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The deployment of Distributed Antenna Systems (DAS) in poorly covered indoor areas has been a strategy to improve and extend radio-frequency (RF) coverage. However, this may imply a rise in the risk perception related to human exposure to electromagnetic fields (EMF), despite the existence of protection limits. Therefore, the objective of the current study is to analyze the overall impact of the installation of indoor DAS on the global human exposure. This analysis takes into account both downlink exposure, which includes exposure from outdoor base stations and indoor DAS, as well as uplink exposure induced by mobile phones. To this end, we carried out measurement campaigns in the premises of an organization and two subway stations in France, with the capability to selectively activate or deactivate the DAS antennas. The global exposure is evaluated using the ‘Exposure Index (EI)’ metric, which was developed as part of the European project LEXNET. The EI metric takes into consideration the exposure induced by both base stations and mobile devices, as well as the specific usage service (such as data or voice calls). The results have shown that deploying indoor DAS implies a reduction in the global EMF exposure while improving the quality of the cellular network connectivity. In addition to the impact of the usage service of mobile phones, the extent of EMF decrease is heavily influenced by the presence of additional RF sources. Specifically, significant reductions in EMF exposure have been observed in locations with minimal additional RF sources, whereas relatively lower reduction factors have been observed in locations with additional RF sources.

This study proposes an integrated framework of single-selection distributed antenna systems (DAS) and simultaneous wireless information and power transfer (SWIPT) with orthogonal multiple access (OMA), and analyzes the synergetic effects of SWIPT and DAS. To demonstrate the performance gains of the proposed SWIPT-enabled OMA with DAS, we jointly optimize power allocation for the OMA and power splitting (PS) ratio for energy harvesting of SWIPT with three different optimization goals: sum-rate maximization, user fairness, and energy efficiency. Although all of the above optimization problems are non-convex, the closed-form solutions of the problems maximizing the sum-rate and fairness are presented. Owing to difficult analytical tractability of the problem maximizing the energy efficiency, the problem is divided into three subproblems: power allocation for the base station (BS), power allocation for radio remote unit (RRU), and PS ratio assignment. Then, an iterative algorithm is presented to provide the energy-efficient SWIPT-enabled OMA with DAS. Theoretical findings are validated by numerical results, which show that the framework of applying DAS to SWIPT-OMA improves data rates and energy efficiency compared to SWIPT-OMA without DAS, while satisfying the minimum rate and harvested energy requirements. [ABSTRACT FROM AUTHOR]

Device-to-Device (D2D) communication is a potential technology to improve the spectral and energy efficiency (EE) of communication networks. In this paper, we study energy-efficient power allocation (PA) schemes in uplink distributed antenna system (DAS) with device-to-device underlay communication. Our goal is to maximize the total EE of all D2D pairs while guaranteeing the data rate and transmit power requirements of the cellular user and D2D links. To solve this non-convex constrained optimization problem, we propose an energy-efficient near-optimal PA algorithm based on the concave-convex procedure and fractional programming theory. This near-optimal algorithm can achieve the EE performance close to the optimal exhaustive search. To reduce the complexity, we furthermore present an efficient sub-optimal algorithm with the antenna selection method which can obtain the closed-form power allocation expressions. Simulation results demonstrate the significant EE performance of our proposed PA schemes.

Device-to-Device (D2D) communication is a potential technology to improve the spectral and energy efficiency (EE) of communication networks. In this paper, we study energy-efficient power allocation (PA) schemes in uplink distributed antenna system (DAS) with device-todevice underlay communication. Our goal is to maximize the total EE of all D2D pairs while guaranteeing the data rate and transmit power requirements of the cellular user and D2D links. To solve this non-convex constrained optimization problem, we propose an energy-efficient nearoptimal PA algorithm based on the concave-convex procedure and fractional programming theory. This near-optimal algorithm can achieve the EE performance close to the optimal exhaustive search. To reduce the complexity, we furthermore present an efficient sub-optimal algorithm with the antenna selection method which can obtain the closed-form power allocation expressions. Simulation results demonstrate the significant EE performance of our proposed PA schemes. [ABSTRACT FROM AUTHOR]

We develop two distributed downlink resource allocation algorithms for user-centric, cell-free, spatially-distributed, multiple-input multiple-output (MIMO) networks. In such networks, each user is served by a subset of nearby transmitters that we call distributed units or DUs. The operation of the DUs in a region is controlled by a central unit (CU). Our first scheme is implemented at the DUs, while the second is implemented at the CUs controlling these DUs. We define a hybrid quality of service metric that enables distributed optimization of system resources in a proportional fair manner. Specifically, each of our algorithms performs user scheduling, beamforming, and power control while accounting for channel estimation errors. Importantly, our algorithm does not require information exchange amongst DUs (CUs) for the DU-distributed (CU-distributed) system, while also smoothly converging. Our results show that our CU-distributed system provides 1.3- to 1.8-fold network throughput compared to the DU-distributed system, with minor increases in complexity and front-haul load - and substantial gains over benchmark schemes like local zero-forcing. We also analyze the trade-offs provided by the CU-distributed system, hence highlighting the significance of deploying multiple CUs in user-centric cell-free networks. [ABSTRACT FROM AUTHOR]

To attain automation across different applications, industries are beginning to leverage advancements in wireless communication technologies. A "one-size-fits-all" solution cannot be applied since wireless technologies are selected according to application needs, quality of service requirements, and economic restrictions. To balance the trade-off between technical and economic requirements, a multi-band heterogeneous wireless network architecture is presented and discussed in this paper. Wireless local area network (WLAN) and distributed antenna system (DAS) with Long Term Evolution (LTE) are considered as the backbone for the multi-band heterogeneous network into which other wireless technologies can be integrated. The technical and economic feasibility of the network are evaluated through a techno-economic analysis (TEA). The economic feasibility of the proposed network is measured in terms of net present value while the technical feasibility is measured in terms of network throughput and latency. Finally, network performance for DAS with LTE and WLAN are verified using an NS3 simulator for machine-to-machine, real-time video, and high-definition video data transmissions. The TEA analysis showed that the number of DAS units required to achieve technical feasibility is less than WLAN units, but the overall cost of DAS units are higher compared to WLAN units, even without taking into consideration industrial, scientific, and medical band technologies. [ABSTRACT FROM AUTHOR]

Copyright of Journal of South China University of Technology (Natural Science Edition) is the property of South China University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, we proposes a joint energy-efficient optimal resource allocation algorithm in multicell large-scale distributed antenna system with full-duplex (FD) radio remote heads (RRHs), which enable simultaneous uplink and downlink communications. To maximize the energy efficiency (EE) of the network, a non-convex optimization problem is formulated subject to circuit power consumption, minimum data rate requirements, and a maximum allowed transmit power per RRH. By exploiting the Dinkelbach algorithm, the non-convex optimization problem is transformed into an equivalent optimization problem in subtractive form. An iterative optimization algorithm is proposed to solve the problem by separately implementing antenna selection with user scheduling and power allocation. To address this significant computational complexity, a norm-based joint antenna and user selection algorithm that uses Tabu Search is proposed to select optimum antennas and users for transmission. A Lagrangian dual decomposition method is utilized to derive a power allocation strategy that can run independently in each cell. Simulation results demonstrate that the proposed algorithm can achieve its maximum EE within several iterations. They also show that incrementing the number of antennas or users does not necessarily yield a higher EE. In addition, regardless of the number of selected antennas or users, the proposed iterative algorithm improves the performance of the traditional norm-based algorithm and simplified cloud radio access network based energy efficient power allocation scheme (S-CEEPA). As a result, the proposed algorithm achieves efficient EE in FD system with imperfect CSI and has superior performance over convectional FD and half-duplex baseline algorithms. [ABSTRACT FROM AUTHOR]

We consider the analysis and design of distributed wireless networks wherein remote radio heads (RRHs) coordinate transmissions to serve multiple users on the same resource block (RB). Specifically, we analyze two possible multiple-input multiple-output wireless fronthaul solutions: multicast and zero forcing (ZF) beamforming. We develop a statistical model for the fronthaul rate and, coupled with an analysis of the user access rate, we optimize the placement of the RRHs. This model allows us to formulate the location optimization problem with a statistical constraint on fronthaul outage. Our results are cautionary, showing that the fronthaul requires considerable bandwidth to enable joint service to users. This requirement can be relaxed by serving a low number of users on the same RB. Additionally, we show that, with a fixed number of antennas, for the multicast fronthaul, it is prudent to concentrate these antennas on a few RRHs. However, for the ZF beamforming fronthaul, it is better to distribute the antennas on more RRHs. For the parameters chosen, using a ZF beamforming fronthaul improves the typical access rate by approximately 8% compared to multicast. Crucially, our work quantifies the effect of these fronthaul solutions and provides an effective tool for the design of distributed networks. [ABSTRACT FROM AUTHOR]

The safety of vulnerable road users is paramount, particularly as we move towards the widespread adoption of autonomous and self-driving vehicles. In this study, we investigate the use of a six-element distributed antenna system (DAS), operating at 5.8 GHz and mounted on the exterior (i.e., roof and wing mirrors) of an automobile, to enhance signal reliability for pedestrian-to-vehicle (P2V) communications. Due to its low complexity and ease of implementation, we consider the use of a switch-and-examine combining with post-examining selection (SECps) scheme to combine the signal received by the DAS. During our experiments, a pedestrian wearing a wireless device on their chest either stood stationary or walked by the side of a road. It was found that the overall signal reliability depends on not only the number, but also different groupings of the antennas which are selected. The goodness-of-fit results have shown that the temporal behavior of the diversity gain was adequately described by the Gaussian distribution. Building upon this, we also provide some useful insights into the antenna selection through the comparison of three different antenna selection mechanisms, namely per-sample random antenna selection, one-shot antenna selection and per-sample optimal antenna selection. [ABSTRACT FROM AUTHOR]

We propose and demonstrate a cascaded distributed antenna system (DAS) for efficiently extending the coverage of the mmWave-based 5G indoor network. For this, we exploit the radio-over-fiber (RoF) system based on the intermediate-frequency-over-fiber (IFoF) transmission technique that is enabled to add/drop the specific wavelength to the designated remote antenna unit (RAU) with using optical splitters and coarse wavelength division multiplexing (CWDM) filters. Moreover, the IFoF transceivers (TRx) perform the subcarrier multiplexing (SCM) in order to transmit 2 × 8 frequency allocation (FA) 5G signals per a single optical carrier, where each FA has 100 MHz bandwidth, leading each RAU to support 2 × 2 MIMO operation. Consequently, the cascaded structure allows for the adaptive and flexible configuration of the order of MIMO in accordance of the required data throughput at the specific indoor area. We introduce the cascaded IFoF link structure that can support up-to 13.5 dB optical power budget with following errorvector-magnitude (EVM) performance characterizations. And then we experimentally demonstrate the RoFbased cascaded DAS network, showing that more than 1 Gb/s total throughput can be achieved per a single antenna. Furthermore, we examine the use of avalanche photodiode (APD) to further increase the optical power budget (i.e., the coverage) based on experiment as well as simulation.

In this paper, the performance of uplink distributed antenna system (DAS) with Device-to-Device (D2D) communication is investigated over composite Rayleigh fading channels, and an energy-efficient power allocation (PA) scheme is developed for D2D communication underlaying DAS. Firstly, we establish the uplink DAS model with D2D communication. Then, the optimization problem for energy efficiency (EE) maximization subject to maximum total power constraint and the minimal rate constraints of cellular user and D2D user is formulated. Based on the pseudo-concave of objective function in optimization problem, we propose an optimal PA scheme with the bisection method to obtain the optimal solution of the optimization problem. The simulation results demonstrate the effectiveness of our proposed scheme. The proposed optimal PA scheme can achieve better EE performance than the conventional equal PA scheme, and the same EE as the PA scheme based on two-dimensional search method but with lower complexity. [ABSTRACT FROM AUTHOR]

Recently, a novel network architecture for a distributed antenna system with interlaced clustering has been proposed to mitigate the cell-edge problem. Under this network architecture, we propose a more practical implementation for ultradensely deployed remote antenna units (RAUs) with large numbers of users. Furthermore, we focus on the user selection (USC) and sparse beamforming technologies to optimize the weighted sum rate (WSR) with both backhaul and power constraints. First, we divide each cluster pattern (CP) into several adaptive cells, where RAUs are connected to a central processor via finite-capacity backhaul links. Aiming at reducing the computational complexity for large numbers of users and RAUs, we solve the original problem with two steps. In the first stage, we propose an efficient USC algorithm to find the largest user subset that satisfies the quality of service requirement. In the second stage, we adopt a CP-based weighted sum minimum mean square error algorithm to optimize the WSR problem for the selected users in the previous stage. Moreover, two decomposition algorithms, named primal decomposition and dual decomposition, are exploited to further reduce the computational complexity. Furthermore, based on the adaptive cells, we provide a low-complexity alternating optimization method for sparse beamforming. Finally, simulation results show that the proposed algorithms can achieve a significant performance gain on edge-user rates without losing much performance gain. At the same time, the backhaul information exchange is largely reduced, and approximately 90% of the RAUs consumes less than 66.7% of backhaul for each RAU.

Full-duplex (FD) distributed antenna system (DAS) can take advantage of both FD and DAS to dramatically improve system capacity. The challenges of designing such a system are self-interference at the base station (BS) and multiuser interference, as well as hardware cost, computational complexity and signaling overhead, especially for dense antenna deployments. To address these problems mentioned above, in this paper, we investigate an antenna selection strategy at the BS for FD DAS including FD-capable BS antennas and half-duplex (HD) users. In particular, we separately optimize the receive and transmit antenna selection problems to maximize the achievable sum rate. To reduce the computational complexity and signaling overhead, each user is restricted to selecting only the BS antennas in its virtual cell. The optimization problem is a nonconvex integer programming problem, for which it is difficult to find a globally optimal solution. Using variable relaxation and successive convex approximation, we present an iterative antenna selection algorithm based on difference of convex functions (D.C.) programming to obtain a suboptimal solution. The simulation results demonstrate that the proposed antenna selection algorithm can provide significant performance gain over various reference algorithms.

In this paper, we consider the combination of machine learning (ML) and wireless communication. We design a machine learning generated clusters model in a distributed antenna system (DAS), which is constructed by two different ML clustering algorithms, i.e., k-means algorithm and Gaussian mixture model-based (GMM) algorithm. Under the communication scenario of DAS with ML generated clusters model, we investigate two different power allocation optimization problems with the interference of maximizing spectral efficiency (SE) and energy efficiency (EE) in DAS, respectively. We compare the SE and EE of DAS with ML generated clusters model and the conventional model. The simulation results verify the effectiveness of DAS with ML generated clusters model, which can obtain the much better performance of SE and EE compared with the conventional communication model in DAS.

In this paper, we intend to study the energy efficiency (EE) optimization for a simultaneous wireless information and power transfer (SWIPT)-based distributed antenna system (DAS). Firstly, a DAS-SWIPT model is formulated, whose goal is to maximize the EE of the system. Next, we propose an optimal resource allocation method by means of the Karush-Kuhn-Tucker condition as well as an ergodic method. Considering the complexity of the ergodic method, a suboptimal scheme with lower complexity is proposed by using an antenna selection scheme. Numerical results illustrate that our suboptimal method is able to achieve satisfactory performance of EE similar to an optimal one while reducing the calculation complexity. [ABSTRACT FROM AUTHOR]

In this letter, we aim to optimize the placement of base station (BS) antennas for maximizing the average ergodic sum capacity of a multi-user distributed antenna system (DAS). Different from previous studies where deterministic optimization approaches were usually taken, we formulate the BS antenna placement as a stochastic optimization problem, and propose a stochastic-gradient-descend-based algorithm to effectively solve it. Simulation results demonstrate that the proposed algorithm converges fast and provides significant gains in average ergodic sum capacity over the existing representative BS antenna placement schemes. [ABSTRACT FROM AUTHOR]

In this paper, we propose an energy-efficient resource allocation algorithm in the downlink of a multicell large-scale distributed antenna system. A non-convex optimization problem is formulated to maximize the energy efficiency (EE) of the entire network. The optimization problem considers the circuit power consumption, the minimum data rate requirements, and the maximum allowed transmit power per remote radio head. The optimization problem is transformed into an equivalent optimization problem in the subtractive form using the Dinkelbach method. An iterative algorithm for the optimization solution is proposed in which antenna selection with user scheduling and power allocation are implemented separately. To tackle this significant computational complexity, a norm-based joint antenna and the user selection algorithm that uses Tabu Search are proposed to select optimum antennas and users for transmission. Next, a Lagrangian dual decomposition method is adopted to derive a power allocation strategy that can run independently in each cell. Simulation results show that the proposed algorithm can achieve its maximum EE in several iterations, and that increasing the number of antennas or users does not necessarily result in a higher EE. In addition, the proposed iterative scheme is always able to achieve a better performance than the traditional norm-based algorithm and the simplified cloud radio access network based energy efficient power allocation scheme, no matter how many antennas or users are selected. [ABSTRACT FROM AUTHOR]

Copyright of Journal of South China Normal University (Natural Science Edition) / Huanan Shifan Daxue Xuebao (Ziran Kexue Ban) is the property of Journal of South China Normal University (Natural Science Edition) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, we considered a distributed antenna system (DAS) to expand the coverage of VHF maritime communication systems and analyzed its performances. To reflect the geometrical distributed antenna port placements along the coastline, we considered a linear antenna layout. By deriving the lower bounds of the expected signal-to-noise ratio (SNR), we analyzed the SNR performances for both single-ship and multiple-ship transmission schemes. Next, based on the analytical results, we present design guidelines to implement the DAS based VHF maritime communication system. From the simulation results, the coverage expansion effect of the DAS was verified by the increased expected SNR. In addition, we confirmed that the system design parameters could be found from simple numerical calculations. [ABSTRACT FROM AUTHOR]

The fifth generation (5G) cellular network is expected to include the millimeter wave spectrum, to increase base station density, and to employ higher-order multiple-antenna technologies. The centralized radio access network architectures combined with radio-over-fiber (RoF) links can be the key enabler to improve fronthaul networks. The sigma-delta modulated signal over fiber (SDoF) architecture has been proposed as a solution leveraging the benefits of both digitized and analog RoF. This work proposes a novel distributed antenna system using sigma-delta modulated intermediate-frequency signal over fiber (SDIFoF) links. The system has an adequately good optical bit-rate efficiency and high flexibility to switch between different carrier frequencies. The SDIFoF link transmits a signal centered at a 2.5 GHz intermediate frequency over a 100 m multi-mode fiber and the signal is up-converted to the radio frequency (24–29 GHz) at the remote radio unit. An average error vector magnitude (EVM) of 6.40% (−23.88 dB) is achieved over different carrier frequencies when transmitting a 300 MHz-bandwidth 64-QAM OFDM signal. The system performance is demonstrated by a 2 × 1 multiple-input single-output system transmitting 160 MHz-bandwidth 64-QAM OFDM signals centered at 25 GHz. Owing to transmit diversity, an average gain of 1.12 dB in EVM is observed. This work also evaluates the performance degradation caused by asynchronous phase noise between remote radio units. The performance shows that the proposed approach is a competitive solution for the 5G downlink fronthaul network for frequency bands above 24 GHz. [ABSTRACT FROM AUTHOR]

This paper presents multi-user (MU) linear precoding methods for massively distributed antenna system (DAS) with polarized antennas, where mobile stations (MSs) are spatially grouped and the distributed antenna (DA) ports with a polarized-antenna are connected to a central base station (BS). While the (slowly-changing) long-term channel state information (CSI) (i.e., large scale fading and polarization) can be accurately estimated at the transmit-side, the short-term CSI (instantaneous channel response) is available at the transmit-side with quantization errors due to the limited feedback. Accordingly, the utilization of a large number of DA ports is not always beneficial due to the imperfect short-term CSI at the transmitter (CSIT). In this paper, we first derive the asymptotic achievable rate and signal-to-leakage-and-noise ratio (SLNR) for the MU linear precoding in the massive DAS, which depends on the long-term CSIT and the number of feedback bits, and propose a transmit DA port selection based on the asymptotic SLNR performance. Here, the number of selected DA ports can be also optimized according to the long-term CSIT and the number of feedback bits. Furthermore, we also propose a polarization selection strategy at each DA port (equipped with multi-polarized antennas) so as to exploit the polarization diversity. Through the simulation, we confirm that the proposed MU precoding with the DA port selection outperforms the conventional precoding schemes for the DAS and, furthermore, the proposed polarization selection strategy achieves a rate performance comparable to the DAS with a (single polarized antenna) node density twice as large. [ABSTRACT FROM AUTHOR]

A systematic way is proposed to fully characterize omnidirectional antennas by measuring their complex normalized effective height (CNEH). Usually, antennas are utilized to convert the voltage waves in a waveguide into the vectorial electromagnetic fields in free space and vice versa; however, this conversion relationship cannot be fully expressed with the traditional antenna parameters, e.g., the antenna gain, and so on, because they are not vectorial and possess no phase information. CNEH is a versatile parameter, which can reveal accurately the relationship between the voltage waves in waveguides and the radiated fields in free space. The feature makes it particularly useful for the distributed antenna system or multi-probe array system. The measurement of a CNEH usually uses the far-field method; however, it is a challenge for omnidirectional antennas. We propose a novel method to precisely generate CNEHs based on the broadband calculable antennas. Experimental results show that the difference in transmission coefficient between a pair of calculate dipole antennas resonating at 90 MHz is less than 0.2 dB for amplitude and 2° for phase from 20 to 330 MHz; equivalently, the difference in CNEHs generated from calculable dipole antennas (CDAs) between measurements and calculations will be half of the above results. The key points for CDAs to achieve the superior performance are briefly introduced. Eventually, a way to calibrate the CNEHs of any omnidirectional antennas is illustrated by experiments. Some common antenna parameters are calculated from the CNEH; thus, we present a method to get many antenna parameters by one measurement. [ABSTRACT FROM AUTHOR]

In this paper, a power allocation (PA) scheme aiming at maximizing energy efficiency (EE) with minimum rate constraint is proposed for a distributed antenna system (DAS) in composite fading channels. The EE for DAS with dynamic circuit power consumption is first presented. Then, maximizing the EE under the maximum power constraint of each remote antenna (RA) and the minimum rate requirement of the system, an optimization problem is formulated. Based on this, two cases of the optimization problem are, respectively, analyzed. The first case is that the rate equals the given minimum value, and an effective algorithm is proposed to get the number of active antennas and the corresponding power allocation for this case. The second case is that the rate is greater than its given minimum value. For that case, we present an efficient algorithm, where the optimal number of active RAs is firstly derived, and then an optimal PA in closed form is achieved by using the Lambert function. By combining these two cases, an optimal PA scheme for the EE optimization problem is proposed, and it can include some existing optimal schemes as special cases. Simulation result shows that the proposed PA scheme is effective and applicable for different fading channels. Moreover, it can obtain the superior EE performance and meet the required constraints.

This paper presents an internet of things (IoTs) enabled smart meter with energy-efficient simultaneous wireless information and power transfer (SWIPT) for the wireless powered smart grid communication network. The SWIPT technique with energy harvesting (EH) is an attractive solution for prolonging the battery life of ultra-low power devices. The motivation for energy efficiency (EE) maximization is to increase the efficient use of energy and improve the battery life of the IoT devices embedded in smart meter. In the system model, the smart meter is equipped with an IoT device, which implements the SWIPT technique in power splitting (PS) mode. This paper aims at the EE maximization and considers the orthogonal frequency division multiplexing distributed antenna system (OFDM-DAS) for the smart meters in the downlink with IoT enabled PS-SWIPT system. The EE maximization is a nonlinear and non-convex optimization problem. We propose an optimal power allocation algorithm for the non-convex EE maximization problem by the Lagrange method and proportional fairness to optimal power allocation among smart meters. The proposed algorithm shows a clear advantage, where total power consumption is considered in the EE maximization with energy constraints. Furthermore, EE vs. spectral efficiency (SE) tradeoff is investigated. The results of our algorithm reveal that EE improves with EH requirements.

In this paper, by maximizing the energy efficiency (EE), an optimal power allocation scheme is developed for downlink distributed antenna system (DAS). Different from conventional optimal power allocation schemes that need iterative calculation, the developed scheme can provide closed-form power allocation and no iteration is required. Based on the definition of EE, the optimized objective function is firstly formulated, and then a computationally efficient algorithm is proposed to obtain the optimal number of active remote antennas and the corresponding power allocation. Using the optimal number, the multidimensional solution for the optimized function is transformed into searching one-dimensional solution. As a result, closed-form expression of power allocation coefficients is attained. Numerical results verify the effectiveness of the proposed scheme. The scheme can obtain the same EE as the conventional optimal scheme but with lower complexity, and it has more accuracy than the existing low-complexity scheme.

To achieve the massive device connectivity and high data rate demanded by 5G, wireless transmission with wider signal bandwidths and higher-order multiple-input multiple-output (MIMO) is inevitable. This work demonstrates a possible function split option for the next generation fronthaul interface (NGFI). The proof-of-concept downlink architecture consists of real-time sigma-delta modulated signal over fiber (SDoF) links in combination with distributed multi-user (MU) MIMO transmission. The setup is fully implemented using off-the-shelf and in-house developed components. A single SDoF link achieves an error vector magnitude (EVM) of 3.14% for a 163.84 MHz-bandwidth 256-QAM OFDM signal (958.64 Mbps) with a carrier frequency around 3.5 GHz transmitted over 100 m OM4 multi-mode fiber at 850 nm using a commercial QSFP module. The centralized architecture of the proposed setup introduces no frequency asynchronism among remote radio units. For most cases, the 2 × 2 MU-MIMO transmission has little performance degradation compared to SISO, 0.8 dB EVM degradation for 40.96 MHz-bandwidth signals and 1.4 dB for 163.84 MHz-bandwidth on average, implying that the wireless spectral efficiency almost doubles by exploiting spatial multiplexing. A 1.4 Gbps data rate (720 Mbps per user, 163.84 MHz-bandwidth, 64-QAM) is reached with an average EVM of 6.66%. The performance shows that this approach is feasible for the high-capacity hot-spot scenario. [ABSTRACT FROM AUTHOR]

In this study, we report the successful demonstration of an intermediate-frequency-over-fiber (IFoF)–based radio access network (RAN) for 28 GHz millimeter-wave (mmWave)-based 5G mobile communication. In order to increase the network coverage of the mmWave-based 5G networks, we propose a distributed antenna system (DAS) that uses the IFoF technology. An IFoF-based DAS with 2 × 2 multiple-input multiple-output (MIMO) configuration was deployed in the PyeongChang area to provide 5G trial demonstration during the Winter Olympics. 5G trial services such as high-speed data transfer and autonomous vehicle driving were offered to the public through the IFoF-based DAS. A downlink throughput of ∼1 Gb/s and uplink throughput of ∼200 Mb/s were achieved in the DAS-deployed area. We also present an IFoF-based 5G mobile fronthaul that can overcome the bandwidth bottleneck in RANs. We performed real-time transmission of mmWave-based 5G wireless access networks using the IFoF-based mobile fronthaul. The real-time downlink throughput achieved per 5G terminal was approximately 9 Gb/s, when using a 4 × 4 MIMO configuration. An outdoor demonstration was performed to verify the technical feasibility of the 5G fronthaul based on IFoF technology. When moving the 5G terminal between remote radio heads at a speed less than 60 km/h, 5G mobile broadband services could be provided with real-time throughput more than 5 Gb/s. Thus, we confirmed that the IFoF technology was capable of supporting RANs for mmWave-based 5G networks and providing real-time multi-Gb mobile services. [ABSTRACT FROM AUTHOR]

We demonstrate 4 × 4 multiple-input and multiple-output (MIMO) supporting mmWave-based indoor 5G mobile network based on a distributed antenna system (DAS) that has over-the-air interface to receive the broadband wireless signal from, e.g., remote radio head (RRH) of mobile fronthaul. To realize the cost/bandwidth-efficient and low-latency-inducing indoor 5G DAS network, we exploit the radio-over-fiber (RoF) system that is based on the intermediate frequency-over-fiber (IFoF) technology. To be more specific, we make simultaneous use of wavelength- and frequency-division multiplexing in the IFoF link so as to transport 4 × 4 MIMO 5G signal of which the bandwidth is effectively 3.2 GHz (= 4 × 800 MHz, where each antenna deals with 800 MHz 5G signal). The 4 × 4 MIMO-supporting IFoF link has error vector magnitude (EVM) performance of <4.5% at all channels of downlink and uplink for up to 2 km. The whole RoF system, exploiting the IFoF link, mmWave frequency conversion module, and control /management plane, proves itself to meet the 3GPP-defined EVM requirement (i.e., 8%) at all channels. Based on the RoF system, we demonstrate the indoor 5G DAS network in conjunction with Korea Telecom 5G mobile network, i.e., 5G baseband unit and RRH, investigating the downlink and uplink throughputs. We achieve ∼4 Gb/s total throughput for end user, where the additional latency induced by the DAS network is only a few hundreds of nanoseconds other than the single mode fiber transmission delay. [ABSTRACT FROM AUTHOR]

This paper studies a distributed antenna system (DAS) network with radio frequency (RF) energy harvesting (EH) technology where the distributed antenna ports (DAPs) transmit energy and information to multiple users simultaneously. The time division multiple access (TDMA) protocol is adopted, so for each time slot is allowed to receive information, while the rest of the users harvest energy. In order to maximize the system energy efficiency (EE), subject to the EH requirements and data rate requirements of the users, the transmission time and power assignment are jointly optimized. In order to deal with this non-convex problem, based on Dinkelbach theory and the block-coordinate descent (BCD) scheme, an efficient algorithm is designed to obtain the global optimal solution. Then, simulation results are presented to show that the proposed method achieves much higher system EE compared with benchmark methods. With the increase of the user’s minimum information rate, the system EE decreases rapidly.

In this paper, the energy efficiency (EE) of downlink distributed antenna system (DAS) with multiple receive antennas is investigated over composite fading channel that takes the path loss, shadow fading and Nakagami-m fading into account. Our aim is to maximize EE which is defined as the ratio of the transmission rate to the total consumed power under the constraints of maximum transmit power of each remote antenna. According to the definition of EE and using the upper bound of average EE, the optimized objective function is provided. Based on this, utilizing Karush-Kuhn-Tucker (KKT) conditions and mathematical derivation, a suboptimal energy efficient power allocation (PA) scheme is developed, and closed-form PA coefficients are obtained. The developed scheme has the EE performance close to the existing optimal scheme. Moreover, it has relatively lower complexity than the existing scheme because only the statistic channel information and less iteration are required. Besides, it includes the scheme in composite Rayleigh channel as a special case. Simulation results show the effectiveness of the developed scheme.

In this paper, we study the location optimization problem of remote antenna units (RAUs) in generalized distributed antenna systems (GDASs). We propose a composite vector quantization (CVQ) algorithm that consists of unsupervised and supervised terms for RAU location optimization. We show that the CVQ can be used i) to minimize an upper bound to the cell-averaged SNR error for a desired/demanded location-specific SNR function, and ii) to maximize the cell-averaged effective SNR. The CVQ-DAS includes the standard VQ, and thus the well-known squared distance criterion (SDC) as a special case. Computer simulations confirm the findings and suggest that the proposed CVQ-DAS outperforms the SDC in terms of cell-averaged "effective SNR". [ABSTRACT FROM AUTHOR]