Efficient Uplink User Selection Algorithm in Distributed Antenna Systems

Capacity maximizing in massive MIMO with linear precoding for SSF and LSF channel with perfect CSI

Distributed antenna systems (DASs) are known to be effective to enhance coverage, spectral efficiency, and reliability in mobile communication systems. Because multiple antennas are physically separated in space, DASs benefit from both micro- and macro-diversity, which makes DASs significantly more robust compared to conventional co-located antenna systems in fading channels. However, when multiple antennas are not dispersed enough, there exists a certain degree of correlation in large-scale fading (shadowing), which degrades the macro-diversity gain. In practice, various measurements indicate a high degree of correlation of shadowing in DASs. However, most of the previous studies on DASs have not considered the correlated shadowing and its corresponding performance loss. Motivated by this limitation, we analyze the impact of the correlated shadowing to better evaluate DAS-based schemes with dual diversity transmitters. Assuming that shadowing correlation is an exponentially decreasing function of the inter-element separation, we derive the outage probability of DAS in composite Rayleigh-lognormal shadowing channels. Also, we present numerical and simulation results, which indicate there exists an optimal inter-separation between antennas that minimizes the outage rate to balance a trade-off between macro-diversity and path loss.

In this paper we present a low-complexity user selection algorithm for the downlink of a distributed antenna system (DAS) that achieves an optimum solution for a weighted matching problem. The user selection process is modeled as a linear sum assignment problem (LSAP). The proposed solution consists of two phases. In the first phase, a set of potential users to be scheduled is found by combining two complementary approaches: greedy and minimum-throughput-loss selection. In the second phase, the set of scheduled users is refined by selecting the users that maximize sum throughput. We provide numerical results to confirm the optimality of our user selection algorithm and to compare its performance with existing solutions.

Shadow fading is a common phenomenon in the wireless communication environment, which degrades the system performance severely. Compared with the conventional micro-diversity scheme, distributed antenna system (DAS) can work against such fading effectively. In this paper, a performance analysis of the uplink DAS using maximal ratio combining and equal gain combining diversity is done, and the analytical expressions of the outage probability and bit error ratio are derived. Here an approximation method is used and the results turn out to be quite precise. The conclusion drawn shows that DAS outperforms the conventional system significantly in the shadowing environment, and thus is a very promising technology for the future wireless communication frame.

Cell-Free (CF) massive multiple-input multiple-output (MIMO) system is a distributed antenna system, wherein a large number of access points wish to simultaneously communicate with a relatively small number of users. Similar to co-located massive MIMO system, pilot contamination and multi-user interference are two major impediments to CF massive MIMO network performance improvement. One can mitigate the detrimental effect of pilot contamination and multi-user interference through judicious resource allocation. In this work, we formulate and investigate the problem of frequency assignment for a CF massive MIMO. The formulated optimization problem is proven to be generally NP-hard. Local optima can be found by approaches such as the Lagrangian method that however, has considerably slow rates of convergence. To circumvent this issue, we propose an alternative solution being of two-folds. Firstly, we reformulate the problem as a grouping strategy which enables to attenuate the effect of intra-group multi-user interference. In the second fold, frequencies are assigned in a non-overlapping fashion to each scheduled group to palliate the effect of inter-group interference and pilot contamination. To further improve the performance of the proposed approach, power coefficients are allocated to the users via a sequential convex approximation (SCA)-based framework. The effectiveness of the proposed algorithms is then verified through extensive numerical simulations which demonstrate a non-negligible improvement in the performance of the studied scenario.

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.

In this paper, we confirm that load modulation technique can support generation of high-order m-QAM symbols for LM-MIMO system. And then we evaluate performance of LM-MIMO system using load modulated symbols. A number of RF chains can cause various problems in conventional MIMO system. On the other hand, LM-MIMO system requires single RF chain only. Therefore, LM-MIMO system has low-complexity and low power consumption. As results, we can confirm that load modulation of T-model can generate high-order m-QAM symbols. Also, we can confirm that 4×4 LM-MIMO system with single RF chain has a similar performance to conventional 4×4 MIMO system with a number of RF chains.

Massive MIMO is the new emerging technology which can be used to increase the data rate. Massive MIMO reap all benefits of conventional MIMO. In Massive MIMO we use the receiver diversity. In this paper we are proposing Opportunistic space division multiple access technology with beam selection for massive MIMO system technology. OSDMA-S is the technology in which we generate a orthonormal beam which carry the message symbols. In our proposed scheme we are implementing multi antenna for users. In conventional MIMO system we used only one antenna for one receiver, while in the massive MIMO we use a number of antenna at the user to increase the throughput of the system. In this paper we use four antenna four one user. By implementing Massive MIMO we increases the throughput by 100%.

Hybrid precoding schemes have recently gained a great attention for millimeter wave (mmWave) massive multiple-input-multiple-output (massive MIMO) communication systems because of offered cost and low-power consumption advantages. The singular value decomposition (SVD) method which is exploited in the design of hybrid precoding causes several problems on system design, especially on bit allocation, precoding and equalizing processes. On the other hand, the previous works show that generalized triangular decomposition (GTD) method can present asymptotically optimal performance in conventional MIMO systems. In the light of this, we propose the use of GTD method for designing hybrid precoding operating in mmWave massive MIMO systems. The proposed design is analyzed via performed simulation studies including different system configurations. Moreover, the archived results are compared with the standard orthogonal matching pursuit (OMP) algorithm based hybrid precoding scheme. The simulation results show that the proposed hybrid precoding scheme can reach up to the performance of optimal precoding scheme.

It is the pursuit of a multiple-input-multiple-output (MIMO) system to approach and even break the limit of channel capacity. The electromagnetic channel effective rank of MIMO system describes its effective channel number, which directly characterizes the channel performance and is widely used in the communication systems. However, it is always a big challenge to efficiently characterize the MIMO systems and evaluate the channel effective rank in complex scattering spaces which is crucial for guiding the optimization of the radio frequency front-end to get better propagation than the conventional MIMO systems considering only free space. To address this challenge, this paper proposes an efficient characterization of MIMO systems in complex scattering spaces based on T-matrix multiple scattering fast algorithm and accurately evaluates the electromagnetic channel effective rank under different scattering scenarios. Specifically, the key informatics parameters in free EM space based on a dyadic Green's function are derived. Next, the proposed T-matrix multiple scattering method is developed to describe the representative MIMO system in inhomogeneous scattering spaces. All the analytical results are validated by simulations. Furthermore, based on the efficient characterization of the MIMO system in complex scattering spaces, the electromagnetic channel effective rank is derived to evaluate channel capacity in this paper. In addition, the relationship between the electromagnetic effective capacity and the number of scatterings is explored, showing clearly that with the increase of the number of scatterings, the electromagnetic effectively capacity under different scattering scenarios will increase firstly then decreases. The conclusion can be summarized as follows: an appropriate increase in the number of scatterers can enhance the channel effective rank of MIMO system by creating more information transmission paths through multiple scattering. However, as the number of scatterers continues to rise, Anderson localization may restrict wave propagation, leading instead to a reduction in the channel effective rank. This proposed method can also be employed to precisely evaluate the channel capacity for more complex MIMO systems in future work.

Efficient constellation design is important for improving performance in communication systems. The problem of multidimensional constellation design has been studied extensively in the literature in the context of multidimensional coded modulation and space-time coded MIMO systems. Such constellations are formally called as lattice codes, where a finite set of points from a certain high dimensional lattice is chosen based on some criteria. In this paper, we consider the problem of constellation/signal set design for media-based modulation (MBM), a recent MIMO channel modulation scheme with promising theoretical and practical benefits. Constellation design for MBM is fundamentally different from those for multidimensional coded modulation and conventional MIMO systems mainly because of the inherent sparse structure of the MBM signal vectors. Specifically, we need a structured sparse lattice code with good distance properties. In this work, we show that using an (N,K) non-binary block code in conjunction with the lattice based multilevel squaring construction, it is possible to systematically construct a signal set for MBM with certain guaranteed minimum distance. The MBM signal set obtained using the proposed construction is shown to achieve significantly improved bit error performance compared to conventional MBM signal set. In particular, the proposed signal set is found to achieve higher diversity slopes in the low-to-moderate SNR regime.

This study proposes an uncooperative-multi-cell-multiple-input–multiple-output system to increase the throughput of an ill-conditioned wireless MIMO downlink system. The proposed algorithm suppresses the inter-cell interference at each mobile station using a set of adaptive receive beamformers, but handles the intra-cell interference at each base station using a Tomlinson Harashima precoder. Using the singular vectors of channel matrices, the receive beamformers can be designed based on a linear-constrained-minimum-variance criterion. On the other hand, to obtain high enough degree of freedoms for cancelling the intra-cell interference at each base station, the precoder is applied to the re-assembled downlink virtual channel formed by the simplified channel state information. Using the proposed interference suppression techniques, a multi-cell downlink system with multiple uncooperative base stations can be decomposed into a set of parallel subchannels. The resulting system has better performance in channel capacity than conventional MIMO systems. Computer simulations support the validity of the proposed approach.

A smart phone subscriber needs wide bandwidth services for more fast data communication on the internet. The conventional MIMO system is now developing to resolve these problems with limited device space for antenna and frequency band environment reserved. One of a way to make it practically is to add the number of antennas theoretically. But it is difficult to increase the antenna element as a limited space on the system. Therefore an active beam forming scheme is known as a way of constructing a low power MIMO system for that. In this paper, the fast switching control block was suggested to adjust a reactance of the antenna element and verified experimentally the effects by switching signal on an orthogonal beam forming through a spatial domain.

In this paper, we investigate the beam alignment problem in millimeter-wave (mmWave) distributed antenna systems where a home base station communicates with multiple users through a number of distributed remote radio units (RRUs). Specifically, a two-stage schedule-and-align (TSSA) scheme is proposed to facilitate efficient communications. In the first stage, a coarse beam scanning over the entire angular space is performed while beam indices and the corresponding peak-to-background ratios of the received power-angle-spectrum are obtained from users' feedback. Then, by exploiting the user feedback, an efficient user scheduling algorithm is developed to improve the system spectral efficiency and to reduce the system misalignment probability. Next, the second stage of beam search is performed by each RRU with reconfigured search angles, search steps, and power levels to obtain a refined beam alignment. Simulation results show that the proposed TSSA scheme can significantly outperform the conventional one-stage method in both centralized and distributed mmWave systems in terms of beam alignment accuracy and spectral efficiency.

In this paper, we propose a new low-complexity user selection algorithm for multi-user downlink channels. We only consider the scenario that linear beamforming, such as zero-forcing beamforming, is employed at the base station (BS). In this scenario, the number of concurrent active users is limited by the number of transmit antennas at the BS. Thus, there arises the problem how to select the optimal set of active users that can maximize the downlink channel capacity based on the channel state information (CSI) of all users. However, the optimal solution to this problem is an exhaustive search of all possible combinations of the users, which has prohibitive computational complexity. We propose a sub-optimal greedy user selection algorithm based on the norm and correlation between the channel matrices of different users. Our new algorithm requires low computational complexity and provides nearly optimal performance. Simulation results are presented to illustrate the good performance of our algorithm.