feasibility of the physical layer resource allocation problem and develop efficient algorithms. When the problem is infeasible we devise a strategy which incurs minimum deviation from the proposed rates for maximum number of users. We show by simulations that our proposed scheme can efficiently utilize time variations as well as multiuser diversity in the system.

This letter presents a novel opportunistic cooperative positioning approach for orthogonal frequency-division multiple access (OFDMA) systems. The basic idea is to allow idle mobile terminals (MTs) opportunistically estimating the arrival timing of the training sequences for uplink synchronization from active MTs. The major advantage of the proposed approach over state-of-the-arts is that the positioning-related measurements among MTs are performed without the paid of training overhead. Moreover, Cramer-Rao lower bound (CRLB) is utilized to derive the positioning accuracy limit of the proposed approach, and the numerical results show that the proposed approach can improve the accuracy of non-cooperative approaches with the a-priori stochastic knowledge of clock bias among idle MTs.

In this letter, we study optimal multicast of tiled 360 virtual reality (VR) video from one server (base station or access point) to multiple users in an orthogonal frequency division multiple access (OFDMA) system. For given video quality, we optimize the subcarrier, transmission power and transmission rate allocation to minimize the total transmission power. For given transmission power budget, we optimize the subcarrier, transmission power and transmission rate allocation to maximize the received video quality. These two optimization problems are non-convex problems. We obtain a globally optimal closed-form solution and a near optimal solution of the two problems, separately, both revealing important design insights for multicast of tiled 360 VR video in OFDMA systems.

In this paper, we propose an energy-efficient resource allocation scheme for the downlink of decode-and-forward relay-assisted orthogonal frequency division multiple access systems. The resource allocation is designed based on imperfect channel state information at the transmitter. We jointly optimize the power allocation, data rate allocation, and subcarrier allocation to maximize the system energy efficiency (EE). We formulate the EE problem as a probabilistic mixed non-convex optimization problem, in which the individual power constraints and the outage probability requirements are considered. An iterative algorithm based on bisection method is given to transform the optimization problem into a standard concave form. Also, we consider a proportional fairness design for the EE maximization problem. Simulation results illustrate the effectiveness of the proposed algorithm.

A new family of low density parity-check (LDPC) codes, called as invertible subset LDPC (IS-LDPC) codes, was proposed for peak-to-average power ratio (PAPR) reduction in OFDM systems recently. In this paper, we propose a PAPR reduction scheme for orthogonal frequency-division multiple access (OFDMA) systems based on IS-LDPC codes. The proposed scheme maps the invertible subsets of IS-LDPC codewords onto subcarriers to construct invertible symbol subsets. Then, the invertible symbol subsets are inverted independently for reducing the PAPR of downlink OFDMA systems. There is no need to transmit the side information by extra channels, which significantly reduces the system overhead and eases the system design. Simulation results show that the PAPR reduction scheme based on IS-LDPC codes produces remarkable PAPR reduction performance and good error correction performance in downlink OFDMA systems. Therefore, the proposed PAPR reduction scheme could be an efficient solution to reduce the PAPR of downlink OFDMA systems.

In this study, the authors propose a fine granularity resource allocation algorithm for enhancing overall quality of users’ received video in the orthogonal frequency division multiple access system. Subcarrier's contribution for video transmission is used as the guideline of resource allocation in this algorithm. The subcarrier with the largest contribution is given priority to be allocated on the basis of two‐level paths search in the whole resource allocation tree. Moreover, the authors design the full search implementation scheme and the simplified implementation scheme for the resource allocation algorithm, respectively. The full search implementation scheme can obtain superior performance gain with high complexity. For reducing the complexity, the authors further propose a simplified implementation scheme subject to some minor quality degradation. At last, the authors compare the fine granularity resource allocation algorithm with other existing resource allocation algorithms for video transmission. In the simulation results, it is shown that the proposed algorithm acquires much more superior performance in overall quality of users’ received video.

Orthogonal frequency division multiple access (OFDMA) systems exploit multiuser diversity and frequency-selectivity to achieve high spectral efficiencies. However, they require considerable feedback for scheduling and rate adaptation, and are sensitive to feedback delays. We develop a comprehensive analysis of the OFDMA system throughput as a function of the feedback scheme, frequency-domain scheduler, and discrete rate adaptation rule in the presence of feedback delays. We analyze the popular best-n and threshold-based feedback schemes. We show that for both the greedy and round-robin schedulers, the throughput degradation, given a feedback delay, depends primarily on the fraction of feedback reduced by the feedback scheme and not the feedback scheme itself. Even small feedback delays at low vehicular speeds are shown to significantly degrade the throughput. We also show that optimizing the link adaptation thresholds as a function of the feedback delay can effectively counteract the detrimental effect of delays.

Traditional handover algorithms are based on received signal strength indicator (RSSI) and traffic load intensity in orthogonal frequency division multiple access (OFDMA) systems, in order to guarantee all UEs' Quality of Service (QoS) and handover success ratio, a transceiver is activated even if there is only one low date rate activated user in its coverage area. In this paper, we propose an energy efficient handover algorithm combined coordinated multiple-points (CoMP) with OFDMA in a cellular systems, energy efficiency is introduced into the handover algorithm as an important parameter. The idea of the design is to enable adjacent cells to shutdown partial transceivers in some timeslots in low traffic conditions by concentrating the activated edge UEs to less cells. All activated UEs are classified into edge users and center users according to their distance to base stations, the analysis indicates that there exist an optimal edge distance corresponding to the maximum energy efficiency under different load for the proposed algorithm. Furthermore, a practical and low-complexity scheme that only considers the edge users is put forward. The edge users are identified by the reference signal received power (RSRP). Simulation results show that it can obtain up to 60% energy reduction at low traffic scenario.

One of the major drawbacks of the orthogonal frequency division multiple access (OFDMA) system is the multi-user interference (MUI) induced by the carrier frequency offsets (CFOs). In sub-band based OFDMA systems, users occupy consecutive and non-overlapping frequency sub-bands. The pilots are usually placed on the edges of a sub-band for channel estimation. However, the channel estimation performance is seriously degraded by the MUI. Traditionally, the MUI is alleviated by inserting a guard sub-carrier between adjacent users. In this paper, a novel pilot architecture is proposed, where three pilots are placed on each edge of a sub-band and pilots of adjacent users are overlapped. The proposed architecture has the same bandwidth efficiency as that of the conventional guard sub-carrier insertion scheme and provides better channel estimation performance and MUI reduction.

Orthogonal Frequency Division Multiple Access (OFDMA) is a promising technique which can provide high capacity in the wireless environments. Also cooperative communications are effectively used to achieve cooperative diversity for high reliability. In this paper, we propose the pair-based OFDMA frame structure in which cooperative users transmit their blocks in turns for achieving cooperative diversity in OFDMA systems. In order to guarantee the fairness of users we also propose a dynamic resource allocation scheme based on cooperative communications. Through the proposed scheme, user fairness can be achieved by sharing the remained capacity of users near the base station (BS) with users who are farther from the base station. For this purpose, the center-located users select their partner whose channel suffers the lowest SNR to BS among their neighbor set. Based on the partner selection results, subchannels are assigned to cooperative and non-cooperative users. Through simulations in the IEEE 802.16e system environments, it is shown that the proposed scheme outperforms the non-cooperation based scheme in terms of user fairness.

In this paper, we mathematically derive a matrix-form solution named resource allocation matrix (RAM) for sub-band allocation in an orthogonal frequency division multiple access (OFDMA) system. The proposed scheme is designed to enhance throughput under a strict user fairness condition such that every user has an equal number of sub-bands per frame. The RAM designates the most preferable sub-band for every user. The proposed scheme is evaluated in terms of throughput and user fairness by comparison with the proportional fairness (PF) scheme and greedy scheme. Numerical results show that the proposed scheme has overwhelming superiority to other schemes in terms of fairness and tight competitive in terms of throughput.