Downlink massive distributed antenna systems scheduling

Spectral efficiency and energy efficiency of distributed antenna systems with virtual cells

A two-stage downlink beamforming design is proposed for multicell multi-input single-output channels with limited backhaul capacity and local channel state information (CSI). The first stage is to maximize the signal-to-leakage-plus-noise ratio with local CSI. Each base station (BS) then calculates the corresponding channel gains and shares them with all other BSs, which typically requires low-rate backhaul signaling. Finally, all the BSs design their beamforming vectors in pursuit of increasing the sum-rate with the shared information. Simulation results show that the proposed scheme shows the sum-rate higher than that of the state-of-the-art scheme and even close to that of the scheme with global CSI even without vector channel information.

Over the last decade high data rate wireless transmission has gained considerable attention in hot spot areas, including high buildings. It has been demonstrated that distributed antenna systems (DASs) improve the performance of the indoor environment by providing spatial diversity and covering dead spots. In this paper, indoor wireless communications have been studied together with a femtocell based DAS. In this DAS, a femtocell managed by a central unit (CU) is deployed to cover several neighbouring floors, which compose a floor-bank. Since the radio spectrum becomes limited and expensive, the spectrum should be reused among different floor-banks. The performance of downlink DAS transmission is analysed in terms of bit error rate (BER) in the presence of co-channel interference from other floor-banks. Numerical results show that when decreasing the number of floors in a floor-bank, the BER performance degrades due to the strong co-channel interference. The number of floors in a floor-bank has a significant effect on the BER performance in high buildings.

In this paper, we propose an optimal scheme for a distributed antenna system (DAS) to maximize energy efficiency (EE) under a constraint of overall transmit power of each remote access unit (RAU). We exploit the multicriteria optimization method to systematically investigate the relationship between EE and spectral efficiency (SE). Using the weighted sum method, we first convert the multicriteria optimization function, which is extremely complex, into a simpler single objective optimization function. Then an optimal algorithm is developed to allocate the available power to tradeoff EE and SE effectively. Furthermore, we also illustrate the effectiveness of the proposed method and demonstrate there is a tradeoff between energy-efficient and spectral-efficient transmission through computer simulation of a downlink multiuser DAS.

The main focus of this paper is to investigate the downlink outage probability of the distributed antenna system (DAS) over shadowed Nakagami-m fading channels. In the analysis, by making use of the moment generating function (MGF), this paper first derives the probability density function (PDF) of the output signal to noise ratio (SNR) after maximal ratio combining (MRC) at the receiver. Further, an approximate analytical expression of outage probability is derived for the downlink of DAS with an antenna selective transmission scheme (ASTS). The numerical results show that the derived analytical expression can evaluate the system performance very accurately.

In this paper, we investigate the resource allocation scheme for orthogonal frequency division multiple access (OFDMA) full-duplex (FD) distributed antenna systems (DASs), in which both remote access units (RAUs) and users having the full-duplex capability. We aim to maximize the system spectral efficiency through jointly optimizing subcarrier assignment and power allocation, where users’ uplink/downlink quality of service requirements, per-user uplink/downlink transmit power constraints, and subcarrier reuse are considered. The user-centric virtual cell approach is adopted to reduce the computational and signaling overhead. Based on the successive convex approximation method and penalty factor, we propose an efficient overall optimization algorithm to tackle the non-convex optimization problem. Simulation results show that the proposed algorithm can achieve performance close to the exhaustive search algorithm, comparable to the hierarchical decomposition algorithm using the optimal subcarrier allocation scheme, and better than other benchmark algorithms. In addition, the proposed algorithm can guarantee fairness among users at a low cost of system spectral efficiency.

Energy efficiency(EE) has caught more and more attention in future wireless communications due to steadily rising energy costs and environmental concerns. In this paper, we propose an EE scheme with proportional fairness for the downlink multiuser distributed antenna systems (DAS). Our aim is to maximize EE, subject to constraints on overall transmit power of each remote access unit (RAU), bit-error rate (BER), and proportional data rates. We exploit multi-criteria optimization method to systematically investigate the relationship between EE and spectral efficiency (SE). Using the weighted sum method, we first convert the multi-criteria optimization problem, which is extremely complex, into a simpler single objective optimization problem. Then an optimal algorithm is developed to allocate the available power to balance the tradeoff between EE and SE. We also demonstrate the effectiveness of the proposed scheme and illustrate the fundamental tradeoff between energy- and spectral-efficient transmission through computer simulation.

To reduce the complexity and cost of remote access units (RAUs), colorless transport architecture is preferred in a wavelength-division multiplexing (WDM) system. The wavelength-reuse technique is commonly adopted to realize colorless RAUs. However, in traditional approaches, RAUs employ crystal-based Mach&#x2013;Zehnder modulators (MZMs) to modulate the distributed carriers. Hence, polarization tracking systems are necessary to align the polarization state of the distributed carriers with the MZM principal axis. This increases the cost of the RAUs. In this paper, a full-duplex millimeter-wave (MMW) radio-over-fiber (RoF) access architecture employing polarization-insensitive RAUs is proposed. In our proposed RAUs, the upstream signals are generated using polarization-orthogonal lights, and the performance of the upstream signals is independent of the polarization state of the MZM input lights. The proposed system is mathematically formulated and experimentally demonstrated. The 1.2-Gb/s quadrature phase-shift keying (QPSK) orthogonal frequency-division multiplexing (OFDM) downstream signal at the 60-GHz band and 5-Gb/s on&#x2013;off keying (OOK) polarization-insensitive upstream signal over a 15-km standard single-mode fiber (SSMF) are demonstrated. In our results, a polarization-insensitive RAU is successfully obtained. The power penalty resulting from the interference of downstream signal is about 0.4 and 0.6 dB with a bit error rate (BER) of <inline-formula> <tex-math notation="LaTeX">$10^{-9} $</tex-math></inline-formula> in back-to-back and 15-km fiber transmission, respectively.

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.

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.

We propose the Optimum Power Allocation (OPA) scheme for Distributed Antenna Systems(DAS) in the time-varying Rayleigh fading channel. Recently, the OPA schemes which uses the Channel State Information (CSI) including a small scale (fast) fading have been proposed. However, the channel is changing vary fast over time due to small scale fading, therefore Bit Error Rate (BER) increases. Because of this reason, we derive the OPA for minimizing BER in DAS, which only uses a large scale fading to CSI and excepts a small scale fading. The simulation results show that the proposed OPA achieves better BER performance than conventional OPA considering a small scale fading in time-varying Rayleigh fading channel, and also has similar performance in Rayleigh flat-fading environment. The BER performance of proposed OPA which derived in Rayleigh fading channel is similar to minimum BER of Ricean fading channel which has small Line-of-Sight (LOS).

Interference alignment (IA) is a promising technique for interference mitigation in multicell networks due to its ability to completely cancel the intercell interference through linear precoding and receive filtering. In small networks, the amount of required channel state information (CSI) is modest and IA is, therefore, typically applied jointly over all base stations. In large networks, where the channel coherence time is short in comparison to the time needed to obtain the required CSI, base station clustering must be applied however. We model such clustered multicell networks as a set of coalitions, where CSI acquisition and IA precoding are performed independently within each coalition. We develop a long-term throughput model, which includes both CSI acquisition overhead and the level of interference mitigation ability as a function of the coalition structure. Given the throughput model, we formulate a coalitional game where the involved base stations are the rational players. Allowing for individual deviations by the players, we formulate a distributed coalition formation algorithm with low complexity and low communication overhead that leads to an individually stable coalition structure. The dynamic clustering is performed using only long-term CSI, but we also provide a robust short-term precoding algorithm, which accounts for the intercoalition interference when spectrum sharing is applied between coalitions. Numerical simulations show that the distributed coalition formation is generally able to reach long-term sum throughputs within 10% of the global optimum.

We study the optimal transmission strategy of a multiple-input single-output wireless communication link. The receiver has perfect channel state information while the transmitter has only long-term channel state information in terms of the channel covariance matrix. It was recently shown that the optimal eigenvectors of the transmit covariance matrix correspond with the eigenvalues of the channel covariance matrix. However, the optimal eigenvalues are difficult to compute. We study the properties of these optimal capacity achieving eigenvalues, and present a necessary and sufficient condition for the optimal eigenvalues of the transmit covariance matrix. Furthermore, we develop a necessary and sufficient condition for achieving capacity when transmitting in all directions. We compare the capacity gain of an optimal diversity system with a system which works with beamforming, and we derive an upper bound. We answer the main questions regarding the system design using the developed results. Additionally, we show in which way the multiplexing gain can be computed in case the channel covariance matrix is given. We compute the maximum number of required parallel data streams, and we define a multiplexing function in order to obtain a measure for the available multiplexing gain. Furthermore, we show that the capacity gain is small considering the additional complexity at the receiver. We illustrate all results by numerical simulations.

Opportunistic packet scheduling optimization problem in orthogonal frequency division multiplexing (OFDM) distributed antenna systems (DAS) is investigated by this paper. Physical-layer channel state information (CSI) and wireless links' requirements for bit error rate are taken into account during problem formulation. The optimization aim is to minimize packet loss rate (PLR) subject to limited wireless resource, which is characterized by power, subcarrier, antenna et al. According to the characteristics of users' packet queues as well as CSI, the proposed algorithm adaptively allocates wireless resource to users to exploit as much spatial and multiuser diversity as possible. Simulation results show the proposed algorithm achieves the lowest PLR in all compared algorithms. Further more, the proposed circular DAS significantly outperforms co-located antenna systems (CAS) due to distributed antenna deployment.

A beamforming vector design based on a deep neural network (DNN) is proposed for multicell multi-input single-output channels with scalar information exchange and local channel state information (CSI). The beamforming vectors are designed making zero generating-interference to the selected interference-free users (IFUs). The set of IFUs is chosen by the DNN based on supervised learning where the inputs can be obtained with only local CSI and limited scalar information exchange. Simulation results show that the DNN is well-trained in estimating the unknown CSI from the inputs with only local CSI in multicell networks.