Worst User Research Articles

Learning to Beamform in Joint Multicast and Unicast Transmission With Imperfect CSI

With the rapid development of mobile Internet, the demand for multicast is growing rapidly, such as content pushing and video streaming. The multicast service is usually offered to users without interrupting their on-going unicast transmission, and thus the multicast and unicast beamformers needs to be jointly designed, which generally requires perfect channel state information (CSI). However, perfect CSI is usually unavailable due to the channel estimation error. In this paper, we propose a learning based approach to jointly design the multicast and unicast beamformers with imperfect CSI. To learn the beamforming strategy, a new graph neural network (GNN) based architecture named unicast-multicast GNN (UMGNN) is proposed, which only requires the estimated channel. UMGNN can guarantee the permutation invariance/equivalence and model the special property in the multicast transmission, i.e., the multicast rate is determined by the worst user. Moreover, by sharing the parameters across different users, UMGNN exhibits a pretty good scalability to different number of users. Numerical results show that UMGNN outperforms a fully connected neural network and a widely used sampling-based algorithm. To highlight its performance in the multicast transmission, we also show that UMGNN can find the correct worst user that determines the multicast rate.

Enhanced 5G Mobile Broadcasting Service With Shape-Adaptive RIS

There emerges a strong trend recently to create an intelligent and controllable wireless transmission environment by installing reconfigurable intelligent surfaces (RIS) on the surface of diverse. We research the use of RIS in 5G multicast TV applications in this paper. In particular, the shape-adaptive RIS is developed to relay 5G multicast TV signals and achieve extra RIS gain. To optimize the shape bending in RIS model, we employ the algorithm of Deep Deterministic Policy Gradient (DDPG), a reinforcement learning technique that combines both Q-learning and Policy gradients. Our simulation results show that RIS can considerably enhance the SINR of worst users and improve the system’s overall Modulation and Coding Scheme (MCS) level for 5G mobile broadcasting services.

Multiobjective Optimization for Joint Task Offloading, Power Assignment, and Resource Allocation in Mobile Edge Computing

Mobile edge computing (MEC) is an emerging computational paradigm for providing storage and computing capabilities in network edge, to improve the experience of users, to shorten the delay, and to reduce the energy consumption of mobile devices. In this article, we consider a multiuser and multiserver scenario, where each user has an application composed of multiple independent tasks that need to be executed, and each MEC server is equipped on a base station (BS) for assisting mobile users to execute computation-intensive and time-sensitive tasks. Multiobjective optimization for joint task offloading, power assignment, and resource allocation is studied to maximize the offloading gains of users. A multivariable and multiobjective optimization problem with three objectives is constructed. An efficient multiobjective evolutionary algorithm is developed to solve the problems of minimizing the response time, minimizing the energy consumption, and minimizing the cost. Simulation results verify the effectiveness of our algorithm, and show the method significantly improves the user’s offloading benefits. According to the author’s knowledge, this is the first paper on the exploration of multiobjective optimization of multiuser with multiple tasks and multiserver MEC system, in which the worst user offloading revenue is regarded as the optimization objectives.

BDS signal-in-space anomaly probability analysis over the last 6 years

Knowledge of the signal-in-space (SIS) anomaly probability is important for the integrity monitoring of satellite navigation. An efficient SIS anomaly detection method is indispensable for characterizing the probability of SIS anomalies with sufficient confidence. The traditional GPS anomaly detection method based on the zero-mean Gaussian distribution assumption of the instantaneous signal-in-space user range error (IURE) is not suitable for the emerging BeiDou navigation satellite system (BDS) because of the nonzero-mean, asymmetric distribution of the BDS IURE. By deliberately extracting the time series trend terms of the satellite orbit and clock errors, an SIS anomaly detection method with the worst user location protection principle is proposed based on 6 years of BDS data from March 2013 to March 2019. The detection results have shown that the probability of single-satellite SIS anomalies is at the 10−3 level and the probability of multiple-satellite SIS concurrent anomalies is at the 10−4 level. Meanwhile, the operational service performance provided by the BDS gradually improves over time.

Physical Layer Security Aided Wireless Interference Networks in the Presence of Strong Eavesdropper Channels

Under both long (infinite) and short (finite) blocklength transmissions, this paper considers physical layer security for a wireless interference network of multiple transmitter-user pairs, which is overheard by multiple eavesdroppers (EVs). The EVs are assumed to have better channel conditions than the legitimate users (UEs), making the conventional transmission unsecured. The paper develops a novel time-fraction based transmission, under which the information is transmitted to the UEs within a fraction of the time slot and artificial noise (AN) is transmitted within the remaining fraction to counter the strong EVs’ channels. Based on channel distribution information of UEs and EVs, the joint design of transmit beamforming, time fractions and AN power allocation to maximize the worst users’ secrecy rate is formulated in terms of nonconvex problems. Path-following algorithms of low complexity and rapid convergence are proposed for their solution. Simulations are provided to demonstrate the viability of the proposed methodology.

A Physical Layer Multicast Precoding and Grouping Scheme for Bandwidth Minimization

Physical layer multicasting exploits multiple antennas at the transmitter side to deliver a common message to a group of $K$ users. To this end, two formulations have been well addressed in the literature: i) the max-min-fair criterion, which maximizes the signal-to-noise ratio (SNR) of the worst user for a fixed transmit power; and ii) the quality of service (QoS) formulation, which minimizes the transmit power subject to a target SNR. Nevertheless, it is known that the performance and complexity of these approaches is severely degraded as the group size grows. In this paper, we propose a different formulation that aims at minimizing the required bandwidth needed to provide the multicast service. This is achieved by dividing the users into smaller groups and assigning the bandwidth required to provide a target rate to each group. Contrary to the common belief, it is shown that dividing the users into different groups that use orthogonal bandwidth allocations can lead to a smaller aggregated bandwidth than the single-group with single bandwidth allocation counterpart, if an intelligent grouping scheme is used. An iterative algorithm to derive the optimal number of groups is presented with an stopping criterion to reduce the numerical complexity. It is shown through simulation that our proposed approach greatly reduces the required bandwidth compared to existing schemes that rely on single bandwidth allocation. Interestingly, results reveal that our proposed scheme also leads to a greater SNR for a randomly chosen user, and it reduces the variance of the required bandwidth, which eases the implementation in real networks.

Proactive Eavesdropping via Jamming in NOMA Network

Recently, non-orthogonal multiple access (NOMA) has been considered as a promising technique in 5G network, and many investigations have addressed on the physical layer security to improve the security performance. In this paper, an alternative problem, where the eavesdropping process is considered as a legal activity, will be analyzed to track suspicious communications. More specifically, we study a wireless surveillance system in which the legitimate monitor is equipped with multi-antenna to overhear the messages between the suspicious receiver and the suspicious transmitter. Suspicious users are grouped into pairs and use the NOMA technique to transmit signals to a suspicious base station. Meanwhile, the legitimate monitor (LM) simultaneously transmits jamming signals, listens to suspicious links, decode-and-forward (DF) the eavesdropped information to the legitimate eavesdropper (LE). Based on the proposed mechanism, we investigate the power allocation policies for jamming signals of the legitimate monitor under deterministic and non-deterministic interference channel. Accordingly, we derive the closed-form expression of the successful eavesdropping probability for the best and the worst user to evaluate the system performance. Monte Carlo simulations are provided to verify our analytical results.

Access Point Placement for Hybrid UAV-Terrestrial Small-Cell Networks

We address the problem of access point (AP) placement in small-cell networks with partial infrastructure flexibility, i.e., a novel class of problem in Beyond 5G, resultant from the utilization of unmanned aerial vehicles (UAVs) with AP functionalities (UAV-APs), to aid fixed wireless networks in coping with momentary peak-capacity requirements. We use the signal-to-generated-interference-plus-noise ratio (SGINR) metric as an alternative to the traditional signal-to-interference-plus-noise ratio (SINR) to quantify the effects of inter-cell interference (ICI) on the per-user capacity. From average SGINR, we derive the ICI-aware distortion measure leading to the Inter-AP Lloyd algorithm to obtain throughput-optimal AP placement for a fully flexible infrastructure. We then impose a hybridity constraint to the AP placement problem which turns a fraction of the network into a fixed infrastructure composed of terrestrial APs (T-APs) while the remainder is constituted by UAV-APs with flexibility in position. This newly formulated AP placement problem is solved by the proposed Lloyd-type algorithm called Hybrid AP Placement Algorithm (HAPPA). Furthermore, we present an initialization method for the Lloyd and Lloyd-type algorithms for Gaussian mixture models (GMMs) that offers an AP allocation leading to a higher rate compared to the k-means++ initialization. Finally, computer simulations show that the Inter-AP Lloyd algorithm can improve the performance of the worst users by up to 42.75% in achievable rate, assuming a fully flexible network. By using HAPPA on hybrid networks, we achieve improvements of up to 71.92% in sum rate over the fixed network and close the performance gap with fully flexible networks down to 2.02%, when an equal number of UAV-APs and T-APs is used. Further, our proposed initialization scheme always results in a balanced AP allocation, which means a more even distribution of users per AP, whereas the k-means++ scheme results in unbalanced allocations at least 30% of the time, resulting in a worse minimum rate.

Max–Min Fairness Optimization for D2D Communications Coexisting with Cellular Networks

This paper considers a system consisting of a nonorthogonal multiple access (NOMA)-based device-to-device (D2D) communication system within a cellular network, in which the time and frequency resources are shared by everyone. In particular, D2D groups that constitute different pairs are assigned to the subchannels that the cellular users occupy. A max–min fairness optimization problem with power budget constraints is formulated and solved in this paper to reduce the mutual interference between the cellular users and D2D devices that substantially impacts that with the worst channel condition. For a low computational complexity solution, we propose the use of the bisection method together with the solution of a system of linear equalities. The proposed algorithm can provide uniformly good service to all of the cellular users and D2D devices in the coverage area by utilizing the minimal total transmit power. The simulation results indicate the effectiveness of the proposed algorithm in the improvement of the spectral efficiency of the worst user under the different widely used subchannel assignments and pairing techniques.

Subgrouping‐based multicast transmission over high‐throughput satellite systems with beam cooperation

SummaryThis paper investigates the multicast transmission for multicast services in high‐throughput satellite (HTS) systems. Considering the multibeam multicast feature of HTSs, cooperative transmission among beams is involved in to improve the efficiency of the multicast transmission. Since the multicast transmission rate depends on the worst user channel state, all the users experience an unreasonably low rate. In this situation, subgrouping techniques are employed to increase transmission rates of users. A subgrouping‐based multicast transmission problem aiming at maximizing the lowest transmission rate of the users is studied to guarantee fairness among users. We formulate the problem as a max–min optimization problem and propose two low‐complex subgrouping algorithms for this problem. Additionally, we also consider multicasting in a single beam and devise a two‐layer transmission scheme for it. In the performance evaluation part, besides the impact of parameters on subgrouping performance, we analyze the performance and the computational complexity of the proposed algorithms. The results indicate that the two subgrouping algorithms can achieve favorable performance with low complexity.

Multi-User Regularized Zero-Forcing Beamforming

Regularized zero-forcing beamforming (RZFB) is an interesting class of linear signal processing problems, which is very attractive for use in large-scale communication networks due its simple visualization as a straightforward extension of the well-accepted zero-forcing beamforming (ZFB). However, unlike ZFB, which is multi-user interference free, RZFB must manage multi-user interference to achieve its high throughput performance. Most existing works focus on the performance analysis of particular RZBF schemes such as the equip-power allocated RZBF under a fixed regularization parameter. This paper is the first work to consider the joint design of power allocation and regularization parameter for RZFB to maximize the worst users' throughput or the quality-of-service awarded energy efficiency under a fixed transmit power constraint. Such designs pose very computationally challenging optimization problems, for which the paper proposes two-stage optimization algorithms of low computational complexity. Their computational and performance efficiencies are substantiated through numerical examples.

Han–Kobayashi Signaling in MIMO Broadcasting

This letter applies Han-Kobayashi (H-K) superposition signaling to a network of a multi-antenna transmitter serving two multi-antenna users. By making the rate of the common message for both users contribute to user individual rate, it shows that H-K superposition signaling clearly outperforms both state-of-the-art orthogonal multiaccess and nonorthogonal multiaccess schemes (NOMA) in terms of the worst user rate. More importantly, unlike NOMA, H-K superposition signaling does not require the user channels to be differentiated for efficient implementation.

Subband CQI Feedback-Based Multicast Resource Allocation in MIMO-OFDMA Networks

Multicast transmission is one of the key enablers toward a more spectral- and energy-efficient distribution of multimedia content in current and envisaged cellular networks. In order to ensure that all users in a multicast group are able to correctly decode the received data, most multicast techniques adopt rather conservative strategies that select a very robust modulation and coding scheme (MCS) whose characteristics are determined by the propagation conditions experienced by the worst user in the group. Obviously, this robustness comes at the prize of a low spectral efficiency. Moreover, in the specific context of wideband communication systems, the selection of the multicast MCS has often relied on the use of wideband channel quality indicators (CQIs) providing rather imprecise information regarding the potential capacity of the multicast channel. Only recently has the per-subband CQI been used to improve the spectral efficiency of the system without compromising the link robustness. However, most subband-CQI multicast schemes proposed so far rely on overpessimistic assumptions that preclude the achievement of high data rates. In this paper, novel subband CQI-based multicast strategies are proposed that, relying on the selection of more spectrally efficient transmission modes, lead to increased data rates while still being able to fulfill prescribed quality of service metrics. To this end, a constrained optimization problem is posed that seeks to maximize the data rate of the whole multicast group while ensuring that the average block error rate for all users remains below a threshold and that a minimum data rate is guaranteed for all users in the group.

Symbol Error Rate Minimization Precoding for Interference Exploitation

This paper investigates a new beamforming approach for interference exploitation, which has recently attracted interest as an alternative to conventional interference-avoidance beamforming for the downlink of multiple-input multiple-output systems. Contrary to existing interference exploitation approaches that focus on signal-to-noise ratio performance, we adopt an approach based on the detection region of the signal constellation. Focusing on quality of service, we then formulate the optimization for minimizing the error probability (EP) for the worst user, subject to power constraints. We do this by employing the knowledge of channel state information at the transmitter, along with all downlink users’ data that are readily available at the base station during downlink transmission. In this context, we also show that the detection-region-based beamforming and the worst user EP downlink beamforming are equivalent problems. Finally, we further propose a sum EPs approach and provide an analytic bound of average symbol error rate performance. Our simulations verify that the proposed techniques provide significantly improved performance over conventional downlink beamforming techniques.

Spectral and Energy-Efficient Wireless Powered IoT Networks: NOMA or TDMA?

Wireless powered communication networks (WPCNs), where multiple energy-limited devices first harvest energy in the downlink and then transmit information in the uplink, have been envisioned as a promising solution for the future Internet-of-Things (IoT). Meanwhile, non-orthogonal multiple access (NOMA) has been proposed to improve the system spectral efficiency (SE) of the fifth-generation (5G) networks by allowing concurrent transmissions of multiple users in the same spectrum. As such, NOMA has been recently considered for the uplink of WPCNs based IoT networks with a massive number of devices. However, simultaneous transmissions in NOMA may also incur more transmit energy consumption as well as circuit energy consumption in practice which is critical for energy constrained IoT devices. As a result, compared to orthogonal multiple access schemes such as time-division multiple access (TDMA), whether the SE can be improved and/or the total energy consumption can be reduced with NOMA in such a scenario still remains unknown. To answer this question, we first derive the optimal time allocations for maximizing the SE of a TDMA-based WPCN (T-WPCN) and a NOMA-based WPCN (N-WPCN), respectively. Subsequently, we analyze the total energy consumption as well as the maximum SE achieved by these two networks. Surprisingly, it is found that N-WPCN not only consumes more energy, but also is less spectral efficient than T-WPCN. Simulation results verify our theoretical findings and unveil the fundamental performance bottleneck, i.e., "worst user bottleneck problem", in multiuser NOMA systems.

A Low-Complexity Transmit Beamforming Scheme in Relayed Multicast Systems

In this work, we study the problem of maximizing the system throughput assuming a multicast system with a multi-antenna Base Station (BS) and one single-antenna relay. We employ two different transmission slots: one in which only the BS transmits and one in which only the relay transmits. Given the multi-antenna and multi-slot nature of the problem, transmit beamforming and diversity techniques can be employed. We present the optimization problem and a heuristic scheme is proposed to solve the problem with low computational complexity. Our solution iteratively combines the current precoder with the optimal precoder to the current worst User Equipment (UE). The results show that the beamforming gain outmatches the loss from the additional time slot in the proposed scheme and that it is capable of performing close to the optimum.

User-relay Assignment based Antenna Selection Scheme in Multi-user Multi-relay AF Cooperative Communication Network

In this paper, the user-relay assignment based antenna selection scheme for multi-user cooperative network is proposed to improve the transmission bit rate and system performance. The low complexity suboptimal user-relay assignment algorithm is first proposed to simultaneously improve both the system performance and individual user’ performance in the multi-user amplify-and-forward (AF) cooperative user-relay network, where each user can fairly select its best relay according to the instantaneous channel state information (CSI). Based on the user-relay assignment scheme and space shift keying (SSK), we further present the antenna selection scheme to further enhance the system performance for the multi-user AF cooperative user-relay network. In order to minimize the system bit error rate (BER), three antenna selection criteria based on the maximum likelihood (ML) detection have been proposed. Numerical results and theoretical analysis show that the proposed schemes can effectively improve the average system sum rate, the outage probability of the worst user, and the system BER performance, compared with the other schemes.

Security-Reliability Trade-Off Analysis for Multiuser SIMO Mixed RF/FSO Relay Networks With Opportunistic User Scheduling

In this paper, we study the performance of multiuser single-input multiple-output mixed radio frequency (RF)/free space optical (FSO) relay network with opportunistic user scheduling. The considered system includes multiple users, one amplify-and-forward relay, one destination, and a multiple-antenna eavesdropper. The users are connected with the relay node through RF links and the relay is connected with the destination through an FSO link. Both maximum ratio combining and selection combining schemes are used at the multiple-antenna relay to combine the signal received from the best user on different antennas. The RF/FSO channels models are assumed to follow Nakagami- $m$ /gamma-gamma fading models with pointing errors. Closed-form expressions are derived for the outage probability, average symbol error probability, and ergodic channel capacity. Then, the power of the selected best user is determined to minimize the system asymptotic outage probability under the dominant RF or FSO link. Then, the considered system secrecy performance is investigated, where the closed-form expressions for the intercept probability are derived. Finally, we propose a new cooperative jamming model in which the worst user is selected by the authorized system to jam the existing eavesdropper. Monte-Carlo simulations are provided to validate the achieved exact and asymptotic results.

A Stochastic Approach for Resource Allocation with Backhaul and Energy Harvesting Constraints

We propose a novel stochastic radio-resource-allocation strategy that achieves long-term fairness considering backhaul and air-interface capacity limitations. The base station (BS) is powered only with a finite battery that is recharged by an energy harvester. The energy harvesting is also taken into account in the proposed resource-allocation strategy. The constrained scenario is often found in remote rural areas where the backhaul connection is limited, and the BSs are fed with solar panels of reduced size. Our results show that the proposed scheme achieves higher fairness among the users and provides greater worst user rate and sum rate if an average backhaul constraint is considered.

Power allocation and subcarrier assignment for joint delivery of unicast and broadcast transmissions in OFDM systems

Most existing studies on broadcast services in orthogonal frequency division multiplexing (OFDM) systems have focused on how to allocate the transmission power to the subcarriers. However, because a broadcasting system must guarantee quality of service to all users, the performance of the broadcast service dominantly depends on the channel state of the user who has the lowest received signal-to-noise ratio among users. To reduce the effect of the worst user on the system performance, we propose a joint delivery scheme of unicast and broadcast transmissions in OFDM systems with broadcast and unicast best-effort users. In the proposed joint delivery scheme, the BS delivers the broadcast information using both the broadcast and unicast subcarriers at the same time in order to improve the performance of the broadcast service. The object of the proposed scheme is to minimize the outage probability of the broadcast service while maximizing the sum-rate of besteffort users. For the proposed joint delivery scheme, we develop an adaptive power and subcarrier allocation algorithm under the constraint of total transmission power. This paper shows that the optimal power allocation over each subcarrier in the proposed scheme has a multi-level water filling form. Because the power allocation and the subcarrier assignment problems should be jointly solved, we develop an iterative algorithm to find the optimal solution. Numerical results show that the proposed joint delivery scheme with adaptive power and subcarrier allocation outperforms the conventional scheme in terms of the outage probability of the broadcast service and the sum-rate of best-effort users.