On the use of frequency-domain cross-layer diversity techniques to cope with lost packets

The Quality of Service (QoS) requirements for modern broadband wireless systems can be very high, with small error rates and delays. To preclude significant degradation on the spectral efficiency, these systems also require high throughputs. Lost packets, either due to errors or collisions, are usually discarded and need to be retransmitted, leading to performance degradation. An efficient alternative to simple retransmissions is to combine the signals associated to different transmission attempts.This paper analyses two time diversity approaches to cope with lost packets that are relatively similar at physical layer but treat different packet loss causes: a low-complexity diversity combining ARQ scheme (Automatic Repeat reQuest) employed in a TDMA (Time Division Multiple Access) architecture; and a Network Diversity Multiple Access (NDMA), which is a multi-packet reception approach able to separate multiple mobile terminals transmitting simultaneously in one slot using temporal diversity. This paper combines the use of these techniques in Single Carrier Frequency Domain Equalization (SC-FDE) systems, which are widely recognized as the best candidates for the uplink of future broadband wireless systems. It aims to present a comparison among the approaches focusing on error rate, throughput and delay performances, not discarding the implementation complexity issues.     

Energy efficiency maximization for IRS-assisted NOMA networks

In this paper, we consider a non-orthogonal multiple access (NOMA) system assisted by intelligent reflecting surface (IRS). As an emerging technology that has received widespread attention, IRS can reconfigure the wireless channel environment by adjusting the relationship between the incident angle and the exit angle, thereby improving system performance. Our goal is to use the flexible assistance of IRS to achieve the maximum energy efficiency of the NOMA system. Our design objects are the beam vector design of the base station and the phase matrix design of the IRS. The original problem is highly non-convex. We consider using the block coordinate descent method to design the phase matrix and beam vector separately. Simulation results show that our proposed scheme has better performance than traditional OMA and systems without IRS assistance.     

Optimization Algorithms for Joint Power and Sub-Channel Allocation for NOMA-Based Maritime Communications

This paper investigates resource optimization schemes in a marine communication scenario based on non-orthogonal multiple access (NOMA). According to the offshore environment of the South China Sea, we first establish a Longley–Rice-based channel model. Then, the weighted achievable rate (WAR) is considered as the optimization objective to weigh the information rate and user fairness effectively. Our work introduces an improved joint power and user allocation scheme (RBPUA) based on a single resource block. Taking RBPUA as a basic module, we propose three joint multi-subchannel power and marine user allocation algorithms. The gradient descent algorithm (GRAD) is used as the reference standard for WAR optimization. The multi-choice knapsack algorithm combined with dynamic programming (MCKP-DP) obtains a WAR optimization result almost equal to that of GRAD. These two NOMA-based solutions are able to improve WAR performance by 7.47% compared with OMA. Due to the high computational complexity of the MCKP-DP, we further propose a DP-based fully polynomial-time approximation algorithm (DP-FPTA). The simulation results show that DP-FPTA can reduce the complexity by 84.3% while achieving an approximate optimized performance of 99.55%. This advantage of realizing the trade-off between performance optimization and complexity meets the requirements of practical low-latency systems.     

Contract Theory-Based Incentive Mechanism for Full Duplex Cooperative NOMA with SWIPT Communication Networks

Cooperative Non-Orthogonal Multiple Access (NOMA) with Simultaneous Wireless Information and Power Transfer (SWIPT) communication can not only effectively improve the spectrum efficiency and energy efficiency of wireless networks but also extend their coverage. An important design issue is to incentivize a full duplex (FD) relaying center user to participate in the cooperative process and achieve a win–win situation for both the base station (BS) and the center user. Some private information of the center users are hidden from the BS in the network. A contract theory-based incentive mechanism under this asymmetric information scenario is applied to incentivize the center user to join the cooperative communication to maximize the BS’s benefit utility and to guarantee the center user’s expected payoff. In this work, we propose a matching theory-based Gale–Shapley algorithm to obtain the optimal strategy with low computation complexity in the multi-user pairing scenario. Simulation results indicate that the network performance of the proposed FD cooperative NOMA and SWIPT communication is much better than the conventional NOMA communication, and the benefit utility of the BS with the stable match strategy is nearly close to the multi-user pairing scenario with complete channel state information (CSI), while the center users get the satisfied expected payoffs.     

DRL-Assisted Resource Allocation for NOMA-MEC Offloading with Hybrid SIC

Multi-access edge computing (MEC) and non-orthogonal multiple access (NOMA) are regarded as promising technologies to improve the computation capability and offloading efficiency of mobile devices in the sixth-generation (6G) mobile system. This paper mainly focused on the hybrid NOMA-MEC system, where multiple users were first grouped into pairs, and users in each pair offloaded their tasks simultaneously by NOMA, then a dedicated time duration was scheduled to the more delay-tolerant user for uploading the remaining data by orthogonal multiple access (OMA). For the conventional NOMA uplink transmission, successive interference cancellation (SIC) was applied to decode the superposed signals successively according to the channel state information (CSI) or the quality of service (QoS) requirement. In this work, we integrated the hybrid SIC scheme, which dynamically adapts the SIC decoding order among all NOMA groups. To solve the user grouping problem, a deep reinforcement learning (DRL)-based algorithm was proposed to obtain a close-to-optimal user grouping policy. Moreover, we optimally minimized the offloading energy consumption by obtaining the closed-form solution to the resource allocation problem. Simulation results showed that the proposed algorithm converged fast, and the NOMA-MEC scheme outperformed the existing orthogonal multiple access (OMA) scheme.     

Performance analysis of PDMA-based hybrid satellite–terrestrial networks with decode-and-forward relaying

As one of the most promising non-orthogonal multiple access (NOMA) technologies in 5G communication, pattern division multiple access (PDMA) has theoretically higher spectrum utilization and a larger communication capacity than conventional orthogonal multiple access (OMA) technologies. In this letter, PDMA is applied to hybrid satellite–terrestrial networks with decode-and-forward (DF) relaying in the downlink, and an in-depth study on the performance of outage probability (OP), ergodic capacity and system throughput is performed. For a more comprehensive analysis, hybrid satellite–terrestrial relay networks (HSTRNs) with conventional OMA technology are used in the comparative analysis. Analysis and simulation results show that PDMA-based hybrid satellite–terrestrial relay networks outperform the other system in terms of OP and ergodic capacity.     

Deployment and trajectory design of fixed-wing UAVs in NOMA assisted wireless networks

This paper proposes a deployment and trajectory scheme for fixed-wing unmanned aerial vehicles (UAVs) deployed as flying base stations in multi-UAV enabled non-orthogonal multiple access (NOMA) downlink communication. Specifically, the deployment of UAVs and power allocation of users are jointly optimized to maximize the sum-rate. Thereafter, the energy efficiency maximization problem is formulated to optimize the trajectory of UAVs by jointly considering the quality of service (QoS) requirement of users, various flight constraints, limited on-board energy, and users’ mobility. Initially, the existing users are divided into clusters by k-means clustering, where each cluster is served by a single UAV. Then, the clusters are further divided into multiple sub-clusters, each having a pair of near and far users. Orthogonal multiple access (OMA) is applied among sub-clusters and NOMA is applied to intra sub-cluster users. Lastly, the Balanced-grey wolf optimization (B-GWO) algorithm is proposed for solving the non-convex optimization problems. Simulation results prove the superiority of the B-GWO based deployment and trajectory algorithms compared to the benchmarks. In addition, the proposed B-GWO based trajectory algorithm achieves a near-optimal performance with an optimality gap of less than 1.5% compared to the exhaustive search.     

On the Age of Information in a Two-User Multiple Access Setup

This work considers a two-user multiple access channel in which both users have Age of Information (AoI)-oriented traffic with different characteristics. More specifically, the first user has external traffic and cannot control the generation of status updates, and the second user monitors a sensor and transmits status updates to the receiver according to a generate-at-will policy. The receiver is equipped with multiple antennas and the transmitters have single antennas; the channels are subject to Rayleigh fading and path loss. We analyze the average AoI of the first user for a discrete-time first-come-first-served (FCFS) queue, last-come-first-served (LCFS) queue, and queue with packet replacement. We derive the AoI distribution and the average AoI of the second user for a threshold policy. Then, we formulate an optimization problem to minimize the average AoI of the first user for the FCFS and LCFS with preemption queue discipline to maintain the average AoI of the second user below a given level. The constraints of the optimization problem are shown to be convex. It is also shown that the objective function of the problem for the first-come-first-served queue policy is non-convex, and a suboptimal technique is introduced to effectively solve the problem using the algorithms developed for solving a convex optimization problem. Numerical results illustrate the performance of the considered optimization algorithm versus the different parameters of the system. Finally, we discuss how the analytical results of this work can be extended to capture larger setups with more than two users.     

A matching-theoretic approach to resource allocation in D2D-enabled downlink NOMA cellular networks

This paper investigates the resource allocation problem in non-orthogonal multiple-access (NOMA) cellular networks underlaid with OMA-based device-to-device (D2D) communication. This network architecture enjoys the intrinsic features of NOMA and D2D communications; namely, spectral efficiency, massive connectivity, and low-latency. Despite these indispensable features, the combination of NOMA and D2D communications exacerbates the resource allocation problem in cellular networks due to the tight coupling among their constraints and conflict over access to shared resources. The aim of our work is to maximize the downlink network sum-rate, while meeting the minimum rate requirements of the cellular tier and underlay D2D communication, and incorporating interference management as well as other practical constraints. To this end, many-to-many matching and difference-of-convex programming are employed to develop a holistic sub-channels and power allocation algorithmic solution. In addition to analyzing the properties of the proposed solution, its performance is benchmarked against an existing solution and the traditional OMA-based algorithm. The proposed solution demonstrates superiority in terms of network sum-rate, users’ connectivity, minimum rate satisfaction, fairness, and interference management, while maintaining acceptable computational complexity.     

System throughput maximization in IRS-assisted phase cooperative NOMA networks

This work investigates performance of system throughput in intelligent reflecting surfaces (IRSs)-enabled phase cooperative non-orthogonal multiple access (NOMA) framework. By exploiting heterogeneous cognitive radio networks concept the aim is to maximize the sum rate of secondary users in the proposed phase cooperative downlink network configuration via optimization solutions. However, the optimization problem comes out to be NP-hard and precludes direct solution. Hence, an alternating optimization is applied at the primary network to solve the maximization problem by exploiting the transmit beamforming (BF) at the power station (PS) and phase shift optimization at the IRS. Later, sum rate maximization for secondary network is performed by utilizing phase shifts of primary network via phase cooperation. In order to find global optimal solutions for active beamformers at both PSs, a branch-reduce-and-bound (BRnB) method is used whereas, passive phase shift optimization at the primary PS is performed via a simple iterative solution, i.e., the element-wise block coordinate descent method. For the proposed framework, Monte-Carlo simulations are performed where the optimality of the global solution is compared with heuristic BF methods including minimum-mean-square-error/regularized zero-forcing-beamforming (ZFBF) and ZFBF. The BRnB algorithm sets an upper performance bound by improving the sum rate of users in comparison with the conventional heuristic BF schemes. This work signifies the utilization of phase cooperation in IRS-assisted NOMA networks for a multi-user environment.     

Relationship between Age and Value of Information for a Noisy Ornstein–Uhlenbeck Process

The age of information (AoI) has been widely used to quantify the information freshness in real-time status update systems. As the AoI is independent of the inherent property of the source data and the context, we introduce a mutual information-based value of information (VoI) framework for hidden Markov models. In this paper, we investigate the VoI and its relationship to the AoI for a noisy Ornstein–Uhlenbeck (OU) process. We explore the effects of correlation and noise on their relationship, and find logarithmic, exponential and linear dependencies between the two in three different regimes. This gives the formal justification for the selection of non-linear AoI functions previously reported in other works. Moreover, we study the statistical properties of the VoI in the example of a queue model, deriving its distribution functions and moments. The lower and upper bounds of the average VoI are also analysed, which can be used for the design and optimisation of freshness-aware networks. Numerical results are presented and further show that, compared with the traditional linear age and some basic non-linear age functions, the proposed VoI framework is more general and suitable for various contexts.     

Matching theory based user-grouping for indoor non-orthogonal multiple access visible light communication heterogeneous networks

This Letter proposes a model of indoor visible light communication(VLC) heterogeneous networks entirely based on LEDs with different specifications and applies non-orthogonal multiple access(NOMA) to it because of the narrow modulation bandwidth of LEDs. Moreover, a user-grouping scheme that is based on matching theory is proposed to improve the network achievable sum rate. Simulation results indicate that when each NOMA cluster contains 6 users, the proposed scheme has a 49.54% sum-rate enhancement compared with the traditional user-grouping scheme. As the number of users in each NOMA cluster increases, the proposed scheme performs better at the cost of computational complexity.     

Design and performance evaluation of successive interference cancellation based Slotted Aloha MAC protocol

As a result of densification, the performance of the wireless networks has become highly interference-limited and energy inefficient. To overcome this problem, interference mitigation techniques such as Successive Interference Cancellation (SIC) can be used to decode multiple packets simultaneously at the receiver. In this context, we analyze a SIC-based Slotted Aloha (SIC-SA) Medium Access Control (MAC) protocol for wireless networks. We derive expressions for packets decoding probability and optimal transmission probability of the nodes of the SIC-SA MAC protocol. Our derivation is based on the order statistics of Independent and Identical/non-Identical exponentially distributed received-signal-powers from the nodes under the Rayleigh channel condition. Throughput, delay, and energy efficiency of the SIC-SA MAC protocol have been derived and validated against simulation. The effect of path loss exponent, SINR threshold, and the number of nodes on the performance of SIC-SA have been studied. The performance of SIC-SA in a network of nodes distributed randomly according to the Poisson Point Process has been analyzed. Extension of our analysis to Power Domain Non-Orthogonal Multiple Access (NOMA) has been demonstrated. We also analyzed the impact of imperfect estimation of channel state information and imperfect SIC at the receiver. Results show an improvement in performance metrics of SIC-SA over the traditional Slotted Aloha.     

Channel Quality-Based Optimal Status Update for Information Freshness in Internet of Things

This paper investigates the status updating policy for information freshness in Internet of things (IoT) systems, where the channel quality is fed back to the sensor at the beginning of each time slot. Based on the channel quality, we aim to strike a balance between the information freshness and the update cost by minimizing the weighted sum of the age of information (AoI) and the energy consumption. The optimal status updating problem is formulated as a Markov decision process (MDP), and the structure of the optimal updating policy is investigated. We prove that, given the channel quality, the optimal policy is of a threshold type with respect to the AoI. In particular, the sensor remains idle when the AoI is smaller than the threshold, while the sensor transmits the update packet when the AoI is greater than the threshold. Moreover, the threshold is proven to be a non-increasing function of channel state. A numerical-based algorithm for efficiently computing the optimal thresholds is proposed for a special case where the channel is quantized into two states. Simulation results show that our proposed policy performs better than two baseline policies.     

On the performance of a virtual user pairing scheme to efficiently utilize the spectrum of unpaired users in NOMA

This paper evaluates the performance of a virtual user pairing scheme that efficiently utilizes the spectrum of unpaired users in non-orthogonal multiple access (NOMA), termed as VP-NOMA. The scheme aims at utilizing the frequency bands of those users which remain unpaired due to the non-uniform distribution of users in a cellular area. We consider a case where the cell edge users are more than the cell center users, so that complete one-to-one correspondence does not exist between all cell center and cell edge users to be accommodated/paired using conventional NOMA (C-NOMA) user pairing. Thus, some cell edge users remain unpaired, and are served using conventional multiple access (OMA) schemes. In such scenario, VP-NOMA pairs a single cell center user with two or more clustered (closely located) cell edge users over non-overlapping frequency bands, thus enabling the cell center user to efficiently use the frequency bands of these previously unpaired cell edge users. Performance of VP-NOMA in terms of ergodic sum capacity (ESC), outage probability (OP), and outage sum capacity (OSC), is analyzed through comprehensive mathematical derivations and simulations for a generalized system model. Moreover, the mathematical analysis is validated through close concordance between analytical and simulation results of ESC, OP, and OSC.     

Joint user grouping and power allocation in VLC-NOMA system

With the energy consumption of wireless networks increasing, visible light communication (VLC) has been regarded as a promising technology to realize energy conservation. Due to the massive terminals access and increased traffic demand, the implementation of non-orthogonal multiple access (NOMA) technology in VLC networks has become an inevitable trend. In this paper, we aim to maximize the energy efficiency in VLC-NOMA networks. Assuming perfect knowledge of the channel state information of user equipment, the energy efficiency maximization problem is formulated as a mixed integer nonlinear programming problem. To solve this problem, the joint user grouping and power allocation (JUGPA) is proposed including user grouping and power allocation. In user grouping phase, we utilize the average of channel gain among all user equipment and propose a dynamic user grouping algorithm with low complexity. The proposed scheme exploits the channel gain differences among users and divides them into multiple groups. In power allocation phase, we proposed a power allocation algorithm for maximizing the energy efficiency for a given NOMA group. Thanks to the objective function is fraction form and non-convex, we firstly transform it to difference form and convex function. Then, we derive the closed-form optimal power allocation expression that maximizes the energy efficiency by Dinkelbach method and Lagrange dual decomposition method. Simulation results show that the JUGPA can effectively improve energy efficiency of the VLC-NOMA networks.     

Energy efficient collaborative computation for double-RIS assisted mobile edge networks

Computation offloading in mobile edge computing (MEC) systems emerges as a novel paradigm of supporting various resource-intensive applications. However, the potential capabilities of MEC cannot be fully unleashed when the communication links are blocked by obstacles. This paper investigates a double-reconfigurable-intelligent-surfaces (RISs) assisted MEC system. To efficiently utilize the limited frequency resource, the users can partially offload their computational tasks to the MEC server deployed at base station (BS) by adopting non-orthogonal multiple access (NOMA) protocol. We aim to minimize the energy consumption of users with limited resource by jointly optimizing the transmit power of users, the offloading fraction of users and the phase-shifts of RISs. Since the problem is non-convex with highly coupled variables, the block coordinate descent (BCD) method is leveraged to alternatively optimize the decomposed four subproblems. Specifically, we invoke successive convex approximation for low complexity (SCALE) and Dinkelbach technique to tackle the fractional programming of power optimization. Then the offloading fraction is obtained by closed-form solution. Further, we leverage semidefinite relaxation (SDR) and bisection method to address the phase-shifts design of double RISs. Finally, numerical results illustrate that the proposed double-RIS assisted NOMA scheme is capable of efficiently reducing the energy consumption and achieves significant performance gain over the benchmark schemes.     

Joint terminal-AP association and power allocation for NOMA-enabled space–air–ground integrated networks

This paper considers a space–air–ground integrated network (SAGIN) to provide network access services for aerial and terrestrial terminals. The non-orthogonal multiple access (NOMA) is used for improving spectral efficiency in the uplink transmission between terminals and access points (APs) in SAGIN. A sum rate maximization optimization problem is formulated by optimizing terminal-AP association and power allocation, while simultaneously satisfying the constraints of transmit power, network coverage characteristics, and quality-of-service (QoS) requirements of both aerial and terrestrial terminals. To deal with the formulated mixed integer nonlinear programming (MINLP) optimization problem, we first decouple it into separated terminal-AP association and power allocation problems. Then, we adopt the Q-learning algorithm to solve the terminal-AP association subproblem. Based on the obtained terminal-AP association solution, an iterative power allocation algorithm is developed by exploiting the Lagrange dual method. Moreover, the computational complexity of the proposed algorithm is further analyzed. Simulation results demonstrate that, compared with other schemes, our proposed algorithm can achieves a better performance in terms of the achievable sum rate, average achievable rate, and outage probability.     

Multiuser detection for the uplink of clustered 5G systems with universal frequency reuse

With 5G (Fifth generation) cellular communications, systems have to be able to cope with a massive increase of mobile devices and services and simultaneously improve the system’s spectral efficiency, as well as dealing with high interference levels. Base Station (BS) cooperation architectures jointly with block transmission techniques, such as OFDM (Orthogonal Frequency Division Multiplexing) for the downlink and SC-FDE (Single-Carrier with Frequency-Domain Equalization) for the uplink, are proven to be suitable for broadband wireless transmission systems. In BS cooperation systems MTs (Mobile Terminals) in adjacent cells share the same physical channel allowing the reducing of the frequency reuse and improving the spectral efficiency of cellular systems. In this paper we present a set of multiuser detection techniques for the uplink transmission in clustered architectures based on the C-RAN (Centralized-Radio Access Network) concept. We consider BS cooperation systems employing a universal frequency reuse approach. Our performance results demonstrate that by employing clustered techniques for the detection procedure it is possible to reduce substantially the signal processing complexity and the side information that must be transmitted by the backhaul structure.