Multiple Access Wireless Systems Research Articles

Signal Identification in Non-Orthogonal Multiple Access Wireless Systems Using Bi-Directional Long Short-Term Memory Network

This study's goal is to provide an early analysis of deep learning (DL) for signal identification in wireless systems that use non-orthogonal multiple access (NOMA). The successive interference cancellation (SIC) approach is frequently used at the receiver in NOMA systems when several users are decoded successively. Without explicitly calculating channels, a DL-based NOMA receiver can decode messages for several users at once. To estimate the multiuser uplink channel (CE) and recognize the initial broadcast signal in this study, it is recommended that a deep neural network with bi-directional long short-term memory (Bi-LSTM) be utilized. The suggested Bi-LSTM model, in contrast to conventional CE techniques, may immediately retrieve transmission signals impacted by channel distortion. During the offline training phase, the Bi-LTSM model is trained using simulation data based on channel statistics. The trained model is then applied to retrieve the transmitted symbols in the stage of online deployment. According to the findings, the DL method could outperform a maximum probability detector that considers interference effects when inter-symbol interference is substantial.

On Performance of Downlink Non-Orthogonal Multiple Access Wireless System Relying on UAV

Wireless communications relying on Unmanned Aerial Vehicles (UAVs) is a promising candidate in future communication systems. Compared with conventional terrestrial communications, UAV networks has some significant benefits including cost-effectiveness, mobility, fast deployment, higher probability of Line-of-Sight (LoS) links between UAV and ground terminals. Based on ideal conditions of high Signal-to-Noise Ratio (SNR), Non-Orthogonal Multiple Access (NOMA) with fixed power allocation factor is adopted to indicate performance of two users. These ground user from UAV is independent of channel and trajectory parameters is further evaluated under impact of imperfect channel state information (CSI). We drive the closed-form formula of outage probability for two ground users. Simulation results provide impacts of system parameters on outage behavior.

Theoretical analysis of a graphene quantum well hybrid plasmonic waveguide to design an inter/intra-chip nano-antenna

In this paper, a smart multi-user wireless link based on a graphene quantum well vertical hybrid plasmonic waveguide-fed nano-antenna is proposed. The theoretical method and finite element method (FEM) are used to verify that the vertical hybrid plasmonic waveguide (VHPW) supports both even and odd fundamental modes. Utilizing multi-mode graphene quantum well VHPW leads to the design of a selective mode nano-antenna with intermediate broadside and end-fire radiation patterns with high directivities of 9.38 dBi and 11.8 dBi at 193.5 THz, respectively, obtained by the finite-difference time-domain method. Also, to verify the accuracy of nano-antenna results, the FEM approach is used. The nano-antenna performance as a wireless inter/intra-chip link is investigated, which confirms the even mode plays a key role to create a multiple-access wireless system. Based on the amazing features of graphene as an epsilon-near-zero and absorptive/transparent material, the accessibility of receivers is easily controlled. The effect of a single row array structure and its application as beam steering is studied. Finally, to estimate the performance of quantum well nano-antenna as a real device, which is compatible with electron-beam lithography and lift-off fabrication techniques, the effect of metal layer roughness and 5% tolerance for geometrical parameters are investigated.

Transmit Antenna Selection Strategies for SC- FDMA- IDMA Massive MIMO Systems

The 5 G wireless offers many advancements over the prevalent 4 G LTE communication networks, such as enhanced data transmission rates (in order of Gbps), Substantially reduced latency, many times increase in the Base Station Capacity and praiseworthy betterments in the QoS offered to the users. IDMA has already proven its potential in 5 G and it can be easily integrated in to massive MIMO systems. The ideology behind the concept of Massive MIMO is to match the requirement for efficient usage of spectrum, and is implemented using several numbers of antennas at the Base Station, catering to a number of subscribers concurrently using same band of the given frequency. However, the cost and complexity of implementation of such large-scale antenna systems is quite high. Thus for reduction in the number of radio frequency chains, the technique of Transmit Antenna Selection is used. In this paper, we propose two transmit antenna selection strategies considered for individual user or overall users based on selection criteria maximum sum rate or minimum bit error performance considering for (MIMO) multiuser multiple input and multiple output single carrier frequency division multiple access based interleave division multiple access wireless system (MIMO-SCFDMA-IDMA). We have taken this scheme for the uplink communication and selection of the subcarrier is through the bulk selection. The performance may get degraded in case of heavy load of multiple subcarriers attached to one antenna, which will in turn call for the role of power amplifier and thus efficiency of the system may go down. Therefore, here we prefer bulk subcarrier selection instead of per subcarrier selection. It is shown in this paper that enhanced sum rate can be achieved as more users are allowed to transmit concurrently, and thus multiuser gain is achieved. We also demonstrated the comparison with simulation result of sum rate performance and Bit error rate performance of varying users. Result shows that antenna selection based on overall system is better than the antenna selection considering each user.

A user-centric economic-driven paradigm for rate allocation in non-orthogonal multiple access wireless systems

In this paper, a novel approach towards optimizing users’ rate allocation and price customization in a non-orthogonal multiple access (NOMA) wireless network under quality of service (QoS)-differentiated requested services is proposed and studied. A multi-service wireless system is considered, where each user’s QoS requirements are reflected through a utility function, alongside his willingness to pay for the corresponding service. Within this setting, in order to jointly allocate the customized price and rate, a two-variable optimization problem arises. Based on the principles of S-modular theory, the above two-variable (rate and price) optimization problem is modeled and solved as a distributed non-cooperative game. The existence and convergence to the Nash equilibrium point with reference to both user’s uplink transmission rate and price is proven. The proposed approach, allowing for decision-making at the user side, is well aligned with the self-optimization and self-adaptation objectives of future emerging 5G wireless networks. The performance evaluation of the devised framework is conducted via modeling and simulation under various scenarios, and the numerical results clearly demonstrate its superiority against other existing approaches.

Reduced feedback link design for device‐relaying enhanced multiple‐input single‐output orthogonal frequency‐division multiple access wireless systems

Device-relaying enhanced multiple-input single-output (MISO) orthogonal frequency-division multiple access (OFDMA) systems are one of the promising and cost-effective methods to satisfy data rate requirements of future wireless networks. To implement device relaying in MISO-OFDMA systems efficiently, the channel state information belonging to all links is required at the base station. However, the feedback load increases with the number of users, device-relay candidates, antennas and subcarriers. A novel scheduling and a joint feedback link design and relay selection algorithm in device-relaying enhanced downlink MISO-OFDMA systems are proposed, while reducing the feedback load significantly without sacrificing the system performance.

Performance Analysis of a WCDMA System Model in a Low Mobility and Indoor Environment with Channel Coding over Additive White Gaussian Noise Channel

This paper has analyzed the performance a Wireless Division Multiple Access (WCDMA) system model at a data rate of 384kbps and 2Mbps over an Additive White Gaussian Noise (AWGN) channel. The signal was modulated by Quadrature Phase Shift Keying (QPSK) and Quadrature Amplitude Modulation (QAM) with modulation order, M=16. The performance of the system was enhanced by implementing convolution coding scheme. This study was important as it formed a basis through which the performance analysis can be extended to Long Term Evolution (LTE) networks which have data rates starting from 1Mbps to as high as 100Mbps.The performance of the WCDMA at these data rates was seen to improve when convolutional coding scheme was implemented. Since the Shannon capacity formula depends on the BER of a system then this improvement means an additional capacity in the channel and this can accommodate more users in the channel. The results have further shown that the choice of a modulation technique depending on the throughput required affects the BER performance of the system. Therefore, there must be a trade-off between the throughput required, the modulation format to be used and the pulse shaping filter parameters.

Optimal pre‐equalisation for wireless multi‐carrier code division multiple access systems under quality of service requirements

This work addresses an optimal pre-equalisation scheme to provide power and phase compensation in multi-carrier code division multiple access wireless systems under quality of service (QoS) restrictions. Two assignation schemes are studied: independent and uniform pre-equalised transmission (IPT and UPT) per subcarrier. First, the QoS was quantified in terms of the signal-to-interference noise ratio (SINR) after using a linear detector in the receiver. The SINR expressions for IPT and UPT were explicitly derived, to highlight their dependence on the pre-equalisation factors. These relations are exploited to derive analytical procedures to obtain the required pre-equalisation factors that satisfy an objective SINR per active user. The author's proposal for IPT achieves the lowest power while requiring a simple detector independent of the channel state information (CSI). For IPT, two minimum norm solutions are derived by translating the SINR restrictions into linear equations: one based on spectral factorisation, and a second one based on a simultaneous zero-forcing effect plus an energy scaling. On the other hand, for UPT, multi-user detectors like zero-forcing (ZF) and minimum-mean-square error (MMSE) have to be employed at the receiver to achieve a solution to the QoS requirements. In the numerical evaluations, IPT attained roughly a 2.5–3% reduction in the overall transmission power compared to UPT with ZF and MMSE by varying the objective SINR and noise variance. Although this reduction is further expanded as the number of active users increases, achieving a reduction in transmission power larger than 50% for a fully-loaded system.

Dual-Domain Adaptive Beamformer Under Linearly and Quadratically Constrained Minimum Variance

In this paper, a novel adaptive beamforming algorithm is proposed under a linearly and quadratically constrained minimum variance (LQCMV) beamforming framework, based on a dual-domain projection approach that can efficiently implement a quadratic-inequality constraint with a possibly rank-deficient positive semi-definite matrix, and the properties of the proposed algorithm are analyzed. As an application, relaxed zero-forcing (RZF) beamforming is presented which adopts a specific quadratic constraint that bounds the power of residual interference in the beamformer output with the aid of interference-channel side-information available typically in wireless multiple-access systems. The dual-domain projection in this case plays a role in guiding the adaptive algorithm towards a better direction to minimize the interference and noise, leading to considerably faster convergence. The robustness issue against channel mismatch and ill-posedness is also addressed. Numerical examples show that the efficient use of interference side-information brings considerable gains.

Convergence of Price-Based Resource Allocation Algorithms in Multicellular Multicarrier Systems

Inter-cell interference mitigation is a key challenge in the heterogeneous wireless networks which are expected to use an aggressive frequency reuse factor and a high-density access point deployment to improve coverage and spectral efficiency. In this paper, the problem of resources allocation in multicell Orthogonal Frequency Division Multiple Access wireless system is considered with universal frequency reuse and target of Weighted Sum-Rate Maximization. We address multi cell modified iterative water filling as an iterative power allocation algorithm. Also, a new extension of fixed point implementation of Successive Convex Approximation for Low complExity (SCALE) algorithm to multicellular system [referred to as Multi Cell Fixed point SCALE (MCF-SCALE)] is presented and it has been shown both of them resulted to the same convergence point. It is also demonstrated that using Lagrangian multiplier instead of noise variance in Standard Yates framework (as has been used in some previous papers) is not a suitable method for proving convergence and all the previous results based on this pattern need to be revised. Finally, a new framework is presented for proving the convergence of MCF-SCALE algorithm based on Jacobi iterative algorithm. Moreover, some previous convergence criteria are shown to be interpreted as a special case of this condition.

Optimized Encoding of Scheduling Assignments Using Finite Blocklength Coding Bounds

We provide an analytical framework for optimizing the number of resources required for the signaling of scheduling information in wireless multiple access systems. In doing so, we use recent bounds on the achievable rate in the finite blocklength regime. We formulate optimization problems for finding the minimum required number of channel uses such that the overall error probability in the decoding of the control information is below a given threshold. Three specific control signaling schemes are compared.

Cooperative Access in Wireless Networks: Stable Throughput and Delay

We investigate the impact of a protocol-level cooperation idea in a wireless multiple-access system. By dynamically and opportunistically exploiting spatial diversity among the <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$N$</tex></formula> source users, a packet is delivered to the common destination through either a direct link or through cooperative relaying by intermediate source nodes that have a statistically better channel to the destination. The traffic burstiness at the source is taken into account, and the performance metrics of the stable throughput region and delay are evaluated for the case of packet-erasure channels. We consider conflict-free, work-conserving transmission policies as well as plain time-division multiple-access policy. We establish that the stable throughput regions under both classes of cooperative policies are the same, which strictly contain the stable throughput regions achieved without cooperation. Moreover, the optimal policy for minimizing the average delay among the class of all cooperative work-conserving policies is determined. Then, in the case of two users, the closed-form delay expressions are explicitly derived as well. Our results indicate that cooperation can significantly reduce delay for both users.

Error Reduction in Multiple-Access Systems by Message Wrapping

In wireless multiple-access systems, CSMA/CA cannot eliminate packet collision completely, especially in the presence of hidden terminals. To address the problem, ZigZag decoding was proposed to resolve collisions. In this paper, we characterise the probability of decoding failure (due to rank deficiency) for a given transmission overhead. We then propose a new technique called message wrapping to further reduce the probability of decoding error. Our analytical and numerical results both show that errors can be significantly reduced by message wrapping.

Reducing Physical Layer Control Signaling Using Mobile-Assisted Scheduling

We present a scheme for reducing the part of the downlink signaling traffic in wireless multiple access systems that contains scheduling information. The theoretical basis of the scheme is that the scheduling decisions made by the base station are correlated with the CSI reports from the mobiles. This correlation can be exploited by the source coding scheme that is used to compress the scheduling maps before they are sent to the mobiles. In the proposed scheme, this idea is implemented by letting the mobiles make tentative scheduling decisions themselves, and then letting the base station transmit "agreement maps" instead of raw scheduling maps to the mobiles. The agreement maps have lower entropy and they require less resources to be transmitted than the original scheduling maps do. The improvement can be substantial. We also model the task of finding the optimal scheduling assignments according to the proposed scheme as a combinatorial optimization problem and present an efficient algorithm to find the optimal solution.

New designs of frequency hopping sequences with low hit zone

Frequency hopping sequences have been found wide applications in various modern frequency hopping spread spectrum communications and radar systems. With potential applications to these areas such as ultra wide bandwidth time hopping code division multiple access radio systems, multi-user and sonar systems, the design of quasi-synchronous time/frequency hopping code division multiple access systems by employing low hit zone hopping sequences has attracted wide attentions. In this paper, we present three construction methods for the low Hamming correlation zone frequency hopping sequences. The parameters of these sets of frequency hopping sequences with low hit zone are new and flexible. The constructed sequences are almost optimal and optimal respectively with respect to the Peng---Fan---Lee bounds. The simplicity of this technique makes it attractive for practical use.

A Relay Assisted Cooperative Transmission Protocol for Wireless Multiple Access Systems

In this paper, we propose a spectrally efficient cooperative transmission protocol for multiple access scenarios. The key feature is to utilize multi-user diversity and fully exploit the dynamic nature of radio propagation. In particular, by carefully scheduling the multiple sources and relays' transmissions, a source with a poor connection to the destination can have higher priority to obtain help from a relay with better channel condition. As a result, the full diversity gain is achievable even though only a fraction of relays is scheduled to help each user. We developed an achievable diversity-multiplexing tradeoff for the proposed transmission protocol to assist performance evaluation. When the number of relays is large, the diversity-multiplexing tradeoff achieved by the proposed scheme can approximate the optimal multiple-input single-output upper bound. Both analytical and numerical results show that the proposed protocol outperform other comparable schemes in most conditions.

Joint Throughput Maximization and Fair Uplink Transmission Scheduling in CDMA Systems

We study the fundamental problem of optimal transmission scheduling in a code-division multiple-access wireless system in order to maximize the uplink system throughput, while satisfying the users quality-of-service (QoS) requirements and maintaining fairness among them. The corresponding problem is expressed as a weighted throughput maximization problem, under certain power and QoS constraints, where the weights are the control parameters reflecting the fairness constraints. With the introduction of the power index capacity, it is shown that this optimization problem can be converted into a binary knapsack problem, where all the corresponding constraints are replaced by the power index capacities at some certain system power index. A two-step approach is followed to obtain the optimal solution. First, a simple method is proposed to find the optimal set of users to receive service for a given fixed target system load, and then the optimal solution is obtained as a global search within a certain range. Furthermore, a stochastic approximation method is presented to effectively identify the required control parameters. The performance evaluation reveals the advantages of our proposed policy over other existing ones and confirms that it achieves very high throughput while maintains fairness among the users, under different channel conditions and requirements.

A new partial transmit sequence scheme using genetic algorithm for peak-to-average power ratio reduction in a multi-carrier code division multiple access wireless system

One major drawback of multi-carrier broadband wireless transmission system is that its signal may cause high peak-to-average power ratio (PAPR). This article proposes a new partial transmit sequence (PTS) scheme using genetic algorithm for PAPR reduction in a synchronous multi-carrier code division multiple access wireless system. We investigate the impact of each genetic algorithm operator and optimally configure genetic algorithm to be suitable for the practical system design. The simulation results demonstrate that our proposed genetic algorithm-based PTS scheme achieves low PAPR values with much lower computational complexity than other existing solutions. Meanwhile, the optimal parameters of genetic algorithm assisted PTS are provided.

Fast Blind Adaptive Beamforming Algorithm With Interference Suppression

A fast blind adaptive beamforming algorithm is proposed in code-division multiple-access wireless systems based on an array pattern synthesis approach. By incorporating an interference suppression mechanism in the iterative procedure, the proposed algorithm outperforms conventional blind algorithms. Two practical adaptive beamforming algorithms are further presented, which provide fast convergence speed with low complexity. The simulation results demonstrate the effectiveness of the proposed adaptive beamforming algorithms in various signal environments.

Adaptive Multiuser Channel Estimation using Reduced Kalman/LMS Algorithm

This paper presents an adaptive multiuser channel estimator using the reduced-Kalman least-mean-square (RK-LMS) algorithm. The frequency-selective fading channel is modeled as a tapped-delay-line filter with smoothly time-varying Rayleigh distributed tap coefficients. The multiuser channel estimator based on minimum-mean-square-error (MMSE) criterion is used to predict the filter coefficients. We also present its convergence characteristics and tracking performance using the RK-LMS algorithm. Unlike the previously available Kalman filtering algorithm based approach (Chen, Chen IEEE Trans Signal Process 49(7): 1523---1532, 2001) the incorporation of RK-LMS algorithm reduces the computational complexity of multiuser channel estimator used in the code division multiple access wireless systems. The computer simulation results are presented to demonstrate the substantial improvement in its tracking performance under the smoothly time-varying environment.