Improved subcarrier allocation in cooperative OFDMA system

This paper investigates relay selection and subcarrier allocation in cooperative OFDMA systems where users with best-effort (BE) service and rate-constrained (RC) service coexist. We formulate the problem as a binary integer linear programming to maximize the network data rate with quality-of-service (QoS) requirements. A greedy algorithm is proposed for the degradation problem of only BE users and a direct search algorithm for hybrid users is proposed to reduce the number of variables and the size of the constraint matrix. Simulation results demonstrate that the proposed algorithm significantly improves the computing speed and enhances the system total throughput.

In this paper, we study the joint allocation of three types of resources, namely, power, subcarriers and relay nodes, in multi-relay assisted dual-hop cooperative OFDM systems. All the relays adopt the amplify-and-forward protocol and assist the transmission from the source to destination simultaneously but on orthogonal subcarriers. The objective is to maximize the system transmission rate subject to individual power constraints on each node or a total network power constraint. We formulate such a problem as a subcarrier-pair based resource allocation that seeks the joint optimization of subcarrier pairing, subcarrier-pair-to-relay assignment, and power allocation. Using a dual approach, we solve this problem efficiently in an asymptotically optimal manner. Specifically, for the optimization problem with individual power constraints, the computational complexity is polynomial in the number of subcarriers and relay nodes, whereas the complexity of the problem with a total power constraint is polynomial in the number of subcarriers.We further propose two suboptimal algorithms for the former to trade off performance for complexity. Simulation studies are conducted to evaluate the average transmission rate and outage probability of the proposed algorithms. The impact of relay location is also discussed.

We study the joint allocation of three types of resources, namely, power, subcarriers and relay nodes, in cooperative two-hop multi-relay OFDM systems. Each relay adopts the amplify-and-forward (AF) protocol. The objective is to maximize the system transmission rate subject to individual power constraints on each node. We formulate such a problem as a subcarrier-pair based resource allocation that seeks the joint optimization of subcarrier pairing, subcarrier-pair-to-relay assignment, and power allocation. Using a dual decomposition method, we solve this problem efficiently in an asymptotically optimal manner. We further propose two suboptimal algorithms to trade off performance for complexity. Simulation results demonstrate that the proposed subcarrier-pair based resource allocation schemes significantly outperform the symbol based benchmark scheme. Moreover, it is shown that subcarrier pairing plays an important role in improving the system performance.

In this letter, a new secure information transmission scheme based on polar codes with a pre-shared secret key is proposed. In polar codes, after the channel polarization is induced, good split channels are used to transmit the user message and bad channels are utilized to support the reconstruction of the message by sharing fixed information. If the fixed information in bad channels is secret, an adversary gets difficulty in reconstructing the user message in good channels without knowledge of the fixed information. From this observation, we construct a secure information transmission scheme. By appending pre-/post-processing that imposes a dependency between the transmitted message sub-blocks, the adversary's difficulty can be changed to an intractability, since only partial information can be decodable by attackers. A new class of secret key scheme is developed in such a way.

In this paper, we investigate noncoherent detection methods for amplify-and-forward cooperative OFDM systems in frequency-selective block fading channels. In particular, by exploiting the time-frequency relationship of OFDM, a noncoherent detector is proposed for phase-shift keying modulated signals. The proposed noncoherent detector uses only one OFDM block signal for data detection, and therefore is suitable for relatively fast time-varying environments. We show that the noncoherent detection can be cast as a quadratic maximization problem, which can be efficiently solved by the convex approximation technique, namely, semidefinite relaxation. Simulation results demonstrate that the noncoherent detector exhibits near-coherent performance and outperforms channel-estimation-aided detection methods.

In cooperative systems, users achieve spatial diversity and multihop gains by transmitting packets over multiple independent fading paths provided by their partners. Most previous works on cooperative communications focus on the physical layer aspects such as coding, modulation, and transceiver signal processing techniques. In this work, we study the advantages of user cooperation from a MAC layer perspective and devise queueing strategies to exploit cooperative gains in random access networks. Based on the conventional slotted ALOHA protocol, we propose a simple cooperative transmission mechanism for a two-user cooperative pair. We derive the two-user stability region of the proposed system and show the improvements compared to noncooperative systems. The benefits can be attributed to both physical layer cooperation, where users with good channels may relay for those with bad channels, and MAC layer cooperation, where system parameters can be chosen to enhance cooperation and reduce competition. Then, we extend the proposed strategy to a finite-user system that consists of multiple cooperative pairs. By treating each pair as a single transmission entity, we derive inner bounds for the finite-user stability region and propose a ranking system to characterize the transmission entities' relative tendency of being stable (or unstable).

Cooperative multiuser OFDMA is an important technology for current and future wireless communications systems. A critical part of this technology is performing multiuser subcarrier resource allocation and a wide variety of techniques have been suggested that can increase overall throughput, decrease total transmit power or improve other key performance measures. A particular subcarrier resource allocation approach that is of interest in this paper is a method based on nodes that transmit and receive on adjacent OFDM subcarriers simultaneously. This approach has shown significant promise, but its feasibility has not been fully investigated. In particular there will be a performance tradeoff in realistic systems as adjacent subcarriers will not be completely isolated and there will be interference on the receiving subcarriers that are adjacent to those that are transmitting. In this paper we look into the performance of such cooperative OFDMA systems under realistic conditions. We propose a transceiver structure to reduce the interference between transmitting subcarriers and receiving subcarriers. Its performance in terms of signal to interference and noise ratio (SINR) is evaluated by both analysis and simulation and is incorporated into a recently proposed cooperation strategy for OFDMA systems to examine its performance under the realistic structure. It is shown that although the cooperation strategy suffers from performance degradation due to the residual interference between the transmitting and receiving subcarriers, it still outperforms the conventional cooperation schemes.

In this paper, we propose to design a call admission control algorithm which schedules the channels for real time and non-real time users based on Utility function. In Long Term Evolution (LTE) 3GPP Networks, several works were done on call admission control but these works rarely considers scheduling of resources to the real time and non-real time users. The call requests are classified into new call (NC) request and handoff call (HC) request and the type of services are classified as VoIP and video. Then based upon the received signal strength (RSS) value, the channel is estimated as good channel or bad channel. Resource allocation is made for VoIP users based on traffic density. Then non-VoIP users and the non-real time users are allocated resource blocks using the channel condition based marginal utility function. When there are no sufficient resources to allocate, it allocates the resources of bad channel users there by degrading their service. Thus from our simulation results we show that this admission control algorithm provides channel quality and prioritizes the handover calls over new calls which allocates resources to all kinds of users.

In this paper, we investigate a downlink non-orthogonal multiple access (NOMA) system consisting of a base station (BS) and two users, where each user decodes its own signal through successive interference cancellation (SIC). When the signal of one user, called the weak user (WU) who has a bad channel, is being decoded, the signal of the other user, called the strong user (SU) who has a good channel, acts as interference. In an interference channel, we can increase the achievable rate by applying improper Gaussian signaling (IGS). Therefore, we apply IGS to SU, aiming to mitigate the interference. We also consider imperfect SIC at SU, which is a more general assumption for a NOMA system. For the considered NOMA system model, we derive the outage probability of each user in a closed form, provide its asymptotic expression, and obtain its diversity order. We also derive the ergodic rate of each of the two users in a closed form. We propose two algorithms to maximize the fairness of the NOMA system based on the primal decomposition method. Through simulation, we verify that our analysis is correct, and confirm that applying IGS improves the fairness of the NOMA system.

This paper addresses the medium access control (MAC) and physical (PHY) cross-layer design of a time-division multiple access protocol (TDMA) where users with good channels are allowed to relay the packets of other users with less favorable conditions. All signals are combined at the central node using signal processing tools in order to achieve diversity. The work is focused on an asymmetrical scenario where users experience different channel and queuing states. Two performance metrics are used: packet throughput and access delay. To facilitate the analysis, a packet reception model which represents more efficiently the cooperative PHY layer is also proposed. A multi-objective optimization is used to derive the boundaries of the throughput region, i.e., the set of all achievable user throughput values. Sketches of the two-user case show that the region is always convex and larger than the region of its non-cooperative counterpart. The results also show that cooperation is useful when some users with good channels experience low/medium traffic loads and thus can help other users with bad channels and higher traffic loads. Evaluation of access delay is also obtained by using the expressions of a modified TDMA system.

In this paper we have studied the subcarrier and optimal power allocation strategy for OFDM-based cognitive radio (CR) networks. Firstly, in order to protect the primary user communication from the interference of the cognitive user transmissions in fading wireless channels, we design an opportunistic power control scheme to maximize the cognitive user capacity without degrading primary user's QoS. The mathematical optimization problem is formulated as maximizing the capacity of the secondary users under the interference constraint at the primary receiver and the Lagrange method is applied to obtain the optimal solution. Secondly, in order to limit the outage probability within primary user's tolerable range we analyze the outage probability of the primary user with respect to the interference power of the secondary user for imperfect CSI. Finally, in order to get the better tradeoff between fairness and system capacity in cognitive radio networks, we proposed an optimal algorithm of jointing subcarrier and power allocation scheme among multiple secondary users in OFDM-based cognitive radio networks. Simulation results demonstrate that our scheme can improve the capacity performance and efficiently guarantee the fairness of secondary users.

Cooperative communication and orthogonal frequency-division multiplexing (OFDM) technology are both promising candidates for next-generation wireless communication systems. In this paper, we investigate cooperation strategies and resource-allocation algorithms for multiuser cooperative orthogonal frequency-division multiple-access (OFDMA) systems. There are two major contributions of this paper. First, we propose a novel cooperation strategy for the OFDMA system. When there are two users in the system, the strategy achieves the capacity region upper bound for decode-and-forward (DF) cooperation. When there are multiple users in the system, the strategy can achieve near upper-bound performance in certain network topologies. Moreover, the strategy always outperforms those that are previously proposed for cooperative OFDMA systems. The second contribution is that we develop novel centralized resource-allocation algorithms for cooperative OFDMA systems. The advantages of the algorithms are that they not only simultaneously solve relay, power, and subcarrier allocation but also have complexity that increases only linearly with the number of subcarriers in the systems.

This paper introduces a cooperative orthogonal frequency division multiplexing (CO-OFDM) based on amplify and forward (AF) relay and utilizing a fast low complexity T-transform as a subcarriers modulation scheme. The proposed cooperative system is developed by changing the modulation/demodulation algorithms which significantly enhanced the immunity of the system to deep notches of the multipath channels. Thereafter, the paper presents a mathematical analytic model for the proposed amplify and forward CO-T-OFDM scheme. The use of T-transform in the transceiver of the proposed system enhances the signal diversity. Therefore, the presented AF cooperative system is efficient in enhancing the signal diversity, mitigating the effects of multipath fading channels and achieving more reliable bit-error-rate (BER) performance than the state-of-the-art cooperative system. It also moderates the peaks power of the signal. The BER of the developed AF cooperative system is evaluated by Monte Carlo simulation over frequency-selective multipath channels when AF relay is used, and compared with the BER performance of the standard AF cooperative system. The results show that the developed AF cooperative technology achieves better BER than the classic CO-OFDM under different transmission scenarios.

Secure communication with low computational resources is a critical issue in the Internet-of-Things (IoT) implementations. It is more challenging in the presence of hybrid adversary enabled with full-duplex (FD) capability to perform eavesdropping and jamming simultaneously. In this work we aim to address this issue through optimal subcarrier allocation towards combating the FD hybrid attacker. We begin with secrecy performance analysis in a multi-user IoT system considering statistical channel state information only of all attacker links. Novel analytical expression for the exact intercept probability is derived and a closed-form approximation is also provided. We further propose an optimisation framework for fair subcarrier allocation with a novel objective of minimising maximum intercept probability among multiple users. Considering the proposed optimisation framework as a non-convex combinatorial, we propose a low-complexity sub-optimal solution by leveraging the integer linear program (ILP) structure of the problem. To reduce the complexity further, the original problem is mapped to the assignment model and solved by exploiting its special structure with graph theory tools providing an optimal solution in polynomial time. Comprehensive investigations, conducted to verify the analysis and quantify the secrecy performance, demonstrate that proposed optimal solutions yield significant enhancement in secrecy performance over relevant schemes.

Cell Clustering has been identified as one of the technique and mechanism for cooperative communication used in Long Term Evolution (LTE). However, the proposed mechanism is subjected to many difficulties in cooperative decisions. This paper gives an overview on clustering techniques for User Equipment (UEs) and eNodeBs (eNBs) being handled in the LTE/LTE-Advanced network such as static and dynamic clustering. Strategic channel allocation schemes are required to equally allocate bandwidth and communication channels to the eNBs. This tends to maximize system spectral efficiency when assigning channels to cells in a cellular network without interference with neighbouring. A new proposed fair channel allocation using a combination of a static and dynamic clustering is being introduced to improve the previous channel assignment techniques. Moreover, fairness among UEs and eNBs during sub-carrier allocation under various propagation impairments has been investigated. By implementing dynamic clustering with fair channel allocation, the inter-cell interference is reduced, thus improving the throughput and network's performance.