Subcarrier Power Allocation Research Articles

MMSE-based-filter and artificial noise design for MIMO–OFDM systems

Physical layer security is a crucial issue in wireless networks to prevent legitimate communication from eavesdropping. This paper investigates the physical layer security of a wireless multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) communication system in the presence of a multiple-antenna eavesdropper. We first propose a minimum mean square error (MMSE)-based-filter secure MIMO–OFDM system which can destroy the orthogonality of eavesdropper’s signals. The MMSE-based-filter is used at the receiver to suppress the inter-subcarrier interference and disturb the reception of eavesdropper while maintaining the quality of legitimate transmission. Next, we propose another artificial noise (AN)-assisted secure MIMO–OFDM system to further improve the security of the legitimate transmission. The time-domain AN signal is designed to be canceled out at the legitimate receiver. Therefore, AN will disturb the reception of eavesdropper while the legitimate transmission will not be affected. Finally, power allocation for AN signals and subcarriers will be discussed since AN is generated utilizing the residual power of the MIMO–OFDM system. Simulation results are presented to demonstrate the security performance of the proposed transmit filter design and AN-assisted scheme in the MIMO–OFDM system.

Multimedia transmission in MC-CDMA using adaptive subcarrier power allocation and CFO compensation

ABSTRACTMulticarrier code division multiple access (MC-CDMA) system is one of the most effective techniques in fourth-generation (4G) wireless technology, due to its high data rate, high spectral efficiency and resistance to multipath fading. However, MC-CDMA systems are greatly deteriorated by carrier frequency offset (CFO) which is due to Doppler shift and oscillator instabilities. It leads to loss of orthogonality among the subcarriers and causes intercarrier interference (ICI). Water filling algorithm (WFA) is an efficient resource allocation algorithm to solve the power utilisation problems among the subcarriers in time-dispersive channels. The conventional WFA fails to consider the effect of CFO. To perform subcarrier power allocation with reduced CFO and to improve the capacity of MC-CDMA system, residual CFO compensated adaptive subcarrier power allocation algorithm is proposed in this paper. The proposed technique allocates power only to subcarriers with high channel to noise power ratio. The performance of the proposed method is evaluated using random binary data and image as source inputs. Simulation results depict that the bit error rate performance and ICI reduction capability of the proposed modified WFA offered superior performance in both power allocation and image compression for high-quality multimedia transmission in the presence of CFO and imperfect channel state information conditions.

Power Allocation for OFDM Wireless Network Localization Under Expectation and Robustness Constraints

In location-aware wireless networks, mobile nodes (agents) can obtain their positions using range measurements to other nodes with known positions (anchors). Optimal subcarrier power allocation at the anchors reduces positioning error and improves network lifetime and throughput. We present an optimization framework for subcarrier power allocations in network localization with the imperfect knowledge of network parameters based on the fundamental statistical limits. Power allocations with expectation and robustness constraints are obtained using semidefinite optimization problems in non-iterative and iterative forms with both unicast and multicast transmissions. Results show that the allocations provide more accurate localization than non-robust designs under channel and agents positions uncertainty.

A Resource Allocation Scheme for Multi-D2D Communications Underlying Cellular Networks with Multi-Subcarrier Reusing

Device-to-device (D2D) communication is proposed as a promising technique of future cellular networks which fulfills its potential in terms of high resource utilization. In this paper, in order to improve the achievable rate of D2D communication and the spectrum utilization, we consider the scenario that multiple D2D pairs can share uplink spectrum resources with multiple cellular users (CUs). We aim to maximize the overall system spectrum efficiency while satisfying the rate requirements of all CUs and guaranteeing that the system gain is positive. We formulate the joint optimization problem of subcarrier assignment and power allocation which falls naturally into a mixed integer non-linear programming form that is a difficult problem to solve. Hence, we propose a two-stage resource allocation scheme which comprises a subcarrier assignment by employing a heuristic greedy strategy, as well as a power allocation algorithm based on the Lagrangian dual method. Numerical results demonstrate the advantageous performance of our scheme in greatly increasing the system sum spectrum efficiency.

Fairness-Aware and Energy Efficiency Resource Allocation in Multiuser OFDM Relaying System

A fairness-aware resource allocation scheme in a cooperative orthogonal frequency division multiple (OFDM) network is proposed based on jointly optimizing the subcarrier pairing, power allocation, and channel-user assignment. Compared with traditional OFDM relaying networks, the source is permitted to retransfer the same data transmitted by it in the first time slot, further improving the system capacity performance. The problem which maximizes the energy efficiency (EE) of the system with total power constraint and minimal spectral efficiency constraint is formulated into a mixed-integer nonlinear programming (MINLP) problem which has an intractable complexity in general. The optimization model is simplified into a typical fractional programming problem which is testified to be quasiconcave. Thus we can adopt Dinkelbach method to deal with MINLP problem proposed to achieve the optimal solution. The simulation results show that the joint resource allocation method proposed can achieve an optimal EE performance under the minimum system service rate requirement with a good global convergence.

Subcarrier Assignment and Power Allocation for Preference-Aware Multicast Services in Active Array Aided LTE Networks

Subcarrier Assignment and Power Allocation for Preference-Aware Multicast Services in Active Array Aided LTE Networks

Distributed joint subcarrier and discrete power allocation for cognitive radio ad hoc networks

One of the key problems in orthogonal frequency division multiple-access (OFDMA) cognitive radio (CR) ad hoc networks is to efficiently and fairly allocate subcarriers and powers in a distributed manner. However, two formidable shortcomings exist in most previous works. One is that the fairness issue has not been sufficiently taken into account so that different types of fairness among secondary users (SUs) may not be guaranteed. The other is that the transmission power of each SU is assumed to take any value in a continuous domain, whereas for practical CR ad hoc networks, the power level can only be quantized into discrete values. To overcome the above shortcomings, an optimization framework is first presented, where different types of fairness for resource allocation are considered and the transmission power of each SU is allowed to take only a finite number of discrete values. In particular, the fairness of resource allocation is guaranteed by associating each SU with a utility function for each subcarrier, where the utility function is allowed to be non-concave or non-differentiable so that our framework can deal with resource allocation for real-time applications. Furthermore, to solve the proposed non-convex integer optimization problem, a distributed algorithm with low complexity is proposed, according to which only limited cooperation among network entities is required. At last, simulation results verify that our algorithm has very good convergence and fairness performance, and then it may be applied to practical OFDMA-based CR ad hoc networks.

Improved power loading scheme for orthogonal frequency division multiplexing based cognitive radio

A subcarrier power allocation scheme for orthogonal frequency division multiplexing (OFDM) based cognitive users has been proposed for spectrum sharing with primary users (PU) allowing secondary users (SU) to coexist in same as well as adjacent frequency bands by underlay and interweave approaches respectively. The SU sum capacity of reliable communication has been maximised under the constraints of total power, each sub-channel power and PU aggregate interference limits. Based on the quality of channel gains and spectral distance from PU bands, the powers of subcarriers adjacent to PU bands are suitably controlled till the interference constraint of PUs are satisfied. Controlled subcarrier deactivation achieved by augmenting this ‘n-adjacent’ power redistribution step to traditional OFDM water-filling gives a powerful tool for efficiently maintaining high SU sum capacity without exceeding PU interference tolerance limit for a wide range of total power budget. Different water levels get assigned for the adjacent and non-adjacent subcarrier groups. In terms of SU capacity and PU interference, the proposed algorithm outperforms some of the existing schemes having almost same complexity as the proposed one. The improvement is significant when the adjacent subcarriers channel gains are relatively ‘good’ or ‘bad’ compared with the non-adjacent ones.

Fair subcarrier-power allocation scheme for multiuser multicarrier systems

The main objective of multiuser orthogonal frequency division multiple access (MU-OFDM) is to maximize the total system capacity in wireless communication systems. Thus, the problem in MU-OFDM system is the adaptive allocation of the resources (subcarriers, bits and power) to different users subject to several restrictions to maximize the total system capacity. In this work, a proposed subcarrier allocation algorithm was presented to assign the subcarriers with highest channel gain to the users. After the subcarrier allocation, subcarrier gain-based power allocation (SGPA) was employed for power and bit loading. The simulation results show that the proposed subcarrier-power allocation scheme can achieve high total system capacity and good fairness in allocating the resources to the users with slightly high computational complexity compared to the existing subcarrier allocation algorithms.

Sum-Rate Optimal Network Beamforming and Subcarrier Power Allocation for Multi-Carrier Asynchronous Two-Way Relay Networks

In this paper, we consider a multicarrier asynchronous bidirectional relay network, where different relay-transceiver links can cause different delays in the signals they convey, thereby producing inter-symbol-interference at the two transceivers. Such a two-way relay link can be modeled as a frequency selective channel with multiple taps, and thus, it can be equalized using orthogonal frequency division multiplexing (OFDM) transmission and reception schemes at the two transceivers, while the relays use simple amplify-and-forward relaying protocol. We prove rigorously that maximizing the sum-rate under a total power budget, through jointly optimal network beamforming at the relays and subcarrier power loading at the two transceivers, leads to a relay selection scheme, where only those relays which contribute to one tap of the end-to-end channel impulse response, have to be active and the remainder of the relays have to be switched off. The optimal tap can then be obtained using a simple search method. Moreover, we present semi-closed-form solutions for the optimal value of transceivers' subcarrier powers as well as for the relay beamforming weights.

Network-coded primary-secondary cooperation in OFDM-based cognitive multicast networks

Abstract This paper investigates resource allocation for network-coded primary-secondary cooperation in orthogonal frequency division multiplexing (OFDM)-based cognitive multicast networks, in which cognitive radio (CR), network coding (NC), multicast, and OFDM are effectively combined toward the spectrum efficient fifth generation (5G) wireless communication systems. Different from the conventional one-to-one/one-to-more primary-secondary cooperation, the paper concentrates on two-to-one primary-secondary cooperation, in which one secondary user (SU) cooperates with two primary users (PUs) to gain more spectrum access opportunities. To accomplish the cooperation, an agreement is established between the SU and PUs. Meanwhile, to alleviate spectrum bands consumed for PUs’ data transmission, network coding is employed at the SU transmitter. Subject to per-primary-user minimum rate requirement and the total power budget at the secondary transmitter, the investigated primary-secondary cooperation strategy is formulated as a mixed integer optimization problem with the aim of maximizing the average multicast transmission rate. The formulated problem is non-convex and difficult to solve directly. In this paper, a stepwise optimization algorithm is proposed in which the subcarrier assignment and power allocation are executed separately to reduce the computation complexity. The simulation results show that compared to existing schemes, the achieved secondary multicast transmission rate in the proposed scheme is greatly improved. The presented network-coded primary-secondary cooperation is a promising paradigm to improve the spectrum efficiency for the future 5G systems.

Energy-Efficient Resource Allocation for Multi-Cell OFDM Networks

ABSTRACTThis paper studies the downlink energy-efficient resource allocation in multi-cell orthogonal frequency division multiple networks with different user distributions in each cell. A non-convex optimization problem is formulated to maximize the energy efficiency of the whole network, which takes the user distribution in each cell as a fairness weight and considers the circuit power consumption and minimum data rate requirement. The optimization problem in fractional form is transformed into an equivalent optimization problem in subtractive form using Dinkelbach method and an iterative algorithm is proposed, in which the subcarrier allocation and power allocation are implemented separately. Heuristic graph-based algorithm is first proposed to achieve the subcarrier allocation and dual decomposition method is adopted to derive the optimal power allocation strategy to maximize the energy efficiency. Simulation results show that the proposed iterative resource allocation algorithm can achieve the maximum energy efficiency in a few iterations and balance capacity between cells with different load conditions which is represented by the relative user density in this paper. Moreover, trade-off between energy-efficiency and network capacity is also unveiled.

Network Coding for Intra-Cell Communications in OFDMA Networks

In this letter, we consider a new communication scenario in cellular networks, which is called intra-cell communications (ICC) , for which user pairs within the same cell exchange information through the base station (BS). A network coding based protocol is proposed to assist ICC in OFDMA networks to improve the spectral efficiency. In the uplink, each user accesses the BS following the OFDMA principle, while in the downlink, the BS transmits to each of the user pairs using the OFDMA principle. To do so, the BS performs bit level XOR (BLX) operation on the information bits received from each user pair. The output is then transmitted back to the same user pair through subcarrier sharing. We formulate the joint uplink/downlink subcarrier assignment and power allocation problem to maximize the weighted sum rate. While the formulated problem is non-convex, an asymptotically optimal, yet low complexity algorithm is proposed. Simulation results are presented to verify that the proposed protocol outperforms subcarrier pairing and assignment schemes which require no subcarrier sharing in both uplink and downlink.

Genetic Algorithm Based QoS Aware Adaptive Subcarrier Allocation in Cognitive Radio Networks

In this paper, an adaptive subcarrier allocation scheme with reconfiguration of operating parameters for Cognitive Radio Networks (CRN) is presented. A QoS-conscious spectrum decision frame work is projected, where spectrum bands are determined by considering the application requirements as well as the dynamic nature of the spectrum bands. The novel subcarrier allocation algorithm is developed to fulfill different performance objective as a solution for subcarrier allocation and power allocation problem for Cognitive Radio (CR) users in CRNs. It employs operating frequency parameter modification using Proportional Resource Algorithm and Genetic Algorithm (GA). The multi objective optimization problem with equality and inequality constraint is considered. Moreover, a dynamic subcarrier allocations scheme is developed based on GA to decide on the spectrum bands adaptively dependent on the time-varying CR network capacity. The proposed algorithm targets to achieve maximum data rate for each subcarrier, maximize the overall network throughput and maximize the number of satisfied user under the constraints of bandwidth and guarantee Quality of Service (QoS) requirement from dynamic spectrum management (DSM) perspective. Moreover, it determines the best available channel.

An Energy-efficiency Approach for Bidirectional Amplified-and-forward Relaying with Asymmetric Traffic in OFDM Systems

Two-way relaying is an effective way of improving system spectral efficiency by making use of physical layer network coding. However, energy efficiency in OFDM-based bidirectional relaying with asymmetric traffic requirement has not been investigated. In this study, we focused on subcarrier transmission mode selection, bit loading, and power allocation in a multicarrier single amplified-and-forward relay system. In this scheme, each subcarrier can operate in two transmission modes: one-way relaying and two-way relaying. The problem is formulated as a mixed integer programming problem. We adopt a structural approximation optimization method that first decouples the original problem into two suboptimal problems with fixed subcarrier subsets and then finds the optimal subcarrier assignment subsets. Although the suboptimal problems are nonconvex, the results obtained for a single-tone system are used to transform them to convex problems. To find the optimal subcarrier assignment subsets, an iterative algorithm based on subcarrier ranking and matching is developed. Simulation results show that the proposed method can improve system performance compared with conventional methods. Some interesting insights are also obtained via simulation.

BER modified decode-and-forward protocol for OFDM-based linear multihop networks

In orthogonal frequency division multiplexing (OFDM) based multihop communications, the conventional decode-and-forward (DF) relay scheme severely suffers from the error propagation problem. This drawback is serious in multihop networks as errors made by any relay node may fail the decoder at the destination in great chance. In this paper, we propose a bit error rate (BER) modified DF protocol (BMDF) which can be applied to systems where error correction channel coding and M-ary modulation are used. By modeling all links except the last one as a binary symmetric channel (BSC), we derive a log likelihood ratio (LLR) modification function relying only on the accumulated BER of all previous links to be applied to the output of the soft demapper. Furthermore, to reduce the computational complexity and signaling overhead, the modification function is simplified from its original exponential expression and less BERs are delivered between nodes by making successive subcarriers share the same BER. In addition, for situations where the channel state information (CSI) of forward link is available, the proposed BMDF can be further enhanced by combining with subcarrier pairing (SP) and power allocation (PA), where a sorted-channel gain SP scheme and a greedy PA algorithm are proposed. The simulation results verify the significant performance improvement to the conventional DF.

Cooperative Subcarrier Allocation and Power Allocation in the Downlink of an Amplify-and-Forward OFDM Relaying System

The increasing use of relays in wireless communication systems is a driving force to explore innovative techniques that can improve the quality of service as well as enhance the coverage in wireless systems. In this article, we propose a two-step approach for subcarrier allocation and power allocation in the downlink of an OFDM-based amplify-and forward relaying system. In the first step, the total power is allocated to mobile users and relays based on the optimum power ratio derived for the single-relay system. In the second step, subcarriers are assigned to the users based on cooperative subcarrier allocation algorithms. Compared to the non-cooperative algorithm with flat power allocation, the total throughput is shown to improve by applying the two-step cooperative subcarrier allocation and power allocation algorithms.

Sequential Optimization for Subcarrier Pairing and Power Allocation in CP-SC Cognitive Relay Systems

A sequential optimization algorithm (SOA) for resource allocation in a cyclic-prefixed single-carrier cognitive relay system is proposed in this study. Both subcarrier pairing (SP) and power allocation are performed subject to a primary user interference constraint to minimize the mean squared error of frequency-domain equalization at the secondary destination receiver. Under uniform power allocation at the secondary source and optimal power allocation at the secondary relay, the ordered SP is proven to be asymptotically optimal in maximizing the matched filter bound on the signal-to-interference-plus-noise ratio. SOA implements the ordered SP before power allocation optimization by decoupling the ordered SP from the power allocation. Simulation results show that SOA can optimize resource allocation efficiently by significantly reducing complexity.

Subcarrier-pair Based Power Allocation for Cooperative OFDM AF Multi-Relay Networks

For conventional subcarrier pairing schemes in cooperative orthogonal frequency division multiplexing amplify and forward multi-relay networks, to avoid interference, each subcarrier pair (SP) is assigned to only one relay. Over a specific subcarrier, the destination receives signals transmitted from only one relay. In our subcarrier pairing scheme, we assign each SP to all the relays. Thus, over a specific subcarrier, the destination receives signals transmitted from all the relays. Since it is assumed that there exists the direct link from the source to the destination, we assume that the source also transmits signals during the second time slot for the direct transmission mode. We propose an enhanced joint subcarrier pairing and power allocation optimization scheme which maximizes the transmission rate subject to total network power constraint. The problem is simplified and solved by using dual method. It is shown from simulation results that our proposed scheme outperforms the other schemes.

Interference Coordination with Fractional Frequency Reuse in Downlink OFDMA Networks

This paper investigates interference coordination for cell-center and cell-edge users in multicell Orthogonal Frequency Division Multiple-access (OFDMA) wireless networks. The objective of our interference coordination scheme is to maximize both of the cell-edge and cell-center users’ throughput, subject to per-base-station (per-BS) power constraints. Here, we assume the data symbols of each user are only known by one BS. Referring to the Fractional Frequency Reuse (FFR) scheme, the resources for cellcenter and cell-edge users are partitioned. On the basis of such resource partitioning, we present a novel Dynamic Coordinated Transmission (DCT) scheme to solve the interference coordination problem. The corresponding subcarrier assignment and power allocation are performed in the DCT scheme. Simulation results show that the proposed DCT scheme improves the cell-edge users’ performance, and yields up a certain overall cell throughput enhancement with low computational complexity.