Performance Enhancement of Random Unitary Beamforming Based Multiuser MIMO Systems with Optimum Combining

Random unitary beamforming is one of the schemes reducing the amount of feedback information in multiuser diversity techniques with multiple-antenna downlink transmission. In multiple-input multiple-output (MIMO) systems, throughput performance is greatly improved using AMC (adaptive modulation and coding). Throughput performance is also improved by allocating power among streams appropriately. In random unitary beamforming, transmitter has only partial channel state information (CSI) of each receiver. Thus, it is difficult for random unitary beamforming to use conventional power allocation methods that use full CSI at all the receivers. In this paper, we propose a new scheduling algorithm with power allocation for downlink random unitary beamforming that improves throughput performance without full CSI. We provide numerical results of the proposed scheduling algorithm and compare them to those of the conventional random unitary beamforming scheduling algorithm.

Random unitary beamforming (RUB) is an attractive transmission scheme for MIMO broadcast channels because of its ability to achieve high sum-rate capacity with limited feedback. In this letter, we derive the exact analytical expressions for the ergodic sum rate of MIMO broadcast channels with RUB. The analysis is facilitated by the development of the complete statistical characterization of ordered beam SINRs for a user, which can find their application in many related problems.

The per user carrier-to-interference ratio (CINR) enhancement in the reverse link (mobile to base station) of a CDMA communications system is analyzed using different antenna array spatial combining algorithms: optimum combining (OC) versus maximal ratio combining (MRC) in a multi-rate (combined voice and data users) multi-antenna scenario. Many low data voice users and a single dominant high data user are used to achieve a high degree of colored spatial interference in the analysis. The ratio of the CINR for OC versus MRC is directly analyzed, ie, Z=CINR/sub OC//CINR/sub MRC/ instead of separate analysis of each CINR term: CINR/sub OC/ and CINR/sub MRC/ with later comparison. Exact solutions are derived for the statistics of a per user CINR/sub OC//CINIR/sub MRC/ improvement, as a function of the high-level interference power to background noise, and is compared with CDMA reverse link Monte Carlo simulations.

Random unitary beamforming (RUB) is a multiple antenna transmission scheme requiring limited channel state information (CSI) with low computational complexity. In this paper, we investigate the security performance of RUB over a multiple-input single-output single-eavesdropper (MISOSE) broadcast channel. We derive the closed-form expressions of ergodic secrecy rate and the secrecy outage probability (SOP) of the resulting design. Meanwhile, the effect of artificial noise (AN) on physical layer (PHY) security performance of RUB-based MISOSE transmission is also investigated. Numerical results are presented to illustrate the tradeoff between performance and complexity of the proposed PHY security design. We show that the deployment of RUB offers an attractive solution for enhancing the security of wireless transmission systems.

In this paper, an undesired fact for multiuser (MU) MIMO (MU-MIMO) systems using block diagonalization is presented, i.e., the increment of user number (K) results in the degradation of sum rate. This fact is caused by the opposition between two main factors determining the sum rate, namely, MU gain and transmit diversity. The MU gain guarantees a high order of degrees of freedom (DoFs) on system level but decreases the rate per user, while, for the transmit diversity, it is exactly opposite. Therefore, the tradeoff between the two factors is established to quantify how the two factors impact on the sum rate. Based on the tradeoff, the optimal K that maximizes the sum rate is further obtained. Additionally, it is pointed out that the sum rate can be improved substantially by only adding a few antennas at the base station when the system is fully loaded. The derivations are under large-scale system assumption, and being implemented on different precoders. Numerical simulations verify the tightness and accuracy of our asymptotic results for both large-scale and conventional systems.

In this letter, a closed form expression of the sum rate upperbound is derived for random beamforming. The proposed analytic solution provides a good approximation of the 'actual' sum rate performance, for which the conventional asymptotic analysis is less meaningful. Moreover, our result leads to an implication of the asymptotic growth rate of M log log K.

There is a continuing interest in low-complexity multiuser MIMO transmission techniques based on random unitary beamforming (RUB). Different RUB schemes mandate different amount of feedback to exploit the multiuser diversity gain for sum-rate capacity benefits. In this paper, we investigate the tradeoff of sum-rate capacity versus feedback load between different RUB schemes through accurate statistical analysis. Specifically, we derive the exact sum-rate expressions for two RUB schemes based on quantized signal-to-interference-plus- noise ratio (SINR) feedback. These analysis are accompanied by the development of the complete statistical characterizations of ordered SINRs for a user, which can find their application in many other related problems. We show through selected numerical examples that the additional feedback of the quantized values of best beam SINR from each user can help considerably improve the sum-rate performance of RUB systems.

In this paper, we apply simulation-based optimization methods to detect quadrature amplitude modulated (QAM) MIMO signals. The first one is the so-called Cross-Entropy (CE) method which enables the corresponding CE-based detector to provide bit-error-rate (BER) performance close to that achievable by the maximum-likelihood (ML) detector when the signal-to-noise ratio (SNR) is relatively low. Unfortunately, the performance curves exhibit error floors in the high SNR region. To improve the performance in the high SNR region, we borrow the concept of Particle Swarm Optimization (PSO) and refer to the resulting iterative detector as the Particle-Swarm-driven Cross-Entropy (PSD-CE) MIMO detector. This detector gives a significant BER performance improvement in the medium-to-high SNR region. We also consider the case when the channel state information is imperfect and suggest a robust detector structure based on a modified score function.

Sum rates for multi-user MIMO vector perturbation precoding with regularization

Fractional domain optimum combining (OC) using fractional Fourier transform has been considered in this article. It has already been established that in an interference-dominated environment, OC is the best among all the diversity techniques used for single-input multiple-output systems. This technique is based on the principle of maximising the signal-to-interference plus noise ratio at the output of the combiner. In this article, a new combiner, which calculates the weights in fractional domain, has been proposed to further enhance the performance of OC in terms of bit error rate (BER). Fractional domain combining gives better signal-to-noise ratio (SNR) at the output of the combiner as compared to time- or frequency-domain combiner due to complete removal of noise. For two receive antennas, the proposed combiner gives an SNR improvement of 7.2 and 2.4 dB as compared to time- and frequency-domain combiners, at a BER of 10−2. It has been concluded that the proposed technique clearly outperforms the existing technique.

The performance of a downlink multi-user MIMO system seriously degrades in time-varying environments because MIMO channels change during the time interval between transmission parameter determination and actual MIMO transmission. Channel prediction techniques have been proposed to improve the performance in dynamic environments. In this paper, based on indoor measurement data, we show the effect of the linear channel extrapolation, and evaluate the bit error rate performance of the multi-user MIMO system with the channel prediction technique.

The high throughput with low latency, massively connected devices, and effective utilization of spectrum for current wireless communication systems can be realized by adopting the fifth-generation (5G) new radio (NR) air interface. The key remarkable features that 5G NR presents are Ultra-Reliable Low-Latency Communications (URLLC), enhanced Mobile Broadband (eMBB), and massive Machine Type Communications (mMTC). To meet thereof features, 5G NR exerts different multiple access and modulation techniques. This paper addresses the physical layer of 5G NR and more explicitly explores the transmission of 5G NR over the physical uplink shared channel (PUSCH) considering several parameters. For example, different sub-carrier spacings (SCSs) are taken into account for analyzing the performance of PUSCH in terms of throughput versus Signal-to-Noise Ratio (SNR). Moreover, the effect of the well-known modulation techniques such as Quadrature Phase Shift Keying (QPSK), different order of Quadrature Amplitude Modulation (QAM) (i.e., 16, 64, and 256) on throughput is studied. Later on, the number of base station (BS) and user equipment (UE) antennas are varied. Lastly, the performance of PUSCH over different propagation channel models (clustered delay line (CDL) and tap delay line (TDL)) is also investigated in this paper. The extensive simulation studies have proved that QPSK exhibits finer outcomes in low SNR regions while 256-QAM shows remarkable results in high SNR regions. The maximum throughput can be realized even in low SNR regime if the number of BS antennas is increased. In addition, high throughput value can be attained by increasing SCS.

The multiuser MIMO (MU-MIMO) systems tend to have inter-user interference in practical systems with limited feedback. Practical MU-MIMO systems with limited feedback can be divided into two classes in general. One is zero-forcing beamforming (ZFBF), and the other is per user unitary rate control (PU <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> RC) which is an extended version of random beamforming (RBF). To improve performance, ZFBF needs more feedback bits, and PU <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> RC needs a larger number of users. We propose a new hybrid MU-MISO system which has the advantages of the two MU-MIMO schemes simultaneously, and analyze the sum-rate performance and the quantization error of the hybrid scheme. The analysis shows how the number of feedback bits, the number of users, and the signal power affect the sum-rate. The throughput scaling laws are also derived in the high and the medium SNR regimes. Simulation results show that the proposed hybrid MU-MISO system performs better than either of the two MU-MIMO systems with the same number of feedback bits. Another advantage is that it has lower complexity for codeword search since it has a hierarchical codebook structure.

In multiuser MIMO systems, block diagonalization (BD) eliminates inter-user interference with perfect CSI since the transmitter decomposes a multiuser MIMO channel into multiple parallel independent single-user MIMO channels. For a large number of users, the transmitter selects a subset of users who have good channels to maximize the system throughput. In this paper, a new low complexity scheduling algorithm with BD is proposed since an exhaustive search for the optimal user set is impractical. Simulation results show that the proposed algorithm has much lower complexity while it achieves the total throughput close to the optimal algorithm. It also has lower complexity than previous low complexity scheduling algorithms.

In this paper, we investigate the outage performance of decode-and-forward (DF) based opportunistic cooperative communications with channel estimation errors at the receivers under Rayleigh fading channels, in which the effect of the direct link has been explicitly evaluated. To be specific, the exact expression of outage probability has been derived for arbitrary values of signal-to-noise ratio (SNR) when pilot power is fixed. Through asymptotic analysis, the closed-form expressions of outage probability in the high SNR region and the diversity order are obtained. The analysis shows that the channel estimation errors due to limited pilot power impose a significant impact on the outage performance, leading to the diversity order be 0 even when the direct link is available. Although deploying more relays can mitigate the estimation errors effectively, the performance limit caused by the estimation errors becomes more obvious as SNR grows. For specific pilot power configuration and relay deployment, the outage probability remains unchanged even if data power approaches to infinity. Furthermore, simulation results are presented to verify our analysis.