主用户链路深度衰落下的认知网络中继

针对主用户链路经历深度衰落而发生通信中断的问题,提出了一种认知网络对主用户进行"透明"中继的方案。在不改变主用户通信协议的前提下,该方案首先感知主用户的状态,以判断其是否需要中继服务。当主用户通信发生中断时,认知网络利用从用户的能量检测器选出一个最优的节点解码转发主用户信号。从中断概率角度证明了这种最优单节点中继具有与多节点中继相同的空间分集作用,能够提高主用户平均传输效率,有较大的中继信道容量。通过仿真分析,验证了其分集效果和传输效率的提升。     

Cooperative Relay Selection Mechanism in Multi-Hop Networks

In this paper, we consider a three-hop relay system based on interference cancellation technique in Underlay cognitive radio (CR) network. Although underlay CR has been shown as a promising technique to better utilize the source of primary users (PUs), its secondary performance will be severely degraded. On one hand, by adapting the Underlay spectrum sharing pattern, secondary users (SUs) would observe the strict power constraints and be interfered by primary users. On the other hand, limited transmit power results in limited transmission range, which greatly degrade the secondary transmission capacity. To solve the problems above, we propose an interference cancellation protocol for multi-hop wireless communication networks in underlay CR, which could develop the long-distance transmission performance and improve the transmission efficiency significantly. As simulation results shows, proposed scheme significantly reduce the secondary outage probability and increase the secondary diversity than the traditional cases.     

Reconfigurable Sensing Time in Cooperative Cognitive Network Using Machine Learning

A cognitive radio network (CRN) intelligently utilizes the available spectral resources by sensing and learning from the radio environment to maximize spectrum utilization. In CRNs, the secondary users (SUs) opportunistically access the primary users (PUs) spectrum. Therefore, unambiguous detection of the PU channel occupancy is the most critical aspect of the operations of CRNs. Cooperative spectrum sensing (CSS) is rated as the best choice for making reliable sensing decisions. This paper employs machine-learning tools to sense the PU channels reliably in CSS. The sensing parameters are reconfigured to maximize the spectrum utilization while reducing sensing error and cost with improved channel throughput. The fine-k-nearest neighbor algorithm (FKNN), employed in this paper, estimates the number of samples based on the nature of the channel under-specific detection and false alarm probability demands. The simulation results reveal that the sensing cost is suppressed by reducing the sensing time and exploiting the traditional fusion rules, validating the effectiveness of the proposed scheme. Furthermore, the global decision made at the fusion center (FC) based on the modified sensing samples, results low energy consumption, higher throughput, and improved detection with low error probabilities.     

Darwinian approach for dynamic spectrum allocation in next generation systems

The authors present the use of a genetic algorithm (GA) model as a solution approach to the dynamic spectrum allocation (DSA) problem considered as a difficult combinatorial optimisation problem. The proposed multi-objective GA model enhances overall spectral efficiency of the network, while optimising its own spectrum utilisation to generate accessible spectrum opportunities for other radio technologies. A novel two-dimensional encoding technique is defined to represent solutions in the problem domain and the technique enables significantly shorter convergence times. A simulation tool has been developed to model the GA-based DSA and to compare the new scheme with the conventional fixed spectrum allocation (FSA) scheme under both uniform and non-uniform traffic distributions. The proposed scheme significantly outperformed the FSA scheme both in terms of spectral efficiency gain and spectral utilisation.     

Interference-limited resource allocation for cognitive radio in orthogonal frequency-division multiplexing networks

Efficient and fair resource allocation strategies are being extensively studied in current research in order to address the requirements of future wireless applications. A novel resource allocation scheme is developed for orthogonal frequency-division multiplexing (OFDM) networks designed to maximise performance while limiting the received interference at each user. This received interference is in essence used as a fairness metric; moreover, by defining different interference tolerances for different sets of users, the proposed allocation scheme can be exploited in various cognitive radio scenarios. As applied to the scheme, the authors investigate a scenario where two cellular OFDM-based networks operate as primary and secondary systems in the same band, and the secondary system benefits by accessing the unused resources of the primary system if additional capacity is required. The primary system benefits either by charging the secondary system for the use of its resources or by some form of reciprocal arrangement allowing it to use the secondary system's licenced bands in a similar manner, when needed. Numerical results show our interference-limited scheduling approach to achieve excellent levels of efficiency and fairness by allocating resources more intelligently than proportional fair scheduling. A further important contribution is the application of sequential quadratic programming to solve the non-convex optimisation problems which arise in such scenarios.     

Adaptive code-division multiple-access system for communications over indoor wireless optical channels based on random optical codes

The authors have designed an adaptive optical codes-based system for communications over the indoor wireless optical channel when large numbers of users access to the channel simultaneously. This system uses a code-division multiple access (CDMA) scheme based on the named random optical codes (ROC). The authors present the characteristics of this kind of optical codes and several results about its performance over noisy indoor wireless optical channels. Finally, the authors describe a CDMA system which adapts its performance to the number of users which are accessing simultaneously to the channel. The proposed system is able to maintain a target bit error rate adapting its data throughput independently of the number of simultaneous users in the optical environment, whenever certain conditions are accomplished.     

A Robust Resource Allocation Scheme for Device-to-Device Communications Based on Q-Learning

One of the most effective technology for the 5G mobile communications is Device-to-device (D2D) communication which is also called terminal pass-through technology. It can directly communicate between devices under the control of a base station and does not require a base station to forward it. The advantages of applying D2D communication technology to cellular networks are: It can increase the communication system capacity, improve the system spectrum efficiency, increase the data transmission rate, and reduce the base station load. Aiming at the problem of co-channel interference between the D2D and cellular users, this paper proposes an efficient algorithm for resource allocation based on the idea of Q-learning, which creates multi-agent learners from multiple D2D users, and the system throughput is determined from the corresponding state-learning of the Q value list and the maximum Q action is obtained through dynamic power for control for D2D users. The mutual interference between the D2D users and base stations and exact channel state information is not required during the Q-learning process and symmetric data transmission mechanism is adopted. The proposed algorithm maximizes the system throughput by controlling the power of D2D users while guaranteeing the quality-of-service of the cellular users. Simulation results show that the proposed algorithm effectively improves system performance as compared with existing algorithms.     

Linear precoding for the downlink of multiple input single output coexisting wireless systems

Coexisting radio systems, often called cognitive radio (CR), have attracted much attention because of the lack of spectrum resources and the low usage statistics of existing spectrum allocations. Interference suppression and cancellation are seen as key technologies for enabling coexisting systems, and the application of multiple antennas might be one solution to tackle interference. Linear vector precoding for downlink of multiple input single output CR systems is addressed. The maximum ratio transmission, zero forcing, optimal interference-free, and optimal interference-constrained (IC) precoding algorithms in the sense of minimum mean squared error (MMSE) are presented. Then the authors compare and analyse these algorithms under different channel assumptions. The simulation results show that the proposed IC precoding algorithm can maximise the utilisation of multiple antennas and greatly improve the system performance.     

Energy-Efficient Low-Complexity Algorithm in 5G Massive MIMO Systems

Energy efficiency (EE) is a critical design when taking into account circuit power consumption (CPC) in fifth-generation cellular networks. These problems arise because of the increasing number of antennas in massive multiple-input multiple-output (MIMO) systems, attributable to inter-cell interference for channel state information. Apart from that, a higher number of radio frequency (RF) chains at the base station and active users consume more power due to the processing activities in digital-to-analogue converters and power amplifiers. Therefore, antenna selection, user selection, optimal transmission power, and pilot reuse power are important aspects in improving energy efficiency in massive MIMO systems. This work aims to investigate joint antenna selection, optimal transmit power and joint user selection based on deriving the closed-form of the maximal EE, with complete knowledge of large-scale fading with maximum ratio transmission. It also accounts for channel estimation and eliminating pilot contamination as antennas M → ∞. This formulates the optimization problem of joint optimal antenna selection, transmits power allocation and joint user selection to mitigate inter-cell-interference in downlink multi-cell massive MIMO systems under minimized reuse of pilot sequences based on a novel iterative low-complexity algorithm (LCA) for Newton’s methods and Lagrange multipliers. To analyze the precise power consumption, a novel power consumption scheme is proposed for each individual antenna, based on the transmit power amplifier and CPC. Simulation results demonstrate that the maximal EE was achieved using the iterative LCA based on reasonable maximum transmit power, in the case the noise power is less than the received power pilot. The maximum EE was achieved with the desired maximum transmit power threshold by minimizing pilot reuse, in the case the transmit power allocation ρ_d = 40 dBm, and the optimal EE = 71.232 Mb/j.     

Asymptotically optimum detection of primary user in cognitive radio networks

Traditionally, the frequency spectrum is licensed to users by government agencies in a fixed manner where the licensee has exclusive right to access the allocated band. However, with increasing demand for the spectrum and scarcity of vacant bands, a spectrum policy reform seems inevitable. Meanwhile, recent measurements suggest the possibility of sharing spectrum among different parties subject to interference-protection constraints. In order to enable access to an unused licensed spectrum, a secondary user has to monitor licensed bands and opportunistically transmit whenever no primary signal is detected. Spectrum-sharing between a primary licensee and a group of secondary users has been studied. The structure of an asymptotically optimum detector based on the measurements of all secondary users is derived and the effect of the quantisation error in such a system is evaluated. Also, it is shown that by using the proposed detector in a sequential detection structure, it is possible to shorten the decision time needed by the detector. The results show the superiority of the proposed detector to other schemes.     

Optimal Cooperative Spectrum Sensing Based on Butterfly Optimization Algorithm

Since the introduction of the Internet of Things (IoT), several researchers have been exploring its productivity to utilize and organize the spectrum assets. Cognitive radio (CR) technology is characterized as the best aspirant for wireless communications to augment IoT competencies. In the CR networks, secondary users (SUs) opportunistically get access to the primary users (PUs) spectrum through spectrum sensing. The multipath issues in the wireless channel can fluster the sensing ability of the individual SUs. Therefore, several cooperative SUs are engaged in cooperative spectrum sensing (CSS) to ensure reliable sensing results. In CSS, security is still a major concern for the researchers to safeguard the fusion center (FC) against abnormal sensing reports initiated by the malicious users (MUs). In this paper, butterfly optimization algorithm (BOA)-based soft decision method is proposed to find an optimized weighting coefficient vector correlated to the SUs sensing notifications. The coefficient vector is utilized in the soft decision rule at the FC before making any global decision. The effectiveness of the proposed scheme is compared for a variety of parameters with existing schemes through simulation results. The results confirmed the supremacy of the proposed BOA scheme in both the normal SUs’ environment and when lower and higher SNRs information is carried by the different categories of MUs.     

Joint Spectrum Partition and Performance Analysis of Full-Duplex D2D Communications in Multi-Tier Wireless Networks

Full-duplex (FD) has been recognized as a promising technology for future 5G networks to improve the spectrum efficiency. However, the biggest practical impediments of realizing full-duplex communications are the presence of self-interference, especially in complex cellular networks. With the current development of self-interference cancellation techniques, full-duplex has been considered to be more suitable for device-to-device (D2D) and small cell communications which have small transmission range and low transmit power. In this paper, we consider the full-duplex D2D communications in multi-tier wireless networks and present an analytical model which jointly considers mode selection, resource allocation, and power control. Specifically, we consider a distance based mode selection scheme. The performance analysis of different D2D communications modes are performed based on stochastic geometry, and tractable analytical solutions are obtained. Then we investigate the optimal resource partitions between dedicated D2D mode and cellular mode. Numerical results validate the theoretical anlaysis and indicate that with appropriate proportions of users operated in different transmission modes and optimal partitioning of spectrum, the performance gain of FD-D2D communication can be achieved.     

Optimisation of limited feedback design for heterogeneous users in multi-antenna downlinks

The authors study the problem of limited channel information feedback in multiple-input single-output (MISO) broadcast channels serving heterogeneous users. The heterogeneous users have different feedback channel capacities because of their physical constraints and limitations. Our objective is to design an optimised limited feedback strategy for multiple users by using a set of multi-resolution codebooks such that, under varying and quantised channel information feedback, the multiuser system can maximise its achievable sum rate. By exploiting the receive antenna combining technique, the authors further generalise the proposed scheme to the multiuser beamforming case with multi-antenna users. Finally, the authors verify the proposed scheme by numerical methods. Simulation results show that the sum rate performance for heterogeneous users can be effectively improved by using the proposed limited feedback scheme, which is optimised according to only statistic channel information of users.     

Iterative low-complexity multi-user detection for asynchronous multi-sequence signalling based bit-interleaved coded modulation code division multiple access systems

An uplink direct sequence spread spectrum communications systems employing a multi-sequence model over a quasi-static frequency-selective fading channel is considered. In analogy with bit-interleaved coded modulation (BICM) technique, a group of bits at the output of a bit-wise interleaver is mapped uniquely to a complex signalling vector belonging to an orthogonal plane sequence modulation signal space, which is constructed over a set of expanded signature sequences. This transmission system provides not only bandwidth efficiency offered by additional signal planes but also time diversity resulting from the BICM technique. It is observed that at high system traffic load error performance could degrade substantially due to user cross-correlations, multi-access asynchronism as well as channel frequency selectivity. The authors employ a 'turbo principle' receiver, consisting of a soft interference cancellation scheme, soft demappers and maximum a posteriori decoders, to avert this capacity loss by exploiting the serially concatenating structure at the transmitter. After simple mathematical manipulation, a soft space-time linear minimum mean-square error multi-user detector could even be explored on the basis of per signal plane per user. Both analytical performance-bound and computer simulation of the proposed framework in terms of bit-error rate (BER) are revealed. Further, performance comparisons with convolutionally coded and conventional bandwidth-efficient coded direct sequence code division multiple access systems under the same system conditions are illustrated. The authors have also investigated the impact of labelling maps on the BER performance.     

Advanced spectrum management in wideband code division multiple access systems enabling cognitive radio usage

The authors propose a new advanced spectrum management (ASM) methodology for wideband code division multiple access systems based on the concept of coupling matrix, which is able to capture inter-cell interactions. The proposed methodology takes into account the fact that each cell can be associated to more than one carrier and aims at liberating some carriers in large geographical zones, so that they could eventually be used by, for example, secondary cognitive radio users that exploit the flexible frequency allocation and opportunistic spectrum access. Simulation results show that the proposed methodology increases spectrum efficiency while guaranteeing the requested QoS levels. Moreover, a new metric has been introduced to reflect the capability of the ASM methodology to liberate some carriers in large geographic zones. This metric has been used to compare the different approaches presented here.     

An Adaptive Power Allocation Scheme for Performance Improvement of Cooperative SWIPT NOMA Wireless Networks

Future wireless networks demand high spectral efficiency, energy efficiency and reliability. Cooperative non-orthogonal multiple access (NOMA) with simultaneous wireless information and power transfer (SWIPT) is considered as one of the novel techniques to meet this demand. In this work, an adaptive power allocation scheme called SWIPT based adaptive power allocation (SWIPT-APA-NOMA) is proposed for a power domain NOMA network. The proposed scheme considers the receiver sensitivity of the end users while calculating the power allocation coefficients in order to prevent wastage of power allocated to user in outage and by offering priority to any one of the users to use maximum harvested power. A detailed analysis on the bit error rate (BER) performance of the proposed scheme is done and closed form expression is obtained. Simulations have been carried out with various parameters that influence the receiver sensitivity and the results show that the network achieves better outage and BER performance using the proposed scheme. It is found that the proposed scheme leads to a ten-fold decrease in transmit power for the same error performance of a fixed power allocation scheme. Further, it offers 96.06% improvement in the capacity for a cumulative noise figure and fading margin of 10 dB.     

Optimisation of cooperative spectrum sensing in cognitive radio network

Spectrum sensing is a key problem in cognitive radio (CR). Because of a low SNR, fading and sensing time constraints, a single CR may not be able to reliably sense the presence of primary radios, which motivates the study of sensing by multiple cognitive users. Here, the authors consider cooperative spectrum sensing (CSS) using a counting rule where several cognitive users sense whether primary users exist or not and send their decisions to the centre where the final decision is made. Optimal strategies under both the Neyman-Pearson criterion and the Bayesian criterion for CSS are derived using a counting rule. In addition, the authors present simple methods to calculate the optimal settings. Another contribution here is the analysis of a randomised rule at the centre, which is a long-existing problem in the field of distributed detection systems.     

Multi-user adaptive orthogonal frequency-division multiplexing system for indoor wireless optical communications

An adaptive orthogonal frequency-division multiplexing (OFDM) system is proposed for multi-user communications over indoor wireless optical channels. The designed system uses multi-user least-squares detection techniques applied to space-division multiple access and OFDM schemes, in conjunction with angle-diversity reception. The system, which does not present an excessive increase in complexity with respect to the previous schemes, can support high bit rates for multiple users, beyond 100 Mbits/s. It also mitigates the channel fluctuations induced when either the space distribution or the number of emitters and receivers varies. The performance of the new proposed scheme is compared with that of a non-adaptive multi-user system and an adaptive single-user system, both described in the previous works, when they face similar environmental situations. The obtained results show a significant enhancement with respect to both the previous multi-user system and the adaptive single-user one, since the new scheme allows adaptively managing the system throughput on a multi-user environment     

acSB: Anti-Collision Selective-Based Broadcast Protocol in CR-AdHocs

As a fundamental operation in ad hoc networks, broadcast could achieve efficient message propagations. Particularl y in the cognitive radio ad hoc network where unlicensed users have different sets of available channels, broadcasts are carried out on multiple channels. Accordingly, channel selection and collision avoidance are challenging issues to balance the efficiency against the reliability of broadcasting. In this paper, an anti-collision selective broadcast protocol, called acSB, is proposed. A channel selection algorithm based on limited neighbor information is considered to maximize success rates of transmissions once the sender and receiver have the same channel. Moreover, an anti-collision scheme is adopted to avoid simultaneous rebroadcasts. Consequently, the proposed broadcast acSB outperforms other approaches in terms of smaller transmission delay, higher message reach rate and fewer broadcast collisions evaluated by simulations under different scenarios.     

Transmitter pre-filtering for the downlink of a time-division-duplex/direct sequencecode division multiple access system over time-varying multipath fading channels

In this paper, we investigate an optimised transmitter pre-filtering technique for downlink time-division-duplex (TDD) code division multiple access (CDMA) communications, which employs the conventional matched filter (MF) detector at the mobile receivers. The proposed pre-filtering technique eliminates the multiple-access interference and intersymbol interference (MAI/ISI) effects by applying a very simple transmission scheme that combines a signal transformation with a cyclic prefix strategy under a power constraint condition. Two constrained pre-filtering transformations are suggested depending on the information required at the mobile unit. An open-loop transmitter pre-filtering is first formulated; however, this solution does not consider the properties of the noise at the mobile receiver. A second solution is then presented via a closed-loop transmitter pre-filtering that includes an optimum gain for a given transmit and noise power. Some associated issues such as system efficiency, computational complexity and channel estimation errors are also addressed. Simulation results show that the proposed transmitter pre-filtering scheme can be used to increase the system performance and capacity. In addition, its performance is compared with another similar transmit pre-processing scheme in order to evaluate the performance improvement by the proposed algorithm.