Uplink Cellular Networks Research Articles

Resource allocation for device-to-device communications underlaying uplink cellular networks

Underlying cellular networks, device-to-device (D2D) communications are a practical network technology that can increase power efficiency and spectrum usage for close-proximity wireless services and applications. However, D2D link interference, when sharing resources with cellular users (CUs), poses a major challenge in such distribution situations. In this research, we primarily utilize wireless channel data that exhibits slowly shifting large-scale fading to conduct spectrum sharing and power allocation. The overall ergodic capacity of all cellular user equipment (CUE) links is initially considered as the optimization target in order to maximize the overall throughput of CUE links while ensuring the reliability of each D2D link. Then, the expansion of the minimum ergodic capacity is measured to ensure a more consistent capacity performance across all CUE links. We utilized algorithms that are resilient to channel fluctuations and produce optimal resource allocation. We use MATLAB, and the computer simulation validates its intended performance.

Joint Particle Swarm Optimization of Power and Phase Shift for IRS-Aided D2D Underlaying Cellular Systems.

Device-to-device (D2D) communication is a promising wireless communication technology which can effectively reduce the traffic load of the base station and improve the spectral efficiency. The application of intelligent reflective surfaces (IRS) in D2D communication systems can further improve the throughput, but the problem of interference suppression becomes more complex and challenging due to the introduction of new links. Therefore, how to perform effective and low-complexity optimal radio resource allocation is still a problem to be solved in IRS-assisted D2D communication systems. To this end, a low-complexity power and phase shift joint optimization algorithm based on particle swarm optimization is proposed in this paper. First, a multivariable joint optimization problem for the uplink cellular network with IRS-assisted D2D communication is established, where multiple DUEs are allowed to share a CUE's sub-channel. However, the proposed problem considering the joint optimization of power and phase shift, with the objective of maximizing the system sum rate and the constraints of the minimum user signal-to-interference-plus-noise ratio (SINR), is a non-convex non-linear model and is hard to solve. Different from the existing work, instead of decomposing this optimization problem into two sub-problems and optimizing the two variables separately, we jointly optimize them based on Particle Swarm Optimization (PSO). Then, a fitness function with a penalty term is established, and a penalty value priority update scheme is designed for discrete phase shift optimization variables and continuous power optimization variables. Finally, the performance analysis and simulation results show that the proposed algorithm is close to the iterative algorithm in terms of sum rate, but lower in power consumption. In particular, when the number of D2D users is four, the power consumption is reduced by 20%. In addition, compared with PSO and distributed PSO, the sum rate of the proposed algorithm increases by about 10.2% and 38.3%, respectively, when the number of D2D users is four.

On the Age of Information and Energy Efficiency in Cellular IoT Networks With Data Compression

The Age of Information (AoI), which evaluates the information freshness, and the energy efficiency (EE) play key roles in cellular IoT networks. This is due to that outdated data can hardly provide any useful information for delay-sensitive applications and the IoT devices usually have limited battery life. In particular, the AoI can be significantly affected by the transmission latency, which becomes the bottleneck for the AoI performance in ultradensely deployed cellular IoT networks. Moreover, it is desirable for cellular IoT networks to achieve low AoI with high EE. The data compression (DC) can decrease the AoI and improve the EE by reducing the transmission latency. Therefore, in this work, the AoI and EE performance in a large-scale densely deployed uplink cellular IoT network are jointly analyzed with the DC technology. Specifically, the closed-form results of AoI are derived and validated by Monte Carlo simulations. Based on these results, the AoI–EE ratio is defined to evaluate the tradeoff between the AoI and the EE. Equipped with these results, the effects of compression ratio (CR) and status update packet generation rate (SUPGR) on both the AoI and the AoI–EE ratio are analyzed numerically. The results show that by jointly optimizing the CR and SUPGR, the AoI can be decreased by up to 82% and the AoI–EE ratio can be reduced by up to 83% as compared with the case that only adjusts the SUPGR without the DC. It indicates that the DC should be widely adopted in IoT devices, which can improve the information freshness with low-energy consumption, especially in an ultradensely deployed scenario.

DNN-Based Dynamic Transmit Power Control for V2V Communication Underlaid Cellular Uplink

Vehicle-to-vehicle (V2V) communication has been designed to afford improvements in the traffic congestion and traffic accidents by directly exchanging information between nearby vehicles. However, V2V communication may have difficulty providing service reliability due to interference between V2V links and vehicle-to-cellular user equipment links. In this paper, we consider the transmit power control algorithm to minimize interference among cellular users and vehicles in the context of V2V communication underlaid uplink cellular networks. First, we formulate the problem, which is an NP-hard combinatorial optimization problem with linear constraints. Addressing this problem with traditional optimization methods is ineffective; therefore, we design and train a deep neural network to address this optimization problem. Computational complexity analyses and simulation results reveal that the proposed algorithm outperforms weighted minimum mean squared error (WMMSE), fixed transmit power, and Dinkelbach's methods, and achieves near-global optimum with lower computation complexity than the exhaustive search (ES).

Power controlled outage-aware optimal protocol for NOMA-assisted underlay D2D networks

Underlay device-to-device (D2D) and non-orthogonal multiple access (NOMA) are two promising technologies that have potential to enhance the spectral efficiency for future wireless communication systems. This paper studies an underlay D2D-NOMA system in an uplink cellular network. Different from the previous works, we minimize the outage probability (OP) while allocating optimal power to the D2D group receivers. Specifically, a D2D power allocation (DPA) problem is formulated and a globally-optimal solution is obtained. As a special case, closed-form expressions are also derived for asymptotic OP-based DPA. Results are numerically validated, and an overall average performance improvement of at least 24% is observed over existing conventional power control schemes.

Outage probability minimization based power control and channel allocation in underlay D2D‐NOMA for IoT networks

AbstractThe emergence of Internet‐of‐Things (IoT) aims to improve modern life by inter‐connecting many smart devices, technologies, and applications. It, however, drastically increases mobile traffic and requires large wireless spectrum. Therefore, for a better spectrum utilization to support this massive connectivity along with low latency and close proximity based communication, non‐orthogonal multiple access enabled underlay device‐to‐device (D2D‐NOMA) is envisioned as a key technology for IoT deployment. Hence, in this work, we consider multiple IoT clusters communicating via underlay D2D‐NOMA in an uplink cellular network, with the objective of minimizing the outage probability (OP) while allocating resources to the clusters. Specifically, for each cluster, we formulate the optimization problem of OP‐based power control with fixed channel allocation (PCCA) and solve it using particle swarm optimization (PSO). Additionally, we prove the convexity of PCCA problem and obtain closed‐form expressions at high SNR. Further, we propose a novel OP‐aware channel allocation (OPCA) algorithm to enhance the overall D2D network outage performance. The results are numerically validated and an average performance improvement of 31% and 51% is observed over the two conventional schemes namely fixed power allocation and orthogonal multiple access enabled D2D, respectively.

DRL-Based Sum-Rate Maximization in D2D Communication Underlaid Uplink Cellular Networks

Device-to-device (D2D) communication affords the benefits of improved network spectral efficiency, throughput, energy efficiency, and delay performance. However, D2D communication underlaid cellular uplinks are degraded by interference between D2D user equipment (DUE) and cellular user equipment (CUE) that use the same frequency band. In this context, researchers have proposed the optimization of the transmit power of the devices to mitigate interference. This power allocation problem is generally modeled as a NP-hard combinatorial optimization problem with linear constraints; therefore, traditional optimization methods are ineffective in addressing the problem. In this paper, we apply a deep reinforcement learning (DRL) algorithm to optimize the transmit power for both DUEs and CUEs in the context of D2D communication underlaid uplink cellular networks, which can solve the optimization problem via optimal decision-making together with efficient deep network training. Our simulation results show that the proposed algorithm affords a near-global-optimum solution with lower computation complexity than exhaustive search, and outperforms the fixed-power, weighted minimum mean square error (WMMSE), gradient descent method, and Newton-Raphson approaches.

Uplink Coverage in Heterogeneous mmWave Cellular Networks With Clustered Users

A K-tier heterogeneous mmWave uplink cellular network with clustered user equipments (UEs) is considered in this paper. In particular, UEs are assumed to be clustered around small-cell base stations (BSs) according to a Gaussian distribution, leading to the Thomas cluster process based modeling. Specific and practical line-of-sight (LOS) and non-line-of-sight (NLOS) models are adopted with different parameters for different tiers. The probability density functions (PDFs) and complementary cumulative distribution functions (CCDFs) of different distances from UEs to BSs are characterized. Coupled association strategy and largest long-term averaged biased received power criterion are considered, and general expressions for association probabilities are provided. Following the identification of the association probabilities, the Laplace transforms of the inter-cell interference and the intra-cluster interference are characterized. Using tools from stochastic geometry, general expressions of the SINR coverage probability are provided. As extensions, fractional power control is incorporated into the analysis, tractable closed-form expressions are provided for special cases, and average ergodic spectral efficiency is analyzed. Via numerical and simulation results, analytical characterizations are confirmed and the impact of key system and network parameters on the performance is identified.

Secure Communication for Uplink Cellular Networks Assisted with Full-Duplex Device-to-Device User

In this paper, the secure communication based on the full-duplex (FD) device-to-device (D2D) in cellular networks is proposed. For the proposed scheme, the novel model is established, in which a D2D user is played as a relay operating in FD mode to assist in the secure transmission of uplink information. Considering that the D2D user as a relay is untrusted, D2D link rate maximization is formulated with the constraint of secrecy rate, which ensures the security of uplink cellular networks. To cope with the optimization problem, the optimal power allocation factors of the cellular user (CU) and the D2D user are jointly optimized. Firstly, by using the monotonicity of the objective function, the optimal solution of the power allocation factor at the D2D user can be obtained. Subsequently, the closed-form expression of the optimal power allocation factor at the CU is derived and verified that the solution is the global minimum point. Simulation results verify that the proposed scheme has better output performance than the conventional scheme.

Performance analysis for uplink NOMA‐based cellular network with M2M/H2H co‐existence

Owing to the growing proliferation of machine type communication devices and other high-end devices in conventional human-to-human (H2H) communication, it is inevitable that these types of communications will co-exist with each other in the next generation of cellular communications. This study investigates an uplink cellular network with machine-to-machine (M2M) and H2H co-existence, where a machine type communication gateway is deployed as a relay in the cellular network to forward the M2M messages to the base station (BS). Non-orthogonal multiple access (NOMA) has been adopted to transmit the data of H2H and M2M communications to the BS simultaneously. Considering the different delay-sensitive transmissions of M2M/H2H communications, the expressions for outage probability and effective capacity (EC) are theoretically derived with the constraints of quality-of-service requirements. Simulation results show that the NOMA scheme outperforms the orthogonal multiple access in terms of outage probability and EC.

On the Optimality of Treating Inter-Cell Interference as Noise in Uplink Cellular Networks

In this paper, we explore the information-theoretic optimality of treating interference as noise (TIN) in cellular networks. We focus on uplink scenarios modeled by the Gaussian interfering multiple access channel (IMAC), comprising $K$ mutually interfering multiple access channels (MACs), each formed by an arbitrary number of transmitters communicating independent messages to one receiver. We define TIN for this setting as a scheme in which each MAC (or cell) performs a power-controlled version of its capacity-achieving strategy, with Gaussian codebooks and successive decoding, while treating interference from all other MACs (i.e., inter-cell interference) as noise. We characterize the generalized degrees-of-freedom (GDoF) region achieved through the proposed TIN scheme, and then identify conditions under which this achievable region is convex without the need for time-sharing. We then tighten these convexity conditions and identify a regime in which the proposed TIN scheme achieves the entire GDoF region of the IMAC and is within a constant gap of the entire capacity region.

Outage probability and ergodic capacity analysis of uplink NOMA cellular network with and without interference from D2D pair

We consider the framework of uplink transmission and interference constraint for new system model to provide multiple access scheme for fifth generation (5G) wireless communications. In particular, such considered system contains normal cellular users deploying a non-orthogonal multiple access (NOMA) scheme and underlay device-to-device (D2D) users deploying traditional orthogonal multiple access (OMA). Such potentials motivate us consider uplink in cellular network in which the base station (BS) is required to fulfill two NOMA users’ diverse quality of service (QoS) requests under location arrangement with nearby D2D user pair. With regard to enhanced successive interference cancellation (SIC) scheme, the BS still performs the signal detection of NOMA users based on the decoding order and even though existence of an extra interference from D2D user pair. In term of quality evaluation, the ergodic capacity and outage probability are two underlying metrics need be investigated systematically. As important results, detailed derivations are provided in a scenario that considering coexistence of D2D users and NOMA users. As extended scenario, multiple antenna NOMA users exhibit improved performance and the related comparisons are provided. Finally, simulations in various scenarios are conducted to corroborate the precision of the mathematically derivations and to confirm potential of deployment in NOMA with SIC operation.

On Coverage Probability With Type-II HARQ in Large-Scale Uplink Cellular Networks

This letter studies uplink transmission in large-scale cellular networks with a Type-II hybrid automatic repeat request (HARQ) retransmission scheme, under which an unsuccessful transmission (if occurs) is combined with the corresponding retransmission through maximal-ratio combining (MRC). Based on stochastic geometry analysis, the uplink coverage probabilities are characterized under a generalized power control scheme in the scenarios with quasi-static interference (QSI) and fast-varying interference (FVI), where the same and different interfering users, respectively, are present during the transmission and retransmission phase. Our analytical expressions reveal some scaling properties of the coverage probabilities and can be used to evaluate the diversity gain of MRC (i.e., the ratio of the required signal-to-interference ratio (SIR) for achieving a target coverage probability with MRC to that without MRC). We show that the diversity gain of MRC is more remarkable in the scenario with QSI compared to that with FVI. Moreover, the diversity gain of MRC can be mostly exploited by adopting full channel-inversion power control.

Achievable Degrees of Freedom of Relay-Aided MIMO Cellular Networks Using Opposite Directional Interference Alignment

In this paper, we propose an interference alignment (IA) scheme for the multiple-input multiple-output (MIMO) uplink cellular network with the help of a relay which operates in half-duplex mode. The proposed scheme only requires global channel state information (CSI) knowledge at the relay, with no transmitter beamforming and time extension at the user equipment (UE), which differs from conventional IA schemes for cellular networks. We derive the feasibility condition of the proposed scheme for the general cellular network configuration and analyze the degrees-of-freedom (DoF) performance of the proposed IA scheme while providing a closed-form beamformer design at the relay. Extensions of the proposed scheme to downlink and full-duplex cellular networks are also proposed in this paper. The DoF performance of the proposed scheme is compared to those of linear IA scheme and relay-aided interference management scheme for a cellular network with no time extension. It is also shown that advantages similar to those in the uplink case can be obtained for the downlink case through the duality of a relay-aided interfering multiple-access channel (IMAC) and an interfering broadcast channel (IBC). Furthermore, the proposed scheme for a full-duplex cellular network is shown to have advantages identical to those of a number of proposed half-duplex cellular cases.

Performance Analysis and Resource Allocation for Cooperative D2D Communication in Cellular Networks With Multiple D2D Pairs

In this letter, we investigate cooperative device-to-device (D2D) communication in an uplink cellular network, where D2D users act as relays for cellular users. We derive the outage probability of a cellular user and the average achievable rate from a D2D transmitter to a D2D receiver in analytic form. We obtain optimal spectrum and power allocation to maximize the total average achievable rate under the outage probability constraint. The validity of the analysis is verified by computer simulations.

On the Effect of Uplink Power Control on Temporal Retransmission Diversity

Using stochastic geometry, this letter studies the retransmission performance in uplink cellular networks with fractional path-loss inversion power control (FPC). We first show that the signal-to-interference-ratio (SIR) is correlated across time, which imposes temporal diversity loss in the retransmission performance. In particular, FPC with lower path-loss compensation factor decreases inter-cell interference but suffers from degraded retransmission diversity. On the other hand, full path-loss inversion achieves almost full temporal diversity (i.e., temporal SIR independence) at the expense of increased inter-cell interference. To this end, the results show that ramping-down the power upon transmission failure improves the overall coverage probability in interference-limited uplink networks.

Optimal Resource Management and Binary Power Control in Network-Assisted D2D Communications for Higher Frequency Reuse Factor.

Device-to-device (D2D) communications can be adopted as a promising solution to attain high quality of service (QoS) for a network. However, D2D communications generates harmful interference when available resources are shared with traditional cellular users (CUs). In this paper, network architecture for the uplink resource management issue for D2D communications underlaying uplink cellular networks is proposed. We develop a fractional frequency reuse (FFR) technique to mitigate interference induced by D2D pairs (DPs) to CUs and mutual interference among DPs in a cell. Then, we formulate a sum throughput optimization problem to achieve the QoS requirements of the system. However, the computational complexity of the optimization problem is very high due to the exhaustive search for a global optimal solution. In order to reduce the complexity, we propose a greedy heuristic search algorithm for D2D communications so as to find a sub-optimal solution. Moreover, a binary power control scheme is proposed to enhance the system throughput by reducing overall interference. The performance of our proposed scheme is analyzed through extensive numerical analysis using Monte Carlo simulation. The results demonstrate that our proposed scheme provides significant improvement in system throughput with the lowest computational complexity.

A Channel Estimator via Non-Orthogonal Pilot Signals for Uplink Cellular IoT

Simultaneous acquisition of channel state information (CSI) of many devices with high accuracy is crucial to provide the Internet-of-Things (IoT) connectivity in cellular networks. A traditional channel estimator in cellular networks adopts the orthogonal pilot structure, which cannot provide high scalability for many IoT devices without a significant increase of pilot overhead. To overcome such a limitation, we propose a novel channel estimator based on non-orthogonal pilot signals for frequency-division duplex (FDD) based uplink cellular IoT networks. The proposed scheme provides an interference-canceled environment during the channel estimation procedure by reconstructing the non-orthogonal pilot signals and removing their effects. Consequently, the proposed scheme can increase the number of available pilot signals without any increase of pilot overhead, which makes the BS spectral-efficiently accommodate more IoT devices with full exploitation of antenna technique. The numerical results verify the effectiveness of the proposed scheme on supporting more IoT devices at the expense of a slight loss of the channel estimation accuracy, compared to the conventional discrete Fourier transform (DFT)-based channel estimator, from the viewpoint of a mean squared error, a bit error rate, and a network throughput.

Energy Efficient V2X-Enabled Communications in Cellular Networks

Vehicle-to-everything (V2X) communications, which provide wireless connectivity among vehicles, roadside drivers, passengers, and pedestrians, are attracting great interest. In this paper, we propose an energy-efficient relay assisted transmission scheme based on V2X communications in the uplink cellular networks for delay insensitive applications. We aim to maximize energy efficiency of the uplink while considering both the circuit power and transmit power consumption, as well as the delay constraint. The optimal resource allocation for direct transmission mode and V2X-enabled transmission mode are derived. For the V2X-enabled transmission mode, we first consider the transmission without the delay constraint and obtain the corresponding optimal power allocation. Based on the obtained result, we further propose the optimal resource allocation policy that satisfies the delay constraint and minimizes the energy consumption. Simulation results show that there exists an energy-delay tradeoff and the proposed V2X-enabled scheme can achieve significant energy saving with an acceptable delay compared with the traditional direct scheme, the decoding-and-forward based transmission scheme, and the opportunistic store-carry and forward based transmission scheme, especially when the cell radius is not small.

Throughput Optimization Using Metaheuristic-Tabu Search in the Multicast D2D Communications Underlaying LTE-A Uplink Cellular Networks

The sum throughput of a cellular network can be improved when nearby devices employ direct communications using a resource sharing technique. Multicast device-to-device (M-D2D) communication is a promising solution to accommodate higher transmission rates. In an M-D2D communication, a multicast group is formed by considering a transmitter that can transmit the same information to multiple receivers by considering the transmission link conditions. In this paper, we focus on the uplink interference generated due to the non-orthogonal sharing of resources between the cellular users and M-D2D groups. To mitigate the interference, we propose a spectrum reuse-based resource allocation and power control scheme for M-D2D communication underlaying an uplink cellular network. We formulate the throughput optimization problem by considering the fractional frequency reuse (FFR) method within a multicell cellular network. In addition, a metaheuristic-tabu search algorithm is developed that maximizes the probability of finding optimal solutions by minimizing uplink interference. To analyze fairness resource distribution among users, we finally consider Jain’s fairness index. Simulation results show that the proposed scheme can improve the coverage probability, success rate, spectral efficiency, and sum throughput of the network, compared with a random resource allocation scheme without a metaheuristic-tabu search algorithm.