Performance Analysis of WLAN Medium Access Control Protocols in Simulcast Radio-Over-Fiber-Based Distributed Antenna Systems

The performance of three wireless local-area network(WLAN) media access control(MAC) protocols is investigated and compared in the context of simulcast radioover-fiber-based distributed antenna systems(RoF-DASs) where multiple remote antenna units(RAUs) are connected to one access point(AP) with different-length fiber links.The three WLAN MAC protocols under investigation are distributed coordination function(DCF) in basic access mode,DCF in request/clear to send(RTS/CTS) exchange mode,and point coordination function(PCF).In the analysis,the inter-RAU hidden nodes problems and fiber-length difference effect are both taken into account.Results show that adaptive PCF mechanism has better throughput performances than the other two DCF modes,especially when the inserted fiber length is short.

Forward Link Performance Analysis in CDMA Distributed Antenna Systems with Imperfect Channel Estimation

The impact of imperfect channel estimation on the forward-link performance inCDMA distributed antenna systems in multi-path fading environment is investigated. A detailedanalytical model based on a hybrid signal combining method is presented and exact outage probabilityexpression is derived. The investigation shows that the effect of imperfect channel estimatesvaries with system load. Furthermore, if simulcasting is employed, macro-diversity can decrease thesensitivity of forward-link to channel estimation errors and increase the forward-link outageperformance, which is contrary to the conclusion drawn based on the ideal channel estimationassumption.

Transmit Antenna Selection with Power and Rate Allocation for Spatial Multiplexing in Distributed Antenna Systems

High spectral efficiency distributed antenna systems （DAS） require vertical Bell-Labs layered space-time （V-BLAST） like spatial multiplexing schemes. However, unlike normal point-to-point multiple input multiple output （MIMO） channels, DAS channels have different large-scale fadings from different transmit antennas, thus making equal power and rate transmission that is feasible in MIMO channels unrealistic in DAS channels. This paper proposes a novel transmit antenna selection scheme with power and rate allocation. The scheme is based on large-scale fading （shadow fading and path loss） and is suitable for VBLAST structures with zero-forcing and successive interference cancellation （ZF-SIC） receivers, ensuring balanced average symbol error rate （SER） performance in each layer. On the receiver side, a fixed detection order is used, which is obtained in the transmit antenna selection process. Simulation results show that the proposed scheme gives good performance gains over equal power and rate transmission systems without antenna selection.

Energy Efficiency of Distributed Antenna Systems with D2D Communications Under Imperfect CSI

In this paper,we investigate the distributed antenna systems(DAS)based on device to device(DASD2D)communications under the imperfect channel state information(CSI).Our aim is to maximize the energy efficiency(EE)of the D2D users equipment(DUE)under the constraints of the maximum transmission power of D2D pairs and the quality of service(QoS)requirements of the cellular user equipment(CUE).The worst-case design is considered so that the QoS of the CUE can be guaranteed for every realization of the CSI error in the ellipsoid region.The EE objective function of the optimization problem is non-convex and non-linear,and thus this problem cannot be solved by the traditional optimization methods.To solve this problem,first we transform it to an EE maximization problem without uncertain parameters by exploiting the Markov and Cauchy-Schwartz inequality.Then using the fractional programming theory and difference of convex functions optimization method,the robust EE maximization algorithms based on the hard and soft protection method are developed to maximize the system’s EE performance,respectively.However,these two algorithms are designed at the cost of the reduced EE of the DUE.Therefore,in order to further improve the EE performance and make a trade-off between the EE performance and the robustness,the iterative update algorithms for the total power constraint and average interference constraint are developed to maximize the system’s EE performance,respectively.Simulation results demonstrate the effectiveness of the four proposed EE algorithms and illustrate the trade-off between the EE performance and robustness for the iterative update algorithms.

Cell-Free Massive MIMO for 6G Wireless Communication Networks

The recently commercialized fifth-generation(5G)wireless networks have achieved many improvements,including air interface enhancement,spectrum expansion,and network intensification by several key technologies,such as massive multiple-input multipleoutput(MIMO),millimeter-wave communications,and ultra-dense networking.Despite the deployment of 5G commercial systems,wireless communications is still facing many challenges to enable connected intelligence and a myriad of applications such as industrial Internet-ofthings,autonomous systems,brain-computer interfaces,digital twin,tactile Internet,etc.Therefore,it is urgent to start research on the sixth-generation(6G)wireless communication systems.Among the candidate technologies for 6G,cell-free massive MIMO,which combines the advantages of distributed systems and massive MIMO,is a promising solution to enhance the wireless transmission efficiency and provide better coverage.In this paper,we present a comprehensive study on cell-free massive MIMO for 6G wireless communication networks with a special focus on the signal processing perspective.Specifically,we introduce enabling physical layer technologies for cell-free massive MIMO,such as user association,pilot assignment,transmitter,and receiver design,as well as power control and allocation.Furthermore,some current and future research problems are described.