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.

High reliability is crucial for stable and accurate control in wireless Internet of Things (IoT) systems. Although average outage probability is a widely adopted metric for evaluating the reliability of wireless IoT systems, it does not account for the sparsity of outage occurrences, which can be interpreted as the frequency of outage occurrence within a certain time. Compared to an isolated single outage, clustered outages can significantly impact stability. To address this problem, we introduce the concepts of virtual queue and consecutively effective throughput. The virtual queue treats outage packets as arrivals, with its service rate determined by the desired frequency of the single outage. In contrast to the traditional throughput, consecutively effective throughput measures the effectiveness of consecutive success of transmissions. Based on these concepts, we then consider maximizing the consecutively effective throughput under virtual queue constraints. Theoretical analysis is conducted to derive the optimal rate for this problem. Specifically, we explore two scenarios: 1) outages caused by packet decoding errors and 2) outages due to packet decoding errors and latency violations. Considering the nonasymptotic property of the virtual queue, queueing theory is utilized to provide closed-form expressions for virtual queue constraints. Based on the theoretical analysis, efficient and effective algorithms are proposed to obtain the optimal rate based on the above analysis. Numerical comparisons between grid searches and our algorithms validate the correctness of our theoretical analysis. This study underscores the importance of specific scheduling designs to control clustered outages, rather than merely enhancing throughput in wireless IoT systems.

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).

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.

Space-Air-Ground Integrated Network is the trend for 6G network development. It could integrate many advantages from terrestrial network, satellites and high altitude platform stations, improving the coverage and service quality significantly. Meanwhile, breaking the barriers of heterogeneous networks and realizing the cooperation between them pose new challenges for network operation. This paper firstly analyzes the current situation and expounds technical researches and commercial achievements from the perspectives of standardization and industry. Secondly, we focus on network architecture, network sharing and private network, mainly investigating the operation and mutual enabling key technologies in Space-Air-Ground Integrated Network. Finally, we point out the challenges from “time-frequency-space” dimensions.

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.

Carrier aggregation was introduced to Long Term Evolution Advanced in order to improve the performance especially in terms of a higher peak data rate. When employed, sets of user equipment will have a set of serving cells, which includes a Primary cell (PCell) and Secondary cells (SCells). For inter evolved Node B (eNB) handover, target eNB is selected only consider the channel condition of the PCell. Thus, a suitable set of serving cells cannot be selected. In order to address this problem, this paper proposes three handover methods considering channel conditions for multiple cells. Methods 1 and 2 adjust the handover margin according to the difference in channel conditions between the PCell and SCells for the serving eNB. Method 3 decides handover based on equivalent channel conditions for the PCell and SCells in both the serving eNB and neighboring eNBs. Simulation results show that the proposed methods provide higher cell-edge throughput and a much smoother handover at the cost of a slightly increased number of handovers.

In LTE-Advanced, macro-pico heterogeneous networks (HetNet) are extensively discussed. Cell range expansion (CRE) and inter-cell interference coordination (ICIC) are introduced to improve the HetNet system performance. In this paper, semi-static ICIC and dynamic ICIC methods are discussed, and the problems facing conventional dynamic ICIC methods are analyzed and investigated. Joint decision and multiple feedback schemes are proposed to enhance the system performance through appropriate selection of normal/mute transmitting status and accurate scheduling for dynamic ICIC. Simulation results show that the proposed schemes achieve better average system performance and edge user performance than the semi-static ICIC and conventional dynamic ICIC methods, even when a reduced feedback method is used in the proposed schemes. The performance gain is as high as 9% for the average throughput and 30% for the edge user throughput with a proper bias and muting ratio.

This paper focuses on investigating appropriate management of Component Carriers(CCs) in carrier aggregation(CA) system, which is identified as one of the most distinct features of 4G systems including Long Term Evolution Advanced (LTE-A). An LTE-A user equipment (UE) is allowed to concurrently utilize multiple carriers, which leads to scalable increase in user throughput. However, in certain circumstances, aggregating entire available carriers for a UE is not meaningful due to probably low channel quality or high traffic load in some of the CCs. Therefore, how to make good use of multiple carriers in real deployment scenarios is an important issue. Based on the analysis of resource allocation across multiple carriers in Layer-2, two CC management methods in Layer 3 are proposed. The proposed method is shown by simulation results to be effective in providing comparable user throughput with lower implementation complexity, as compared to solely ingenious resource allocation.

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.

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 focuses on coordinated scheduling to combat uplink inter-cell interference for LTE/LTE-Advanced. In OFDM system, inter-cell interference is the dominant interference which limits system capacity, especially the performance of cell edge users. Meanwhile inter-cell interference in OFDM system has an inherent characteristic of interference fluctuation, which reduces the efficiency of channel dependent scheduling and the accuracy of MCS selection. In conventional inter-cell interference coordination methods, such as path-loss based coordinated scheduling, fractional frequency reuse and OI (overload indicator) based inter-cell power control, either the estimation of the interference is not accurate or the problem of interference fluctuation is not solved. To combat these problems, we propose a coordinated scheduling method by utilizing multiple OI thresholds. In our method, different OI thresholds are previously determined on different resource blocks, having a complementary pattern among neighbor cells. Based on the exchanged OI information among neighbor cells, one user can be scheduled to an appropriate resource block, on which the neighbor cells can endure inter-cell interference caused by this user. So high interference generated users and high interference endurable users are scheduled on same resource block, resulting in more accurate inter-cell interference estimation and reduced interference fluctuation.

CoMP JP (Coordinated Multi-Point Joint Processing) is regarded as a promising technique to improve both cell edge user throughput and cell average user throughput in LTE-A downlink. CoMP JP can be categorized as CoMP JT (Joint Transmission) and COMP DCS (Dynamic Cell Selection). Compared with CoMP JT schemes, CoMP DCS provides a good trade-off between the transmission algorithm complexity, backhaul overhead and system performance. Conventional DCS scheme can benefit cell edge users by instantaneous selecting the best severed eNB for cell edge users based on limited signaling overhead in uplink radio interface. DCS with muting scheme further apply muting to the strongest neighbor cell for decreasing interference to cell edge users. However the system spectrum efficiency may be degraded, since frequency reuse one is not maintained and radio resource (resource block and power) may not be fully used. An enhanced DCS with muting method is proposed here to further improve the frequency and power efficiency, by using adaptive muting mode selection based on capacity calculation and flexible power allocation based on muting mode selection status. Performance evaluation shows the proposed algorithm can provide about 5.5% cell average throughput gain and about 10% cell edge throughput gain respectively compared with conventional DCS schemes.

Single-carrier frequency division multiple access (SC-FDMA) has been selected as the uplink access scheme in the UTRA Long Term Evolution (LTE) due to its low peak-to-average power ratio properties. Nevertheless, in order to achieve such a benefit, it requires a localized allocation of the resource blocks (RBs), which naturally imposes a severe constraint on the scheduler design. In this paper, two improved recursive maximum expansion scheduling algorithms for SC-FDMA are proposed. Compared with conventional recursive maximum expansion (RME) scheme in which UE can only expand the resource allocation on neighboring RBs with the highest metrics, in proposed improved recursive maximum expansion (IRME) scheme, higher degree of freedom in RB expansion is achieved by allowing RB expansion within certain ranking threshold. Moreover, to further increase the flexibility in resource allocation, multiple surviving paths are introduced in proposed improved tree-based recursive maximum expansion (ITRME) scheme. The simulation results show that, compared with conventional RME scheme, the proposed IRME scheme can exhibit the gain about 15% in terms of spectral efficiency with a linear increase of computational complexity, and the performance can be further improved to 18% with proposed ITRME scheme if further higher complexity is permitted.

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.

Quality of Experience (QoE) reflects the customer's perception of service, and is extremely important for operators. In VoIP service, variety of factors will affect customer's QoE, e.g. source data quality and the transmission channel condition. In cellular systems, although higher level of source coding will improve QoE, more radio resource will be consumed and thus degradation of system capacity will be caused. On the other hand, lower level of modulation and coding can ensure the data delivery, but will lead to more consumption of radio resource. In this paper, to solve these problems in multi-user cellular systems, the source coding quality and channel coding levels are jointly considered according to customer's QoE. In the source and channel coding adaptation, customers with over qualified QoE will sacrifice some radio resource to improve the under guaranteed QoE of others, or increase the system capacity. The simulation shows that the algorithm can effectively balance the utility of limited radio resource and increase customer's satisfaction ratio and system capacity.

In order to reduce handover delay caused by handover failure, radio resource is reserved for handover users not only at target cell, but also at prepared cells. This has been agreed in 3GPP LTE. However, these reserved resources cannot be assigned for other users until the finishing of the handover, which results in inefficiency of radio resource utilization. This paper presents a new resource reservation scheme for handover users to achieve fast handover failure recovery and efficient radio resource utilization. By proposed scheme, a resource pool at prepared cells is shared among multiple users, and the number of prepared cells is dynamically set according to the service type of users. Numerical analysis and simulation results show that the proposed scheme can improve successful handover probability and reduce handover delay.

In this paper we focus on efficient retransmission strategy for MBMS that employs hierarchical modulation. Hierarchical modulation offers a mechanism to enable the transmission of several data streams on one single frequency channel, with different transmission qualities, which requires more efficient HARQ strategy for MBMS. Constellation rearrangement and symbol bits rearrangement based HARQ are two kinds of methods to improve the efficiency of MBMS transmission from the perspective of constellation diversity. To further improve the performance, we proposed a novel retransmission method, including two constellations designed for transmission and retransmission, the transmitter algorithm to select the constellation to be used based on feedback information and the receiver algorithm to combine the retransmission packets. The merit of the proposal is to obtain the benefits from constellation rearrangement and symbol bits rearrangement simultaneously via once retransmission so as to save retransmission number, resulting in improved spectrum efficiency. Simulation results show our algorithm can provide about 21.5% cell throughput gain and 23% cell edge throughput gain than other HARQ methods.

We address the user selection scheme in multi-user wireless communication system, utilizing zero-forcing beamforming for spatial division multiple access. Recently, it has been shown that multi-user scheduling can help to achieve significant throughput gain in addition to the MIMO spatial multiplexing gain. And the capacity-greedy user selection algorithm can achieve near-optimal performance with much lower complexity compared with exhaustive search, due to reduced trial times of possible user combinations. However the computational complexity may be still too high for feasible applications, which depends on the system bandwidth, the number of active users and the number of antennas. In this paper, a novel capacity-greedy user selection scheme is proposed for the multi-user zero-forcing beamforming system, which involves low-complexity approximation for multi-user zero-forcing beamforming capacity. Simulation results verify that the proposed scheme can reduce the computational complexity of user selection greatly, with slightly performance loss.

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.

This paper focuses on bidirectional relaying schemes for multihop communications. For a two hop communication system, traditional 4-step bidirectional relaying (TBR) method allocates 4 slots, resulting in low efficiency; Coded bidirectional relaying (CBR) method, making use of network coding, needs only 3 slots, can provide throughput improvement up to 33% compared with TBR method; Two-way relaying method performs data bidirectional relaying with 2 slots, by employing interference cancellation algorithms in the relay station, can further improve spectrum efficiency. However due to different channel condition between RS to BS and RS to MS and broadcast transmission utilized from RS to BS and MS, CBR and two-way relaying methods can not fully exploit the channel capacity from RS to BS and RS to MS simultaneously. In order to solve the problem, we propose two enhanced relaying schemes: the first one is hierarchical modulation (HM) based scheme, in which HM is adopted to allocate individual MCS for each hop and a novel network coding pattern is designed to avail the introduction of HM to relaying. To further improve the performance of the first method, another method as hybrid constellation based relaying scheme is proposed, in which each end node jointly utilizes a hybrid constellation and the prior data it previously transmitted to retrieve the information from the other end node. Performance evaluation results show our algorithms solve the problem successfully and can improve system spectrum efficiency by 5-12% compared with traditional CBR method. Finally it is concluded that the enhanced bidirectional relaying schemes are promising relaying schemes candidates for multi-hop communications.

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.

Multi-carrier based radio access schemes have been widely accepted as one of the PHY candidates in many standards, for their capabilities not only to combat multi-path propagation, but also to support multiple user access aided by multi-user scheduling. The performance of multi-user wireless system with multi-user scheduling depends on the fluctuation of independent channel response across different users. However, the channel selectivity may be limited in some channel conditions, e.g., light-of-sight (LOS) or spatial correlation, which may limit the multiuser diversity gain. Multi-degree random cyclic delay diversity (MD-RCDD) (Zhengang Pan et al., 2006) scheme is introduced to obtain opportunistic beamforming gain with intensified frequency fluctuation of channel response. However, the available delay sets in MD-CDD are randomly generated, not fully utilizing the spatial resources. Therefore, multi-degree adaptive cyclic delay diversity (MD-ACDD) scheme is proposed in this paper to further optimize the system performance, in which the available delay sets are channel-dependent, and generated based on the feedback information of all users. Moreover, the detailed working procedure and overhead analysis are presented, and simulation results show that proposed scheme can achieve significant performance gain compared with conventional MD-RCDD.

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.

Significant throughput gains can be obtained in multi-user wireless system by exploiting the combination of multi-user scheduling in media access control (MAC) layer and MIMO spatial multiplexing using precoding in physical (PHY) layer. In this paper, we propose a multi-stage hybrid scheduling scheme for codebook-based precoding system, which applies different scheduling methods at different scheduling stages for selecting user equipments (UEs). In detail, we employ different scheduling algorithms when the appropriate UE or UE sets are selected within the same precoding vector, within the same precoding matrix, and within the codebook, respectively, so that we could finely adjust the balance between capacity and fairness. Computer simulation results show that the proposed scheme effectively fills the performance gap between pure maximum carrier-to-interference (C/I) power ratio and pure proportional fairness (PF) methods, and provides an important means at the MAC layer to lever between aggregate cellular throughput and geometry-specific per-user fairness, in order to meet the requirements of more precise quality of service (QoS) provision for future mobile communication systems.

This paper aims to address the problem of inter-cell interference fluctuation, which is inherent on the uplink direction of future cellular systems employing OFDMA or single carrier as multiple access technology. We present here a novel uplink adaptive resource allocation algorithm based on inter-cell interference measurement to achieve both multi-user diversity gain and the cancellation of inter-cell interference fluctuation. The phenomenon of inter-cell interference fluctuation in future cellular systems is explained and its negative effect on traditional resource allocation methods is analyzed. The proposed algorithm includes two independent sub-algorithms: 1) user grouping based resource allocation scheme, in which radio resource is limited to be reallocated within a group of users generating close inter-cell interference; 2) power compensation based resource allocation scheme, in which inter-cell interference fluctuation is compensated by adjusting transmitting power of UE. And performance evaluation results show that our algorithms smooth the inter-cell interference successfully and can improve system spectrum efficiency by 10-15% compared with existing traditional adaptive resource allocation schemes.

Link adaptation, scheduling, and hybrid automatic repeat request (HARQ) are indispensable technology for wireless networks to provide high speed packet data services. While prior scheduling algorithms based on the instantaneous data rate to determine the user to be served in each scheduling interval are useful, they do not fully take into account transmission errors and the impact of retransmission techniques to recover those errors. We propose a more accurate measure of users' effective Signal-to-Noise Ratio (SNR) that accounts for the reliability as well as retransmissions when scheduling transmissions to users. Extensive simulation results comparing performance of the proposed method to conventional methods are presented.

An adaptive turbo coded modulation orthogonal frequency division multiplexing (OFDM) schemes with power variable over subcarriers, variable over subbands, and constant over subcarriers is proposed. Our object is to improve the overall throughput under target bit-error-rate (BER) for OFDM transmissions. Simulation results indicate that our fixed power adaptation scheme exhibits a more than 7dB signal-noise-ratio (SNR) gain relative to nonadaptive turbo coded modulation, and about 2dB additional gain can be achieved with our variable power adaptation. We also discuss the effect of the amount of subbands on throughput performance in our adaptive scheme.

In this paper, two adaptive orthogonal frequency division multiplexing (OFDM) schemes employing rate-compatible turbo coded modulation with power variable subband-by-subband and symbol-by-symbol are proposed. Our object is to reduce the overall transmit power under target bit-error-rate (BER) for constant throughput OFDM transmissions. Simulation results indicate that our adaptive scheme with power variable over symbols exhibits a more than 5 dB signal-noise-ratio (SNR) gain in contrast to non-adaptive turbo coded modulation, and about 1-2 dB SNR gap from our scheme with power variable over subbands. We also discuss the effect of the amount of subbands on our adaptation performance.

Orthogonal frequency division multiplexing (OFDM) is one of the promising techniques in the next generation high-speed data rate wireless networks for its ability to combat the intersymbol interference(ISI), and fair scheduling algorithms are used to utilize the independence of the fading statistics of different user to improve the spectral efficiency. In this paper, we try to analysed the performance of fair scheduling algorithms in the OFDM systems and choose the appropriate subband size to tradeoff between the throughput and the channel feedback. We show that asymptotic scheduling gain of fair scheduling algorithms in the OFDM system increases as the number of user increases and decreases with the average received SNR. We also present the distribution of the averaged received signal-to-noise-ratio (SNR) in a subband, give a formula to evaluate the scheduling gain approximately, and point out that the maximal eigenvalue is a good indicator to choose the appropriate subband size. It is shown that the appropriate subband number is 16 for channel A or 32 for channel B.