Downlink OFDMA System Research Articles

Energy-Efficient Power and Subcarrier Allocation in Downlink OFDMA Systems with Channel Estimation Errors

In this paper, we investigate the joint optimization of power and subcarrier allocation for maximizing the energy efficiency (EE) in downlink OFDMA systems. The problem of EE maximization is formulated as a stochastic optimization to determine the optimal power and subcarrier allocation, in which many practical factors including channel estimation errors, delay requirements, and time-varying channel are considered. We first propose a dynamic power and subcarrier allocation (DPSA) algorithm to solve the formulated problem. Then, we derive the two bounds of EE and delay and reveal the tradeoff between them. The theoretical analysis and simulation results demonstrate the variations of EE and delay with channel estimation errors.

Dynamic power and subcarrier allocation for downlink OFDMA systems under imperfect CSI

In this paper, we investigate the joint power and subcarrier allocation for the downlink of orthogonal frequency division multiplexing access systems, with various practical considerations including imperfect estimation of channel state information, a stochastic packet arrival and a time-varying channel. To this end, we formulate the stochastic optimization problem to minimize the time-averaged power consumption, whilst keeping all queues at the base-station stable. The data transmission rate is defined as a function of the transmit power, the assigned subcarrier and the estimation error. With the aid of Lyapunov optimization method, the original problem is transformed into a series of mixed-integer programming problems, which are then solved via the dual decomposition technique. We determine analytical bounds for the time-averaged power consumption and queue length achieved by our proposed algorithm, which depend on the channel estimation error. Moreover, the theoretical analysis and simulation results show that the proposed algorithm reduces the energy consumption at the expense of queue backlog (i.e., achieves a energy-queue tradeoff), and quantitatively strike the energy-queue tradeoff by simply tuning an introduced control parameter V.

Power-Efficient QoE-Aware Video Adaptation and Resource Allocation for Delay-Constrained Streaming Over Downlink OFDMA

In this letter, we propose a QoE-aware video adaptation and resource allocation approach for power-efficient streaming over downlink OFDMA systems. Our adaptation scheme selectively drops packets from a video stream to produce a lower bit-rate version under QoE and delay constraints. This results in a reduction of the load and an increase of the video capacity of the wireless network. Our resource allocation target is to minimize the transmit power by considering the delay requirements of each stream identified in the video adaptation phase. Experimental results have shown significant performance enhancement of the proposed system in terms of end-to-end delay and power efficiency while satisfying QoE requirements.

Providing Services for the High-Speed Train and Local Users in the Same OFDMA System: Resource Allocation in the Downlink

We consider providing broadband wireless services for passengers in a high-speed train and local users (low-mobility users) in the same OFDMA system. For the train, a two-hop architecture, under which, passengers communicate with base stations (BSs) via a mobile relay (MR) is employed. Then all passengers in the train can be treated as one large user represented by the MR. Since the channel conditions of the MR and local users are different in both large scale-fading and small-scale fading, we allocate the system resources over two time-scales for them. We formulate the resource allocation problem in the downlink OFDMA system as a capacity optimization problem for the MR subject to the sum capacity constraint of local users. We discuss the problem in two cases where perfect intercarrier interference (ICI) cancellation and no ICI cancellation are applied at the MR. The corresponding capacities and optimal power and subcarrier allocation (OPSA) policies are presented for each case. The capacities obtained in these two cases bound the achievable transmission rate of the MR and provide meaningful guidance for the application of ICI cancellation. Finally, the implementation issues of resource allocation policies are discussed to simplify application in practical scenarios.

WIRELESS INFORMATION AND ENERGY TRANSFER: TRADEOFF FOR FAIR RESOURCE ALLOCATION

In this paper, we study two schemes for the fair resource allocation in wireless powered communication networks (WPCNs): a non-orthogonal multiple access (NOMA) scheme, and a proportional fair (PF) scheduling scheme. The considered WPCN consists of a base station (BS) that broadcast radio frequency (RF) energy over the downlink, and N energy harvesting users (EHUs). If NOMA is employed, all EHUs concurrently transmit information over the uplink with successive interference cancellation employed at the BS. If PF scheduling is employed, a single EHU is selected for uplink transmission in each frame. For both schemes, we arrive at optimal allocations for the BS transmit power and the time sharing between uplink and downlink transmissions that maximize the uplink sum-rate, while maintaining high level of system fairness. For the PF scheme, we also derive the optimal scheduling policy. Compared to the state-of-the art schemes based upon time division multiple access (TDMA), both schemes significantly improve the system fairness at the expense of minor (or nonexistent) rate degradation. Key words: energy harvesting; wireless powered communication networks; non-orthogonal multiple access; successive interference cancelation; proportional fair scheduling REFERENCES: [1] P. Grover, A. Sahai: Shannon meets Tesla: wireless information and power transfer, Proc. IEEE ISIT 2010, pp. 2363–2367, Austin, USA, June 2010. [2] D. Gunduz, K. Stamatiou, N. Michelusi, M. Zorzi: Designing intelligent energy harvesting communication systems, IEEE Commun. Magazine, 52, 1, 210–216 (Jan.2014). [3] C. K. Ho, R. Zhang: Optimal energy allocation for wireless communications with energy harvesting constraints, IEEE Trans. Signal Proccessing, 60, 9, 4808–4818 (May 2012). [4] H. Ju, R. Zhang: Throughput maximization in wireless powered communication networks, IEEE Trans. Wireless Commun., 13, 1, 418–428 (Jan. 2014). [5] X. Kang, C. Ho Keong, S. Sun: Optimal time allocation for dynamic-TDMA-based wireless powered communication networks, Proc. IEEE Globecom 2014, Austin, USA, Dec. 2014. [6] H. Ju, R. Zhang: Optimal resource allocation in full-duplex wireless-powered communication network, IEEE Trans. on Commun., 62, 10, 3528–3540 (Oct. 2014). [7] T. Takeda, K. Higuchi: Enhanced user fairness using non-orthogonal access with SIC in cellular uplink, VTC 2011, San Francisco, USA, pp. 1–5, 2011. [8] Z. Ding, Z. Yang, P. Fan, H. V. Poor: On the performance of non-orthogonal multiple access in 5G systems with randomly deployed users, IEEE Signal Process. Lett., 21, 12, 1501–1505 (2014). [9] S. Timotheou, I. Krikidis: Fairness for non-orthogonal multiple access in 5G systems, IEEE Signal Process. Lett., 22, 10, 1462–1465 (2015). [10] H. Chingoska, Z. Hadzi-Velkov, I. Nikoloska, N. Zlatanov: Resource Allocation in Wireless Powered Communication Networks with Non-Orthogonal Multiple Access, IEEE Wireless Communications Letters, 5 (6), 684–687 (2016). [11] P. Viswanath, D. N. Tse, R. Laroia: Opportunistic beamforming using dumb antennas, IEEE Trans. Information Theory, 46, 6, 1277–1294 (June 2002). [12] N. Tekbiyik, T. Girici, E. Uysal-Biyikoglu, K. Leblebicioglu: Proportional fair resource allocation on an energy harvesting downlink, IEEE Trans. Wireless Communications, 12, 4, 1699–1711 (April 2013). [13] H. Chingoska, I. Nikoloska, Z. Hadzi-Velkov, N. Zlatanov: Proportional fair scheduling in wireless powered communication networks, 23rd International Conference on Telecommunications (ICT), May 2013. [14] Z. Hadzi-Velkov, I. Nikoloska, H. Chingoska, N. Zlatanov, Proportional fair scheduling in wireless networks with RF energy harvesting and processing cost, IEEE Comm. Letters, 20, 10, 2107–2110 (2016). [15] T.-D. Nguyen, Y. Han: A Proportional Fairness Algorithm with QoS Provision in Downlink OFDMA Systems, IEEE Comm. Letters, 10, 11 (Nov. 2006). [16] Z. Hadzi-Velkov, I. Nikoloska, G. K. Karagiannidis, T. Q. Duong: Wireless networks with energy harvesting and power transfer: joint power and time allocation, IEEE Signal Process. Letters, 23, 1, 50–54 (Jan. 2016). [17] R. Jain, D. Chiu, W. Hawe: A Quantitative measure of fairness and discrimination for resource allocation in shared computer systems, Tech. Rep. TR-301, DEC, September 1984. [18] W. Yu, R. Lui: Dual methods for nonconvex spectrum optimization of multicarrier systems, IEEE Trans. Commun., 54, 7, 1310–1322 (Jul. 2006). [19] L. Liu, R. Zhang, K.-C. Chua: Wireless information transfer with opportunistic energy harvesting, IEEE Trans. Wireless. Commun., 12, 1, 288–300 (Jan. 2013).

Impact of Random Packet Arrival on the Performance of Video Streaming over OFDMA Downlink Systems

Streaming multiple video sessions over wireless networks is challenging due to the scarcity of wireless resources and the channel variations. Orthogonal frequency-division multiple access is an app...

Energy efficiency optimization for downlink OFDMA system in heterogeneous network with QoS constraints

SummaryEnergy efficiency (EE) has currently turn into one of the major issues in heterogeneous networks (HetNet) paradigm of today's wireless communication industry. In this paper, we optimize EE for downlink OFDMA system in HetNet, taking into account realistic network power consumption model, that is, considering circuit power. This paper investigates the EE maximization using convex optimization theory where primary optimization criterion is data rate in a downlink multiuser HetNet. Given QoS (data rate) requirement, for maximizing EE, a constrained based optimization problem is devised. Because the optimization problem is non‐convex in nature, we reconstruct the optimization problem as a convex one and devise a pragmatically efficient novel resource assignment algorithm for maximizing achievable EE, with quick convergence. The considered optimization problem is transformed into a convex optimization problem by redefining the constraint using cubic inequality, which results in an efficient iterative resource allocation algorithm. In each iteration, the transformed problem is solved by using dual decomposition with a projected gradient method. Analytical insights and numerical results exhibit the potency of the devised scheme for the targeted complex wireless systems. Copyright © 2015 John Wiley & Sons, Ltd.

Throughput Maximization with Short-Term and Long-Term Jain's Index Constraints in Downlink OFDMA Systems

We aim to maximize system throughput subject to constraints on both short-term and long-term fairness in terms of Jain's index in single cell downlink OFDMA systems, where the transmission power is fixed. While it is accepted that short-term fairness implies long-term fairness, we find that this is not always true. Noting that long-term performance metric is the average of short-term ones, we point out that it depends on the averaging method and the fairness definition. We prove that short-term throughput Jain's index implies long-term throughput Jain's index. Therefore, we can remove the long-term fairness constraint if it is looser than the short-term constraint. Otherwise, we heuristically replace the long-term fairness constraint by a cumulative fairness constraint. We relax the considered discrete subchannel and slot allocation problem into a continuous convex problem, which can be efficiently solved. Then, the discrete resource allocation is derived by rounding the optimal solution. The analysis indicates that the rounding error is small. Simulation results show that we obtain a good suboptimal solution with small deviations from the optimal relaxed system throughput and the Jain's index constraints. Moreover, comparing with the strategies that take into account only long-term fairness, we guarantee both long-term and short-term fairness.

Adaptive resource management for downlink OFDMA system with imperfect CSI

The effect of the imperfect channel state information (CSI) on the system performance of radio resource management is addressed for a downlink OFDMA system. Differing from the previous works, it is shown that the imperfect CSI introduces a signal-and-power dependent noise term, and then a new method is proposed to evaluate the utility function. Numerical simulations show that the signal-and-power dependent noise yields a non-negligible degradation to the system performance.

Efficiency and fairness aware resource allocations for energy and spectrum in downlink OFDMA systems

Energy has newly become a scarcer resource for the wireless networks, like spectrum. To utilise the limited resources efficiently and fairly in the downlink OFDMA systems, a novel resource allocation problem is investigated to make the balance between energy efficiency (EE) and spectrum efficiency (SE), the tradeoff between fairness and SE/EE. The problem is first formulated as an optimisation problem, which is NP-hard. Then, the existence of an optimal solution is proved, and an algorithm is designed to obtain the optimal solution. Finally, the numerical results show that the proposed algorithm achieves the SE–EE balance and provides a good tradeoff between fairness and SE/EE.

Efficient channel state feedback scheme for opportunistic scheduling in OFDMA systems by scheduling probability prediction

In this paper, we propose a new feedback scheme called mode selection-based feedback by scheduling probability prediction (SPP-MF) for channel state feedback in OFDMA downlink system. We design the scheme such that it determines the more desirable feedback mode among selective feedback by scheduling probability prediction (SPP-SF) mode and bitmap feedback by scheduling probability prediction (SPP-BF) mode, by calculating and comparing the throughputs of the two modes. In both feedback modes, each user first calculates the scheduling probability of each subchannel (i.e., the probability that a user wins the scheduling competition for a subchannel) and then forms a feedback message based on the scheduling probability. Specifically, in the SPP-SF mode, each user reports the modulation and coding scheme (MCS) levels and indices of its best S subchannels in terms of the scheduling probability. In the SPP-BF mode, each user determines its scheduling probability threshold. Then, it forms a bitmap for the subchannels according to the scheduling probability threshold and sends the bitmap along with the threshold. Numerical results reveal that the proposed SPP-MF scheme achieves significant performance gain over the existing feedback schemes.

Joint subcarrier and power allocation in downlink OFDMA systems: an multi‐objective approach

ABSTRACTIn this paper, we present a new technique for resource allocation in multi‐user orthogonal frequency division multiple access systems. The goal is to maximise the minimum data rate available to any user while minimising the total transmitted power. In order to achieve an optimal solution and capacity bounds, the subcarrier and power should be allocated simultaneously. Multi‐objective genetic algorithm can be used for joint allocation of subcarriers and power in such a case, and in this paper, it is achieved using non‐dominated sorting genetic algorithm‐II. The simulation results indicate that the proposed algorithm achieves high data rates as compared with previous algorithms. The algorithm allocates both subcarriers and bits jointly without being computationally expensive. The faster convergence of the algorithm to near optimal value, as compared with previous algorithms, is indicative of its less complexity. Copyright © 2013 John Wiley & Sons, Ltd.

Joint Channel Shortening and Carrier Frequency Offset Estimation Based on Carrier Nulling Criterion in Downlink OFDMA Systems

In this letter, we present a joint blind adaptive scheme to suppress inter-block interference and estimate a carrier frequency offset (CFO) in downlink OFDMA systems. The proposed scheme is a combination of a channel shortening method and a CFO estimator, both based on the carrier nulling criterion. Simulation results demonstrate the effectiveness of the proposed scheme.

Energy Minimization in OFDMA Downlink Systems: A Sequential Linear Assignment Algorithm for Resource Allocation

We propose a sequential linear assignment algorithm (SLAA) for resource allocation of OFDMA systems consisting of M users and N (N >; M) resource blocks, with the aim of achieving near optimal energy consumption with polynomial complexity. The proposed SLAA allocates subchannels through a linear assignment algorithm (LAA), sequentially; thus, it requires O(MN2(N - M)2) complexity. From numerical results, the required power from the proposed assignment is observed to be within around 0.4 % of the lower bound of minimum possible power required to achieve the same target rates.

Optimal power and subcarriers allocation in downlink OFDMA system with imperfect channel knowledge

Most of existing work on resource allocation in TDMA and OFDMA systems assumes the availability of perfect channel state information (CSI) at the transmitter, which is rarely possible due to feedback delay and channel estimation error. In this paper, we study the effect of feedback delay and channel estimation error on margin adaptive resource allocation in a downlink OFDMA system. By using convex optimization framework, we find an optimal solution to the problem. First, we study the individual effect of feedback delay and channel estimation error on resource allocation by considering them exclusively. Then, we consider the simultaneous presence of feedback delay and channel estimation error and study their combined effect on resource allocation. We derive an explicit close form expression for the users’ transmit power and propose an algorithm for power and subcarriers allocation for each of these three scenarios. The algorithms have polynomial complexities and solve the problem with zero optimality gaps. Simulation results show that the system performance is very sensitive to feedback delay and is affected significantly by imperfect channel estimation. Our proposed algorithms highly improve the system performance in the availability of only imperfect CSI at the transmitter.

Adaptive Subcarrier and Bit Allocation for Downlink OFDMA System with Proportional Fairness

This paper investigates the adaptive subcarrier and bit allocation algorithm for OFDMA systems. To minimize overall transmitted power, we propose a novel adaptive subcarrier and bit allocation algorithm based on channel state information (CSI) and quality state information (QSI). A suboptimal approach that separately performs subcarrier allocation and bit loading is proposed. It is shown that a near optimal solution is obtained by the proposed algorithm which has low complexity compared to that of other conventional algorithm. We will study the problem of finding an optimal sub-carrier and power allocation strategy for downlink communication to multiple users in an OFDMA based wireless system. Assuming knowledge of the instantaneous channel gains for all users, we propose a multiuser OFDMA subcarrier, and bit allocation algorithm to minimize the total transmit power. This is done by assigning each user a set of subcarriers and by determining the number of bits and the transmit power level for each subcarrier. The objective is to minimize the total transmitted power over the entire network to satisfy the application layer and physical layer. We formulate this problem as a constrained optimization problem and present centralized algorithms. The simulation results will show that our approach results in an efficient assignment of subcarriers and transmitter power levels in terms of the energy required for transmitting each bit of information, to address this need, we also present a bit loading algorithm for allocating subcarriers and bits in order to satisfy the rate requirements of the links.

Joint Scheduling and Resource Allocation in OFDMA Downlink Systems Via ACK/NAK Feedback

In this paper, we consider the problem of joint scheduling and resource allocation in the OFDMA downlink, with the goal of maximizing an expected long-term goodput-based utility subject to an instantaneous sum-power constraint, and where the feedback to the base station consists only of ACK/NAKs from recently scheduled users. We first establish that the optimal solution is a partially observable Markov decision process (POMDP), which is impractical to implement. In response, we propose a greedy approach to joint scheduling and resource allocation that maintains a posterior channel distribution for every user, and has only polynomial complexity. For frequency-selective channels with Markov time-variation, we then outline a recursive method to update the channel posteriors, based on the ACK/NAK feedback, that is made computationally efficient through the use of particle filtering. To gauge the performance of our greedy approach relative to that of the optimal POMDP, we derive a POMDP performance upper-bound. Numerical experiments show that, for slowly fading channels, the performance of our greedy scheme is relatively close to the upper bound, and much better than fixed-power random user scheduling (FP-RUS), despite its relatively low complexity.

Sum Rate Analysis of a Reduced Feedback OFDMA Downlink System Employing Joint Scheduling and Diversity

We consider joint scheduling and diversity to enhance the benefits of multiuser diversity in an \OFDMA{} system. The \OFDMA{} spectrum is assumed to consist of $\Nrb$ resource blocks and the reduced feedback scheme consists of each user feeding back channel quality information (\CQI) for only the best-$\NFb$ resource blocks. Assuming largest normalized \CQI{} scheduling and a general value for $\NFb$, we develop a unified framework to analyze the sum rate of the system for both the quantized and non-quantized \CQI{} feedback schemes. Based on this framework, we provide closed-form expressions for the sum rate for three different multi-antenna transmitter schemes; Transmit antenna selection (\TAS), orthogonal space time block codes (\OSTBC) and cyclic delay diversity (\CDD). Furthermore, we approximate the sum rate expression and determine the feedback ratio $(\frac{\NFb}{\Nrb})$ required to achieve a sum rate comparable to the sum rate obtained by a full feedback scheme.

Dynamic Resource Allocation in Multi-Service OFDMA Systems with Dynamic Queue Control

We consider the problem of resource allocation in downlink OFDMA systems for multi service and unknown environment. Due to users' mobility and intercell interference, the base station cannot predict neither the Signal to Noise Ratio (SNR) of each user in future time slots nor their probability distribution functions. In addition, the traffic is bursty in general with unknown arrival. The probability distribution functions of the SNR, channel state and traffic arrival/density are then unknown. Achieving a multi service Quality of Service (QoS) while optimizing the performance of the system (e.g. total throughput) is a hard and interesting task since it depends on the unknown future traffic and SNR values. In this paper we solve this problem by modeling the multiuser queuing system as a discrete time linear dynamic system. We develop a robust H∞ controller to regulate the queues of different users. The queues and Packet Drop Rates (PDR) are controlled by proposing a minimum data rate according to the demanded service type of each user. The data rate vector proposed by the controller is then fed as a constraint to an instantaneous resource allocation framework. This instantaneous problem is formulated as a convex optimization problem for instantaneous subcarrier and power allocation decisions. Simulation results show small delays and better fairness among users.

Mode Selection-Based Channel Feedback Reduction Schemes for Opportunistic Scheduling in OFDMA Systems

In this paper, we present two new feedback schemes, namely the network mode selection-based feedback (NMF) and the user mode selection-based feedback (UMF), that reduce the feedback load needed for opportunistic scheduling in the OFDMA downlink system. The two schemes are designed to select either the selective feedback (SF) mode which feeds back the fine-grained condition of a part of the channels or the bit-map based feedback (BF) mode which feeds back the coarse-grained condition of all the channels using 1 bit for each channel, depending on the channel conditions of the users. Specifically, the NMF scheme makes the BS determine the more desirable feedback mode by predicting and comparing the average total throughputs of the two modes for the given statistical channel characteristics of the users. The UMF scheme makes each user determine its own feedback mode based on both its channel realization and the recommendation of the network. Numerical results reveal that the proposed NMF and UMF schemes achieve significant performance gain over the existing feedback reduction schemes with similar feedback load.