Downlink Distributed Antenna Systems Research Articles

Performance Analysis of Distributed Antenna System for Downlink Ultrareliable Low-Latency Communications

In this article, we consider a distributed antenna system to enable the downlink ultrareliable and low-latency communications (URLLC) for the industrial Internet of Things. To satisfy the low latency, the short packet length is exploited and accordingly, the achievable rate under the finite blocklength codes is considered in the analysis of the packet loss probability in downlink URLLC distributed antenna system. Specifically, the packet loss probability is approximated as a sum of the channel OP and the finite blocklength coding error probability. By using a stochastic geometry approach, we analytically derive the packet loss probability in terms of the system parameters (i.e., the densities of the DA ports and the receiving sensor nodes, the number of receive antennas, and the packet size/duration, etc.), when the sensor nodes and the DA ports are randomly distributed in a given area. From the analytic results, we show how to optimize the short blocklength coding error probability to minimize the overall packet loss probability. Furthermore, we also derive the required DA port density to satisfy the packet loss probability constraint for a given distributed antenna system parameters, which gives us a useful insight into the design of downlink distributed antenna system for URLLC.

Energy Efficiency Optimization for D2D Communication Underlaying Distributed Antenna System

In this paper, the energy efficiency (EE) performance of a downlink distributed antenna system with device-to-device (D2D) underlay communication is investigated over a composite Nakagami fading channel. The optimal power allocation (PA) schemes are developed for improving the EE performance. Under the minimum rate constraint of cellular user (CU), the maximum power constraints of CU and D2D pair, an optimization problem for maximizing the system EE is formulated. The Karush–Kuhn–Tucker conditions are used to solve the optimization problem. Based on the 1-D search method and the bisection method, two schemes and corresponding algorithms are, respectively, proposed to obtain the optimal solutions of PA. For a given transmit power of D2D pair, the closed-form PA of remote antennas (RAs) and the number of active RAs are derived, which greatly simplifies the optimization. It is shown that the proposed two schemes can obtain the same EE performance, and the scheme with the bisection method has lower complexity than that with the 1-D search method. Computer simulation verifies the effectiveness of these two schemes, and superior EE performance can be achieved.

Low-Complexity Energy-Efficient Power Allocation With Buffer Constraint in HSR Communications

In this paper, we investigate the energy-efficient power allocation for downlink distributed antenna system (DAS) with buffer size constraint in high-speed railway (HSR) scenarios. We design the power allocation at different times for HSR communications, utilizing the characteristics of fixed moving path of trains. A key issue we discuss is the matching problem between the data arrival process and instantaneous wireless transmission process under the buffer size constraint. We formulate the energy-efficient power allocation problem with the requirement of buffer size as a non-convex optimization problem. By a parameterized transformation and an iterative algorithm, we derive the optimal solution at different time phases. Then, to reduce complexity of the multiple iterations, we present a low-complexity algorithm by analyzing the feasible region of the optimal solution. Simulation results demonstrate that the proposed power allocation schemes can achieve the optimal energy efficiency (EE) and avoid data overflow. Moreover, with a smaller number of iterations, the low-complexity algorithm can achieve the same EE performance as the optimal algorithm based on the bisection method.

Energy efficient joint energy cooperation and power allocation in multiuser distributed antenna systems with hybrid energy supply

This study investigates the joint power allocation and energy cooperation problem in a multiuser downlink distributed antenna system with hybrid energy supply. The authors focus on the energy efficiency (EE) maximization problem for three different types of precoding, zero-forcing (ZF), general beamforming method and conjugate-beamforming. For ZF precoding, they apply fractional programming and reform the optimization problem to a convex one. An iterative algorithm to deal with the fractional objective function is presented. Whereas the problem is non-convex for general beamforming with user interference, they take maximum ratio transmission as an example and adopt a set of transformation and approximation based on the difference of convex (DC) programming. Furthermore, for conjugate-beamforming, they first transform the quadratic signal to interference plus noise power ratio into a trackable form and then DC programming is applied. A two-loop algorithm for the general beamforming and conjugate-beamforming is presented with fractional programming in the inner loop and DC programming in the outer loop. Simulations show that the proposed algorithm improved EE significantly and indicate that energy cooperation can contribute to a higher EE. It also reveals that ZF achieves better EE with small noise variance while conjugate beamforming in high noise circumstance.

Secrecy Energy Efficiency Optimization in AN-Aided Distributed Antenna Systems With Energy Harvesting

In this paper, the artificial-noise (AN)-aided downlink distributed antenna system with simultaneous wireless information and power transfer is considered, in which the legitimate user uses the power-splitting (PS) scheme to simultaneously decode information and harvest energy. To prevent eavesdroppers from wiretapping the legitimate user, AN is transmitted with the confidential signal at the transmitter. The secrecy energy efficiency maximization (SEEM) problem is studied under the constraints of the minimum secrecy rate requirement, minimum required harvested energy, total radio frequency transmission power, and range of the PS ratio. Because of the coupling of variables, the formulated SEEM problem is non-convex and intractable. Then, a double-layer iterative optimization algorithm is proposed. The outer layer is a 1-D search algorithm for the introduced tight relaxation variable, whereas the inner one is based on the Dinkelbach method to address the fractional optimization problem. The closed-form expressions for the power of the transmitted confidential signal and AN power are further derived. The simulation results reveal the efficiency of the proposed algorithm and the advantage of AN in improving the system secrecy energy efficiency.

Capacity Analysis of Distributed Antenna Systems with Beamforming

Distributed antenna systems (DASs) can reduce the access distance, increase system capacity and improve system performance compared with conventional centralized multiple antenna systems. In this paper, the system capacity of downlink DAS with beamforming is investigated. The mathematical expression of system capacity is derived over the composite channel including Rayleigh fading, shadowing and path loss. At the same time, the interference from other APs is also considered for the studied AP. Numerical methods including Gauss-Hermite integral and composite Simpson’s rule are used to compute the system capacity of DAS under different MS distributions. Numerical results verify the precision of the mathematical analysis of system capacity by comparing Monte-Carlo simulation results. The results also show interference among APs shouldn’t be ignored when APs are close to each other or there are many APs.

Energy Efficient Power Allocation Scheme for Downlink Distributed Antenna System in Composite Fading Channel

In this paper, the energy efficiency (EE) of downlink distributed antenna system is investigated over composite fading channel including the path loss, shadow fading and Rayleigh fading, where both the static and dynamic circuit power consumptions are considered. Under the constraint of maximum transmit power of each remote antenna, our aim is to maximize the EE which is defined as the ratio of the transmission rate to the total consumed power to obtain effective power allocation (PA). According to the definition of EE, the optimized objective function is firstly formulated, and then utilizing the properties of fractional programming theory, the non-convex optimization problem in fractional form is transformed into an equivalent convex optimization problem in subtractive form, which makes the optimized problem become easy to handle. Based on this, using the Karush–Kuhn–Tucker conditions and mathematical calculation, an optimal energy efficient PA scheme is derived. Compared to the existing optimal schemes based on exhaustive search and the iterative calculation, this scheme may provide closed-form calculation of PA coefficients, and thus the computation complexity is lower. Moreover, it can obtain the EE performance identical to the existing optimal schemes. Simulation results verify the effectiveness of the proposed scheme.

Energy Efficient Power Allocation for Distributed Antenna System over Shadowed Nakagami Fading Channel

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 Nak- agami-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 math- ematical 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 infor- mation 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 devel- oped scheme.

Downlink Rate Analysis for Virtual-Cell Based Large-Scale Distributed Antenna Systems

Despite substantial rate gains achieved by coordinated transmission from a massive amount of geographically distributed antennas, the resulting computational cost and channel measurement overhead could be unaffordable for a large-scale distributed antenna system (DAS). A scalable signal processing framework is therefore highly desirable, which, as recently demonstrated in \cite{Dai_TWireless}, could be established based on the concept of virtual cell. In a virtual-cell based DAS, each user chooses a few closest base-station (BS) antennas to form its virtual cell, that is, its own serving BS antenna set. In this paper, we focus on a downlink DAS with a large number of users and BS antennas uniformly distributed in a certain area, and aim to study the effect of the virtual cell size on the average user rate. Specifically, by assuming that maximum ratio transmission (MRT) is adopted in each user's virtual cell, the achievable ergodic rate of each user is derived as an explicit function of the large-scale fading coefficients from all the users to their virtual cells, and an upper-bound of the average user rate is established, based on which a rule of thumb is developed for determining the optimal virtual cell size to maximize the average user rate. The analysis is further extended to consider multiple users grouped together and jointly served by their virtual cells using zero-forcing beamforming (ZFBF). In contrast to the no-grouping case where a small virtual cell size is preferred, it is shown that by grouping users with overlapped virtual cells, the average user rate can be significantly improved by increasing the virtual cell size, though at the cost of a higher signal processing complexity.

Downlink massive distributed antenna systems scheduling

This study investigates the scheduling problem for a single-cell downlink distributed antenna systems (DASs) with a massive number of remote access units (RAUs). To reduce signalling overhead under limited backhaul capacity, the authors make use of local long-term channel state information (CSI) in coordinated scheduling design. They first derive the ergodic rate expressions for both the single RAU transmission and the cooperative RAU transmission modes as functions of long-term CSI. Then greedy scheduling algorithms (GSAs) aiming for the maximum ergodic sum rate for the massive DAS using long-term CSI are proposed. To mitigate the intra-cell interference, a two-stage GSA with hybrid transmission mode is devised. Asymptotic analysis reveals that as the number of RAUs goes to infinity, intra-cell interference can be effectively mitigated. Simulation results verify the analysis and demonstrate that the two-stage GSA exhibits a higher ergodic sum-rate.

Bit Error Rate of SSTS for Downlink Distributed Antenna Systems in Multicell Environment

Based on maximum desired signal criterion, a novel single selection transmission scheme (SSTS) is proposed. In this case, the bit error rate (BER) of downlink distributed antenna systems in multicell environment is investigated. In particular, non-central limit theorem is adopted for SSTS to embody the effect of short-term fading on interference, where the variance of interference plus noise is considered as random variable with changeable variance influenced by the short-term fading. It is assumed that the channels suffer from independent identical Rayleigh fading together with propagation pathloss, and the closed-form expression of BER is derived. Extensive simulations are carried out to validate the theoretical derivation.

Downlink Performance of Distributed Antenna Systems in MIMO Composite Fading Channel

In this paper, the capacity and BER performance of downlink distributed antenna systems (DAS) with transmit antenna selection and multiple receive antennas are investigated in MIMO composite channel, where path loss, Rayleigh fading and lognormal shadowing are all considered. Based on the performance analysis, using the probability density function (PDF) of the effective SNR and numerical integrations, tightly-approximate closed-form expressions of ergodic capacity and average BER of DAS are derived, respectively. These expressions have more accuracy than the existing expressions, and can match the simulation well. Besides, the outage capacity of DAS is also analyzed, and a tightly-approximate closed-form expression of outage capacity probability is derived. Moreover, a practical iterative algorithm based on Newton’s method for finding the outage capacity is proposed. To avoid iterative calculation, another approximate closed-form outage capacity is also derived by utilizing the Gaussian distribution approximation. With these theoretical expressions, the downlink capacity and BER performance of DAS can be effectively evaluated. Simulation results show that the theoretical analysis is valid, and consistent with the corresponding simulation.

Optimal Beamforming Schemes and its Capacity Behavior for Downlink Distributed Antenna Systems

In this paper, we investigate the outage and ergodic capacity of downlink distributed antenna systems (DAS) where each distributed antenna unit (DAU) has multiple antennas with per-DAU power constraint. We first derive the optimal beamforming vector in a closed form by applying a matrix minor condition to relax the positive semi-definite constraint. We observe that our derived solution has a form of maximum ratio transmission per each DAU with full power. Based on the derived optimal beamforming, the outage and ergodic capacity under Rayleigh fading channels are analyzed. To this end, we show that a distribution of the received signal-to-noise ratio is characterized as a Gamma distribution by approximating a sum of non-identical independent Nakagami-m random variables as a single Nakagami-m random variable based on the moment matching method. Then, we present an accurate formula of the outage and ergodic capacity in a closed form which matches well with the simulation results. Furthermore, we derive an upper bound of an achievable average rate of DAS with limited feedback. We then propose a new feedback bit allocation algorithm to maximize the derived metric. Simulation results confirm the accuracy of the derived outage and ergodic capacity expressions and the efficiency of the proposed bit allocation method.

A single transmission selection scheme for downlink distributed antenna system in multicell environment

SUMMARYIn this paper, based on maximum signal‐to‐interference‐plus‐noise ratio criterion at the receiver, we propose a single transmission selection scheme for distributed antenna system and investigate the corresponding ergodic capacity together with outage probability in multicell environment. Assuming that the channels suffer from independent non‐identical Nakagami‐m fading with integer values of fading severity parameter m, we derive exact closed‐form expressions for the ergodic capacity and outage probability. Monte‐Carlo simulations are carried out to validate the theoretical analysis. Simulation results show that the ergodic capacity and outage probability of the proposed single transmission selection scheme outperform that of blanket transmission scheme. Copyright © 2013 John Wiley & Sons, Ltd.

Feedback Bit Allocation Schemes for Multi-User Distributed Antenna Systems

In this paper, we propose a feedback bit allocation algorithm for multi-user downlink distributed antenna systems with limited feedback. We consider a composite fading channel with small scale fadings and path loss, and assume the case where each user is served by only one distributed antenna (DA) port while each DA port can support any number of users. In order to efficiently determine bit allocation, we propose an iterative algorithm which minimizes an upper bound of a mean rate loss. Compared to conventional bit allocation methods, the proposed algorithm can be applied to more general system configurations. Simulation results show that our proposed algorithm offers a performance gain of 20% over an equal bit allocation scheme.

Optimal antenna placement in distributed antenna systems

To minimize the outage probability of the cell (OPC) in downlink distributed antenna systems with selection transmission, a complex-encoding genetic algorithm (GA) is proposed to find the optimal locations of the antenna elements (AEs). First, the outage probability at a fixed location in the cell is investigated. Next, an analytical expression of the OPC is derived, which is a function of the AE locations. Then the OPC is used as the objective function of the antenna placement optimization problem, and the complex-encoding GA is used to find the optimal AE locations in the cell. Numerical results show that the optimal AE locations are symmetric about the cell center, and the outage probability contours are also given with the optimal antenna placement. The algorithm has a good convergence and can also be used to determine the number of AEs which should be installed in order to satisfy the certain OPC value. Lastly, verification of the OPC's analytical expression is carried out by Monte Carlo simulations. The OPC with optimal AE locations is about 10% lower than the values with completely random located AEs.

Antenna Placement Optimization for Distributed Antenna Systems

In this paper, we propose new algorithms to determine the antenna location for downlink distributed antenna systems (DASs) in single-cell and two-cell environments. We consider the composite fading channel which includes small and large scale fadings. First, for the single-cell DAS, we formulate the optimization problem of distributed antenna (DA) port locations by maximizing the lower bound of the expected signal to noise ratio (SNR). In comparison to the conventional algorithm based on the squared distance criterion which requires an iterative method, our problem generates a closed form solution. Next, for the two-cell DAS, we propose a gradient ascent algorithm which determines the optimum DA locations by maximizing the lower bound of the expected signal to leakage ratio (SLR). In our work, we consider selection transmission, maximal ratio transmission and zero-forcing beamforming (ZFBF) under sum power constraint and study equal gain transmission and scaled ZFBF under per-antenna power constraint. Simulation results show that our proposed algorithms based on both the SNR and the SLR criteria offer a capacity gain over the conventional centralized antenna systems.

Capacity analysis of distributed antenna systems in MIMO Nakagami fading multicell environment

In this paper, the downlink capacity analysis of distributed antenna systems (DAS) with multiple receive antennas in Nakagami-m fading multicell environment is presented. According to the performance analysis, and using mathematical manipulation, we derive the probability density function (PDF) of the effective signal to interference plus noise ratio of the system. Based on the obtained PDF, an exact closed-form expression of DAS capacity is derived. This expression includes the existing capacity expression as a special case, and avoids the error in the latter. Thus, it can provide good theoretical performance evaluation for downlink DAS. Computer simulation shows that the theoretical analysis is in good agreement with simulation result. Moreover, the increase of receive antenna and/or Nakagami fading parameter m can improve the capacity effectively.

Energy Efficiency and Spectral Efficiency Tradeoff in Downlink Distributed Antenna Systems

This letter investigates the tradeoff between energy efficiency (EE) and spectral efficiency (SE) in downlink multiuser distributed antenna systems (DAS). Given the SE requirement and maximum power limit, a constrained optimization problem is formulated to maximize EE. Because of the multi-dimensional and non-convex nature of the problem, we first transform the multicriteria optimization problem with high complexity into a simpler single objective optimization problem. Then a novel power allocation algorithm is proposed to achieve maximum EE. Simulation results demonstrate the effectiveness of the proposed scheme as well as illustrate the fundamental tradeoff between energy efficient and spectral efficient transmission in downlink multiuser DAS.

Transmission Schemes Based on Sum Rate Analysis in Distributed Antenna Systems

In this paper, we study single cell multi-user downlink distributed antenna systems (DAS) where antenna ports are geographically separated in a cell. First, we derive an expression of the ergodic sum rate for the DAS in the presence of pathloss. Then, we propose a transmission selection scheme based on the derived expressions which does not require channel state information at the transmitter. Utilizing the knowledge of distance information from a user to each distributed antenna (DA) port, we consider the optimization of pairings of DA ports and users to maximize the system performance. Based on the ergodic sum rate expressions, the proposed scheme chooses the best mode maximizing the ergodic sum rate among mode candidates. In our proposed scheme, the number of mode candidates are greatly reduced compared to that of ideal mode selection. In addition, we analyze the signal to noise ratio cross-over point for different modes using the sum rate expressions. Through Monte Carlo simulations, we show the accuracy of our derivations for the ergodic sum rate. Moreover, simulation results with the pathloss modeling confirm that the proposed scheme produces the average sum rate identical to the ideal mode selection with significantly reduced candidates.