Wireless caching has attracted substantial attention due to the potential for reducing service delays. However, it will waste energy if the cached content item is not requested by users. In order to improve the energy efficiency of wireless caching, we present a socially motivated wireless caching strategy from the cross-domain perspective in this paper. To this end, we first study the evolutionary requesting model based on users’ preference and their social ties. Then we derive the approximated expression for the delay-outage probability with a given power allocation strategy over Rayleigh block fading channels based on the saddle point technology. Based on the derived expression, a two-layer binary search method is presented to determine a suitable caching volume with a given outage probability and a power constraint. After that, we formulate a cross-layer optimization problem to jointly allocate the storage and transmission resources. By solving this optimization problem, we can determine the caching strategy to minimize the power consumption while promising the hit ratio performance. In addition, we extend the energy-efficient caching system over additive white Gaussian noise channels. Finally, numerical results are presented to demonstrate the potential of the presented caching strategy.

This article investigates the integration of movable antennas (MAs) into multicast communication systems. By discretizing the motion of the MAs, a novel MA-assisted multicast transmission architecture is formulated. An alternating optimization (AO) algorithm based on successive convex approximation is proposed to optimize the transmit beamforming and antenna positions. To gain further insights, the two-user case is examined, and a closed-form expression for the optimal beamformer is derived. On this basis, a low-complexity greedy search algorithm is developed to optimize the placement of the MAs. Furthermore, under the assumption of a line-of-sight propagation environment, a branch-and-bound algorithm is designed to determine the globally optimal antenna configuration with reduced complexity compared to exhaustive search. Numerical simulations confirm that the proposed methods effectively enhance the achievable multicast rate.

The integrated sensing and communication (ISAC) attracts growing interest in 6G due to the extension of radar capability. This paper devotes to the resource allocation problem in ISAC system design. Both static and dynamic resource allocation schemes are comprehensively investigated, with the primary distinction lying in the allocation of resources to either communication or sensing services, or their shared utilization. We construct two-class multi-server queues of each scheme, respectively, where communication and sensing services are modeled as Poisson processes with distinct arrival and service rates. To derive the steady-state probabilities of the two models, we present proofs of reversibility. Additionally, key matrices are derived for performance measurement purposes. Numerical results demonstrate the superiority of the dynamic allocation scheme while also providing insights into resource investment and division.

Passive Internet-of-Things (IoT), as a new communication technology, is expected to enable massive device connectivity in a cost-effective and energy-efficient manner. One of the most important topics on Passive IoT is to find a suitable waveform that can be affordable for a wide range of IoT devices. In this paper, we propose a novel waveform design that leverages a low-power on-off keying (OOK) wave. This design cleverly reuses the orthogonal frequency division multiplexing (OFDM) signal generated by the legacy 5G base station, i.e., gNodeB (gNB). Additionally, we enhance the OOK waveform using a central part repetition scheme to acquire frequency diversity gains, thereby improving its resilience against fading channels in realistic environments. Thanks to the repetition being applied only to the central part, no additional bandwidth resources are needed to support the low-power waveform. Simulation results are provided to validate the effectiveness of our approach, demonstrating significant potential for low-power transmissions in passive IoT.

A pioneering secure transmission scheme is proposed, which harnesses movable antennas (MAs) to optimize antenna positions for augmenting the physical layer security. Particularly, an MA-enabled secure wireless system is considered, where a multi-antenna transmitter communicates with a single-antenna receiver in the presence of an eavesdropper. The beamformer and antenna positions at the transmitter are jointly optimized under two criteria: power consumption minimization and secrecy rate maximization. For each scenario, a novel suboptimal algorithm was proposed to tackle the resulting nonconvex optimization problem, capitalizing on the approaches of alternating optimization and gradient descent. Numerical results demonstrate that the proposed MA systems significantly improve physical layer security compared to various benchmark schemes relying on conventional fixed-position antennas (FPAs).

A novel orthogonal frequency division multiplexing (OFDM)-based private-public communication framework is proposed, which harnesses reconfigurable intelligent surface (RIS) to improve the sum private and public rates. A two-user RIS-enabled OFDM system is considered, where the total subcarriers are partitioned into three segments, with two exclusively assigned to users for private/secure communications, while the third segment is reserved for public messages. The active beamformer at the transmitter and the passive reflecting beamformer at the RIS are jointly optimized to maximize the summation of the private/secure rate and the public rate. A novel joint design algorithm is proposed by capitalizing on the mathematical structure of the optimal active beamformer, eliminating the need for iterative updates between the transmit beamformer and the RIS-reflecting beamformer. Numerical results underscore the superior computational efficiency of our proposed algorithms compared to state-of-the-art methods based on alternating optimization, all while achieving nearly identical sum-rate performance.

This paper introduces a novel satellite handover scheme considering the link outage probability (SHLOP). It aims to improve the resource utilization of satellite handover processes in satellite- UAV integrated networks and address the limitations that the state-of-the-art failed to consider the impact of intermittent satellite-ground and inter-satellite links in UAV collaborative penetration scenarios. SHLOP dynamically adjusts the ratio of allocated channel resources for handover according to the link outage probability and the number of UAVs, which helps to reach a compromise between handover success probability and resource efficiency excluding wasted resources. Besides, a performance evaluation model is developed to analyze the relationship between resource utilization, the ratio of reserved resources, the number of users, and the link outage probability. The formulated model identifies a closed-form solution for the optimal reserved resource ratio, which optimizes the SHLOP performance. Numerical evaluation results show that SHLOP outperforms the PDRA and DCR-DQN by at least 11% in terms of resource utilization with intermittent links.

Integrated sensing and communication (ISAC) has been treated as a key technology for providing high-quality performance on both communication and sensing with higher spectrum efficiency and lower hardware cost. Among the research on ISAC, joint Radar and communication (JRC) is one of the typical scenarios. In this paper, we focus on designing the optimal JRC scheduling policy and characterizing the optimal tradeoff between the performance of communication and detection in a time-sharing JRC system. To this end, an optimization problem of minimizing the average delay with the constraints on the average power and detection probability is proposed. With the help of the constrained Markov Decision Process (CMDP) and linear programming (LP), the optimal cross-layer JRC scheduling policy is presented, which also reveals the optimal tradeoff between the performance of the communication and sensing in this JRC system. Moreover, we demonstrate the condition for detection scheduling not occupying the time resources ought to be allocated to send data in the communication-centric system. When this condition holds, we call this JRC system achieves ‘sensing for free’. For the JRC system with this property, the complexity of scheduling design can be reduced while the time resources can be utilized more efficiently.

Ultra Massive MIMO is one of the potential key technologies in 6G, which attracts widespread attention from academia and industry recently. Generally, the system-level simulation is essential to evaluate the performance of Ultra Massive MIMO. However, due to ultra-large-scale antennas and extremely high concurrency, the computation complexity is pretty high, which makes the simulation workload unbearable. To deal with this issue, we propose a two-level parallel optimization via OpenMP and Eigen to drastically promote the simulation efficiency in this paper. Moreover, we provide a comprehensive insight on 6G system-level evaluation platform with modular architecture and parallel computing. It is validated that our simulation platform has the capability of evaluating 6G Ultra Massive MIMO technology and the simulation efficiency can be improved by more than 20 times than that of without parallelization. Based on the simulation results, it is shown that the UE experienced data rate can be increased up to 10 times than that of 5G, which can meet the requirement of 6G.

Wireless communication enabled integrated sensing and communication (ISAC) attracts growing interest recently. This paper investigates the sensing ability of OFDM and OTFS signals. We derive the expression of their ambiguity functions, and show that the ambiguity surface can be shaped by the information carried. To this end, we then develop a Zak-transform based ambiguity function synthesis method and deduce the corresponding information sequence in the l2-norm case. Finally, we present the ambiguity surface of it, and compare it with the Zaddoff-Chu and gold sequences that are widely used in LTE and NR systems. Simulations validate the dependency of sensing performance on the designed sequence and the size of the time-frequency resource.

Integrated sensing and communication (ISAC) has been treated as a key technology for providing high-quality performance on both communication and sensing with higher spectrum efficiency and lower hardware cost. Among the research on ISAC, joint radar and communication (JRC) is one of the typical scenarios. Due to remaining challenges on the design for full-duplex hardware and interference depression, time-division JRC is believed as the first step toward ISAC by switching communication and sensing functions in the time domain. In this article, we focus on designing the optimal cross-layer JRC scheduling policy and characterizing the optimal tradeoff between the performance of communication and sensing in a time-division JRC system with a buffer. For both active and passive radar detection scenarios. To this end, optimization problems of minimizing the average delay with different constraints on the average power and detection performance are formulated. With the help of constrained Markov decision process (CMDP) and linear programming (LP), optimal JRC scheduling policies are presented, which also reveal the optimal tradeoff between the performance of the communication and sensing. Moreover, we summarize the condition for sensing scheduling not occupying the time resources which ought to be allocated for communication in a communication-centric system. When this condition holds, we say this JRC system achievessensing for free. Based on the analysis ofsensing for freeand the investigation of numerical results, a heuristic policy is proposed for JRC systems with passive radar detection. Some insights are obtained into the scheduling design of time-division JRC systems.

The orthogonal time frequency space (OTFS) modulation as a promising signal representation attracts growing attention for integrated sensing and communication. This paper devotes to MIMO-OTFS based channel parameter estimation. Inspired by the insight that superimposed signals can be composed iteratively and processed separately, we develop the Space-Alternating Generalized Expectation-Maximization (SAGE) algorithm to support the resolution of multiple paths with modest complexity. Besides, we derive the Cramer-Rao lower bound (CRLB) of the variance of channel parameters as the fundamental limit of sensing in the OTFS modulation scheme as well as the baseline of the performance evaluation. Simulations in various cases demonstrate the feasibility.

The discontinuous reception (DRX) mechanism is adopted by the Third Generation Partner Project (3GPP) Long Term Evolution (LTE) as a promising technology to extend the user equipment's (UE's) battery lifetime. From our simulation, it can be found that the decrease in power consumption resulted from LTE DRX is always at the price of deteriorated system utility. Thus, this paper focuses on the design of an improved DRX configuration method to provide higher power efficiency. The single threshold adaptive configuration DRX mechanism (S-ADRX) is proposed to guarantee the system utility at the cost of extra energy consumption. Based on S-ADRX, a novel multi-threshold adaptive configuration DRX mechanism (M-ADRX) is presented, which is able to save as much power as possible while maintaining the system utility without any additional signaling overhead. Simulation results indicate that the proposed M-ADRX mechanism outperforms the current LTE DRX.

3rd Generation Partnership Project (3GPP) is specifying Long Term Evolution Advanced (LTE-A) targeting for higher average cell and cell-edge spectrum efficiency over LTE, and multi-user MIMO (MU-MIMO) is identified as a key technique to reach the International Mobile Telecommunication Advanced (IMT-A) performance requirements. In this paper, we present the investigation on the MU-MIMO enhancement issues in LTE-A mainly from the viewpoint of MU-MIMO transparency, i.e., necessity of indication of co-scheduled UEs in the same resource block, and demodulation reference signal (DM-RS) configuration. Besides qualitative analysis from various system impacts, e.g., signaling overhead, scheduling flexibility and channel estimation accuracy, extensive numerical results are provided by both link-level and system-level simulations. In addition, we further propose an adaptive data mapping scheme for transparent MU-MIMO to improve the channel estimation accuracy. Moreover, a novel system-level simulation methodology taking into account dynamic change of channel estimation error is provided in this paper. Finally, based on the investigation results, we propose transparent MU-MIMO with quasi-orthogonal DM-RS configuration in LTE-A.

In order to meet the requirement of wider bandwidth in IMT-Advanced, carrier aggregation (CA) is introduced by 3GPP to support bandwidth up to 100MHz in its LTE-Advanced standards. An LTE Rel.10 UE can aggregate up to 5 component carriers (CCs) simultaneously, but may be assigned only part of the total available CCs depending on its capability or traffic load. Thus, a proper CC selection method is necessary. First, two traditional CC selection methods respectively named Random and Round Robin CC selection are investigated, which can well balance the load across different CCs. However, neither of them is suitable for non-continuous CA scenarios through our analysis. To solve this problem, an improved CC selection method for non-continuous CA is proposed in this paper. Simulation results demonstrate that the proposed method outperforms both of the traditional ones.

Due to the limited feedback amount, the codebook and feedback design is very important. In order to achieve better tradeoff between overhead and performance, the double codebook structures are proposed and discussed, where a final precoder W is determined by two precoders W1and W2, which are selected from two different codebooks. In this paper, we give an overview of several double codebook structures and evaluate them based on system level simulations (SLS). We consider two frameworks to determine a final precoder: W1W2and W2W1where W1and W2track long-term/wideband and short term/subband channel properties, respectively. It is shown that under 4Tx assumption, double codebooks achieve gains compared with Rel.8 codebook when considering the multi-user (MU) MIMO and do not suffer in the case of single-user (SU) MIMO. Both W1W2and W2W1provide nearly the same gains over that for the Rel. 8 codebook with uniform linear array (ULA) deployment. Furthermore, W1W2framework performs better than W2W1framework with cross-polarized array (CPA) deployment.

This paper proposes a novel distributed QoSguaranteed multi-cell radio resource allocation (RRA) scheme for OFDMA systems, which includes two separate steps operated on two time levels: the Hungarian algorithm based intra-cell fast scheduling on the frame level and the X2 interface based inter-cell interference coordination (ICIC) algorithm performed on the super-frame level. The scheme is distributed in the sense that both algorithms are carried out by the enhanced Node B (eNB). Through intense analysis, we proved that the ICIC algorithm not only provides fine robustness against ICI but also achieves good load balancing from a new perspective. Simulation results indicate that the performance of the proposed scheme, when compared to the standard "universal reuse" approach without inter-cell coordination, is significantly better in terms of increasing both the network and cell-edge throughputs.

Coordinated Multi-Point (CoMP) transmission is considered for Long Term Evolution - Advanced (LTE-A) as an effective method to improve both average and cell-edge throughput. However, most of current research on CoMP with Multi-User (MU)-MIMO are under ideal assumption. In this paper, we study CoMP under realistic conditions, including limited feedback and complexity. Taking both performance and complexity into consideration, a hybrid cooperating set selection scheme is proposed. Furthermore, Channel Quality Indicator (CQI) estimation based on instantaneous precoder and CQI update based on statistical distribtion are proposed to improve CQI accuracy for Modulation and Coding Scheme (MCS) selection. Finally, the system level simulation results of CoMP with MU-MIMO are provided, which show that, compared with single cell transmission, CoMP MU-MIMO with our proposed scheme can achieve considerable performance gain in terms of both average and cell-edge throughput.

For E-UTRA, semi-persistent scheduling has been adopted for Voice over Internet Protocol (VoIP) service. Semi- persistent scheduling is suitable for voice traffic which has constant rate characteristics and small packet size. However, the compressed VoIP packet after ROHC (Robust Header Compression) still has size variation. The variation of compressed VoIP packet size causes problem of packet segmentation propagation. In this paper a complementary resource allocation scheme is proposed. Complementary resource is notified to UEs along with predefined persistent pattern at the beginning of VoIP session. Complementary resource is allocated when VoIP packet with the sizes bigger than the size of predefined resource generated and blind decoding is implemented at the UE side. Simulation results show that the proposed scheme can reduce L1/L2 control signaling significantly while support large number of VoIP UEs compared with conventional solutions.

Codebook based multiple-input multiple-output (MIMO) precoding can significantly improve the system spectral efficiency with limited feedback and has been accepted as one of the most promising techniques for the evolved UTRA (E-UTRA). Compared with single-user (SU) MIMO, multi-user (MU) MIMO can further improve the system spectral efficiency due to increased degree of freedom in transmission. In order to reduce the feedback overhead and computational complexity, feedback of single rank 1 (corresponding to transmission of single stream) channel quality indicator (CQI) is required in E-UTRA currently. Then, the main challenge is how to obtain CQIs of other ranks at Node B for rank adaptation with single CQI feedback. Therefore, in this paper, an efficient CQI update scheme at Node B arising from statistical characteristics of CQI of various ranks is proposed. Simulation results show that our proposed scheme can yield significant improvement on spectral efficiency compared with conventional CQI update schemes.

To meet the increasing demand of wireless services associated with the scarcity of the radio spectrum and the trend to provide end to end quality of service (QoS), on the one hand advanced technologies that harness the available resource efficiently should be developed, on the other hand the collaboration of different layers such as physical (PHY) layer and medium access control (MAC) layer is needed. In this paper, we propose a joint space-frequency-power scheduling algorithm (JSFP) for real time service in multiuser cellular MIMO-OFDM system which jointly optimizes the subcarrier, bit and power allocation in the PHY layer along with the scheduling in the MAC layer to exploit the multiuser diversity. This algorithm considers both the user equipments (UE)' QoS requirements (such as packet delay and packet loss ratio) and the UEs' channel conditions and includes three parts: packet scheduling, subcarrier allocation and antenna selection, power allocation. Numerical results show that the proposed algorithm achieves significant system performance improvement compared with the conventional methods.

Codebook based multiple-input multiple-output (MIMO) preceding can significantly improve the system spectral efficiency with limited feedback and has been accepted as one of the most promising techniques for the Evolved UTRA (E-UTRA). Compared with single-user (SU) MIMO, multi-user (MU) MIMO can further improve the system spectral efficiency due to increased degree of freedom in transmission. In order to reduce the feedback overhead, feedback of single channel quality indicator (CQI), e.g. rank 1 CQI, is required in E-UTRA currently. Then, the main challenge is how to obtain CQIs of other ranks at node B for rank adaptation with single CQI feedback. Therefore, in this paper, an efficient CQI update scheme at node B based on statistical characteristics of CQI of various ranks is firstly proposed. To further increase the accuracy of CQI at node B for data transmission, an adaptive CQI feedback scheme is then proposed in which single CQI with the rank same as previously scheduled is fed back. Simulation results show that our proposed CQI update scheme can achieve some performance gain compared with conventional method with fixed backoff. Moreover, with proposed adaptive feedback scheme, much additional performance gain can be obtained and the performance can approach the upper bound.

For the Evolved UTRA (EUTRA), in OFDMA uplink, the Inter-cell interference cannot be predicted precisely, so scheduling becomes a puzzling problem and directly affects the uplink performance in OFDMA based system. Previous works (Galdata, et. al., 2003) did not concern such a problem or just consider single cell environment. In this paper, a novel scheme is proposed that could efficiently solve this problem in multi-cell circumstance. It predefines UEs distributed in the whole cell adopt fixed modulation and coding scheme (MCS) according to the distance from Node B. It employs initial average predictive interference to create the first-loop Inter-cell interference and perform scheduling according to the historical information in the following. Fast power control is adopted in order to compensate the imprecisely predictive inter-cell interference. Soft frequency reuse scheme is adopt in order to improve the cell-edge UE performance. To guarantee the UE fairness, proportional fairness (PF) scheduling is adopted in single input and single output (SISO) environment in this paper.

As the evolution of 3G, long term evolution (LTE) standardization activity is issued in 3GPP and 3GPP2. In previous paper OFDMA is proposed for downlink of LTE. As the channel reciprocity can be obtained in TD-SCDMA LTE system, the channel status information (CSI) can be exploited at the transmitter to obtain the spatial-frequency multiuser diversity by joint spatial-frequency subcarrier and antenna assignment of MIMO OFDMA for the independent fading of different user in spatial and frequency domain. To guarantee the user fairness, a joint spatial-frequency proportional fairness (PF) scheduling is proposed in this paper. Further, no inter-cell interference mitigation capability can be observed from the current MIMO OFDMA schemes in downlink, the soft frequency reuse is adopted in this paper to avoid the inter-cell interference. Finally the downlink performance of the TD-SCDMA LTE with no-real time service is evaluated with spatial frequency PF scheduling and soft frequency reuse in multi-cell scenario