To realize the potential of integrated sensing and communication (ISAC) in cell-free (CF) massive MIMO system, an ISAC framework is proposed in this paper. With numbers and locations of scatterers (targets) unknown, based on received downlink data signals from the transmit access point (tAP) antenna, multiple receive access points (rAPs) first estimate delays locally. In each outer iteration, by comparing the estimated delays with the delays of the paths through extracted scatterer locations, selected rAPs search out mismatched estimated delays. Through cooperation, the potential locations of the scatterers forming each candidate location set corresponding to each mismatched delay are obtained, and each set will be evaluated in sequence. Specifically, a joint evaluation algorithm is proposed, where the probability model for the joint evaluation problem is established based on delay and limited angular information. Under the expectation maximization (EM) framework, by fusing information from all the rAPs, the extracted scatterer locations and candidate locations are adjusted, and the evaluation results are estimated, which can be regarded as the global probability of scatterers exist at candidate locations. When the evaluation results of all the locations in a candidate location set are low, the corresponding delay will be discarded, otherwise, the candidate location with the highest evaluation result in the set will be extracted. The proposed framework avoids exhaustive search in different associations of scatterers and estimated delays, and is more flexible than extraction from all the candidate locations based on fixed thresholds. Then, based on a simplified model, the impact of system parameters on delay based location sensing accuracy is revealed with the theoretical analysis. Finally, based on the prototype system with CF radio access network (RAN) architecture, the proposed framework is experimentally validated.

This article proposes an uplink transmission scheme for cell-free (CF) massive multiple-input-multiple-output (MIMO) systems in high-speed railway communications to mitigate the negative effects of fast time-varying multipath channels with fewer antennas and insufficient angular resolution. To enhance the estimation performance by utilizing the possible similarity of the relatively slow time-varying channel parameters, the Dirichlet process (DP) is introduced to construct the probabilistic model of the doubly selective multiparameter channel estimation problem, which is solved by adopting the expectation-maximization (EM) framework. Furthermore, by introducing successive approximation, an enhanced channel estimation scheme is proposed. Finally, for the data transmission utilizing the orthogonal frequency-division multiplexing (OFDM) modulation, based on estimated channel parameters, a distributed intercarrier interference (ICI) elimination algorithm with local channel quality-based combining is proposed, and the performance of the system under different architectures and ICI elimination algorithms is analyzed. Simulation results show that DP can improve estimation performance by utilizing implicit similarity, the combination of first-order Taylor expansion and successive approximation can effectively improve estimation performance at higher speeds under relatively higher pilot power, and compared to centralized processing, the proposed distributed ICI elimination algorithm with local channel quality-based combining has a relatively small performance loss.

In this paper, we investigate the problem of optimizing the overall system secrecy spectral efficiency of cell-Free massive multiple-input multiple-output (CF-mMIMO) with network-assisted full-duplexing (NAFD) system, considering resisting interception by superimposing artificial noise (AN) on the transmitted signal. The access points (APs) are selected by binary mode selection vectors as transmitting or receiving APs flexibly to serve both uplink and downlink users simultaneously. Since optimization variables are tightly coupled, a double-loop strategy is developed to solve the non-covex combinatorial optimization problem. The outer loop is constructed according to greedy search for duplex mode selection, while the inner loop based on the proposed successive convex approximation (SCA) algorithm aims to optimize the transceivers and AN. Simulation results show that the proposed solution is superior to the fixed-mode duplex scheme in terms of secure spectral efficiency and able to achieve similar performance to that of the optimal exhaustive search scheme.

Sensor sharing is an important ability for vehicle platoon to reduce vehicle costs and improve driving safety. However, sensing data with a large amount of information is difficult to be shared by using traditional communication methods. Applying millimeter-wave communication can improve sensor sharing capabilities of vehicles, but millimeter wave has large propagation loss and is easy to be blocked by obstacles. Therefore, how to apply millimeter-wave communication to improve sensor sharing capabilities in vehicle platoon is still an open issue. To this end, we present a stochastic game approach and propose two distributed algorithms to achieve high-reliability and low-energy sensor sharing. First, we model the multihop millimeter-wave sensor sharing of the vehicle platoon as an optimization problem of reducing energy consumption while ensuring communication reliability, and then based on the characteristics of vehicle communication, we transform the optimization problem into a multiagent stochastic game. Second, by utilizing the characteristic that the immediate cost has nothing to do with the transfer function of the game, we prove that this stochastic game has equilibrium by proving that each subgame has a Nash equilibrium. Third, we propose an equilibrium-guided multiagent distributed (EGMD) algorithm to obtain the optimal action of each vehicle in the platoon, and then based on the analysis of the limitation of the approach, we present a multiagent distributed cooperation (MDC) algorithm to further reduce the system energy consumption. Finally, through simulation experiments, we evaluate a variety of approaches and demonstrate that our proposed methods can significantly reduce energy consumption while ensuring communication reliability.

Reconfigurable intelligent surface (RIS) is a new paradigm that has great potential to achieve cost-effective, energy-efficient information modulation for wireless transmission, by the ability to change the reflection coefficients of the unit cells of a programmable metasurface. Nevertheless, the electromagnetic responses of the RISs are usually only phase-adjustable, which considerably limits the achievable rate of RIS-based transmitters. In this paper, we propose an RIS architecture to achieve amplitude-and-phase-varying modulation, which facilitates the design of multiple-input multiple-output (MIMO) quadrature amplitude modulation (QAM) transmission. The hardware constraints of the RIS and their impacts on the system design are discussed and analyzed. Furthermore, the proposed approach is evaluated using our prototype which implements the RIS-based MIMO-QAM transmission over the air in real time.

How much performance gain for the user equipment (UE) located at cell‐edge can be obtained, from the interference cancellation (IC) by exploiting extra degrees of freedom in multi‐user massive multiple‐input multiple‐output (MIMO), needs to be investigated. Also, it is necessary to reveal the impact of this IC on the performance of cell‐centre UE (CCU). In this study, the authors separately analyse the coverage probability of cell‐edge UE (CEU) and CCU under the IC in irregular network utilising tools from stochastic geometry. Specifically, the closed‐form expressions for the upper bound of CEU coverage probability and the lower bound of coverage probability for CCU are given out. For large threshold scenario, the authors show the potential of massive MIMO with IC on achieving the cell‐centre‐like experience in a more simple closed‐form formula. Analytical and numerical results show that a reasonable balance between the CEU performance enhancement and the CCU performance degradation under the IC can be reached. Moreover, slight influence of cell‐edge area on the coverage probability for both CEU and CCU is observed. Finally, it is found that the coverage probability of CEU is more sensitive to the variation of density of UEs and the base stations than that of CCU.

The spatial degrees of freedom will be sacrificed to perform the precoding‐based interference management (IM) for the cell‐edge user (CEU) in a massive multiple‐input and multiple‐output enabled irregular network. It is desired to evaluate the impact of the precoding‐based IM on the performance of both the cell‐centre user (CCU) and CEU, which leads to a consideration of the balance between the CEU performance enhancement and the CCU tolerable performance degradation. Thus the separate analysis of CEU and CCU performance under the precoding‐based IM is imperative. To facilitate the analysis, the authors propose an approximate distribution of the CEU numbers with a flexible CEU definition in a single‐tier irregular network. With this distribution, the upper bound of the success probability of the typical CEU using the precoding‐based IM is analysed. Also, a lower bound of the success probability of the typical CCU is given. Moreover, the impact of the cell‐edge area on the success probability of both the CCU and CEU is discussed. It is found that the success probability of both the CCU and CEU decreases with the enlarged cell‐edge area in the case of the high density of users and small density of base stations. Nevertheless, the tendency of the success probability versus the cell‐edge area becomes diverse in the dense network or sparse user scenario.

The handoff rate under base stations (BSs) cooperation for the user's two transitions in ultra‐dense network (UDN) is analysed in this study. Frequent handoffs in UDN cause the degradation of user experience, which should be considered for UDN deployment. The determination of cooperation area to prevent the handoff of the first transition (from the origin to the first destination) is investigated and an approximate form that is convenient for practical application is given out. The handoff rate of the second transition (from the first destination to the second) is then studied with the BSs cooperation. Some special cases, where the mobility angle is set at some fixed values are also investigated. It is shown that the handoff rate is significantly affected by both the direction and the length of the user's transition. Moreover, the correlation between the two transitions does impact on the performance of handoff rate under the BSs cooperation. Numerical results are finally presented to verify the authors’ analysis.

Due to the complicated fading environment of distributed multiple-input multiple-output (d-MIMO) systems, the closed-form expression of cell average spectral efficiency (CASE) is in general difficult to be obtained, not to mention the three-dimension model. Hence, by assuming appropriate number of antennas configured on the remote access unit (RAU) of d-MIMO system, we firstly derive out a simple approximate expression of spectral efficiency with fixed pathloss according to the central limit theorem. To be more realistic, the closed-form of CASE at different locations of the target cell, under three-dimensional model, i.e., with considering the height of the RAU, is then given out. The theoretical and simulation results reveal that the CASE of d-MIMO system is bounded by the density and the height of RAU, and the CASE is robust to the changes of the user's location except for the cell-edge. Further, about 50% penalty of CASE from the cell-center to the cell-edge can be found. Moreover, the analytical results fit the simulations well, which verifies our analysis.

The Quality of Service (QoS) requirement of Random Access Procedure (RAP) emphasizes on success ratio and access delay in TD-LTE-A systems. In some applications like urgent communications, User Equipment (UE) will be labeled with different priority level. High priority UEs are critical to system implementation. In this paper, we proposed an Access Priority Level Based Random Access Scheme (APL-RA) in order to provide the access QoS guarantee for high priority UEs. The proposed scheme combines preamble split and backoff algorithm in access procedure to realize different priority level UEs random access for TD-LTE-A systems. The simulation results showed that the proposed scheme has better performance in high level priority UEs scenario, comparing with the conventional random access scheme. Also, it has little overhead and can be smoothly embedded in TD- LTE-A systems.

Cell range expansion (CRE) by pico eNodeB in heterogeneous networks can reduce the uplink interference effectively at the cost of the downlink interference increasing. It will lead to the system capacity decreasing apparently with a large range expansion bias. In this paper, we propose an asymmetric cell selection scheme for inter-cell interference coordination (ICIC) to solve the problems. The UEs in range expansion region will be designed to receive signal from macro eNodeBs and transmit signal to picos by using this scheme. Then, the downlink interference of UEs can be reduced effectively. The simulation results show that the proposed scheme can remarkably improve the system capacity.

Coordinated multiple point transmission and reception can reduce system interference and Distributed Antenna Systems can enlarge wireless coverage with lower transmitting power. These two techniques introduce the flexibility of wireless network architecture design for green communications. In this paper, we extend wireless network architecture with cooperative distributed antenna systems and derive the downlink ergodic capacity in three different kinds of wireless coverage areas. Then, analytical expressions of the downlink ergodic capacity are verified by system simulation. The research results prove that combination of cooperative and DAS can provide beneficial to green wireless communications systems.

Base station joint transmission techniques based on QR decomposition(QRD) and Tomlinson-Harashima precoding (THP) can improve the cell-edge user BER performance. But the large spreading of the subchannel gains may degrade the performance severely. In this paper, an equal rate power allocation (ERPA) strategy and a modified zero-forcing(ZF) THP (M-ZF-THP) technique are introduced which can equalize the subchannel quality and improve the performance of the downlink coordinated multi-point transmission and reception (CoMP). Both techniques are based on the theorem that optimal bit-error-rate performance of the multi-antenna system can be achieved when spatial pipes have the same quality. “Best-first” ordering algorithm is used in M-ZF-THP to enhance the performance. Simulation results show that our proposed schemes are superior to QRD and ZF-THP based algorithms.

OSIC (Order Successive Interference Cancellation) is a conventional MIMO detection algorithm for MIMO OFDM in LTE/LTE-A due to its significant performance gain over linear detection algorithm. But, it suffers from error diffusion, leading to performance decrease in low SNR. The tradeoff between complexity and detection performance is not optimal enough. In this paper, we proposed an adaptive MIMO detection approach for the suppression of error diffusion and reduction of complexity in LTE/LTE Advanced System (Uplink) based on the analysis of OSIC and its modification. This approach combines linear and nonlinear algorithm according to real-time SINR and the symbol error rate threshold. Simulation results show that the proposed algorithm suppresses the error diffusion and reduces the complexity successfully with the appropriate threshold.

Capacity dimensioning is one of the key procedures in wireless network planning. In this paper, the question of how to efficiently evaluate the capacity of wireless communications systems with a comprehensive consideration of adaptive modulation and coding (AMC), hybrid automatic repeat request (HARQ) and packet multimedia traffic source is examined. By investigating the joint effect of AMC and HARQ and modeling the packet multimedia traffic source as a discrete Markov modulated Poisson process (D-MMPP), a four-dimensional discrete time Markov chain (DTMC) is proposed to analyze the system behavior. Based on the stationary state distribution of this Markov chain, system capacity in terms of throughput, delay and packet loss rate is derived in closed-form expressions. Capacity dimensioning results are presented to illustrate the interdependence between system performance and system parameters. Computer simulations are also carried out to verify these results.

Capacity dimensioning is one of the key problems in wireless network planning. Analytical and simulation methods are usually used to pursue the accurate capacity dimensioning of wireless network. In this paper, an analytical capacity dimensioning method for WCDMA with high speed wireless link is proposed based on the analysis on relations among system performance and high speed wireless transmission technologies, such as H-ARQ, AMC and fast scheduling. It evaluates system capacity in closed-form expressions from link level and system level. Numerical results show that the proposed method can calculate link level and system level capacity for WCDMA system with HSDPA and HSUPA.

As a promising wireless network structure, distributed antenna system (DAS) has recently attracted some investigations for its application in future wireless communication systems. Previous work had studied the performance of DAS in indoor and outdoor cellular mobile communications system and investigated signal transmit schemes and power allocation methods for DAS performance analysis. In this paper, we discuss the optimization problem of downlink channel capacity of DAS and analyze the downlink channel capacity in cellular and Manhattan scenarios. Based on the characteristics of nonlinear variation of downlink ergodic capacity with increase of transmitting remote antenna unit (RAU) number, a capacity based RAU selection (CBRS) scheme which combines optimal capacity RAU selection and power allocation is proposed for effective system control of downlink transmission in DAS. Simulation results show that the CBRS control scheme can achieve better capacity performance compared with blanket transmission and selection diversity schemes.

The radio resource scheduling algorithms and power distribution strategies for multi-user MIMO mobile communications system are investigated. The performances of different power distribution strategies combined with diverse scheduling algorithms are compared for the consideration of system capacity and QoS guarantee. Numerical results show that the combination of dynamic scheduling and water-filling solution can enhance system capacity and reduce packet-discarding ratio.