Number Of Tx Antennas Research Articles

Generalized Complementary Coded Scrambling Multiple Access for MIMO Communications

Spectrum efficiency is a critical performance metric in wireless communications due to an increasing demand for radio spectrum to support high data rate applications. Direct sequence spread spectrum technology enables a code division multiple access (CDMA) system a strong anti-interference capability but with a relatively low spectrum efficiency. To address this issue, complementary coded scrambling multiple access (CCSMA) (X. Liu <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al</i> ., in 2018) was proposed to use three-dimensional (space-time-frequency) resources for performance enhancement. However, in a CCSMA system, if the number of multipath returns is larger than the number of transmit (Tx) antennas, a code reuse problem occurs to degrade bit error rate performance significantly. This work designs a new scrambling code, namely generalized complementary coded scrambling multiple access (GCCSMA) codes, to overcome the code reuse problem in CCSMA. GCCSMA uses complementary codes, scrambling modulation, and multiple-input-multiple-output (MIMO) techniques jointly, which works well even in multipath channels with more paths than the number of Tx antennas. The analysis and simulations are conducted to validate the effectiveness of the proposed GCCSMA system.

Simplified Antenna Group Determination of RS Overhead Reduced Massive MIMO for Wireless Sensor Networks.

Massive multiple-input multiple-output (MIMO) systems can be applied to support numerous internet of things (IoT) devices using its excessive amount of transmitter (TX) antennas. However, one of the big obstacles for the realization of the massive MIMO system is the overhead of reference signal (RS), because the number of RS is proportional to the number of TX antennas and/or related user equipments (UEs). It has been already reported that antenna group-based RS overhead reduction can be very effective to the efficient operation of massive MIMO, but the method of deciding the number of antennas needed in each group is at question. In this paper, we propose a simplified determination scheme of the number of antennas needed in each group for RS overhead reduced massive MIMO to support many IoT devices. Supporting many distributed IoT devices is a framework to configure wireless sensor networks. Our contribution can be divided into two parts. First, we derive simple closed-form approximations of the achievable spectral efficiency (SE) by using zero-forcing (ZF) and matched filtering (MF) precoding for the RS overhead reduced massive MIMO systems with channel estimation error. The closed-form approximations include a channel error factor that can be adjusted according to the method of the channel estimation. Second, based on the closed-form approximation, we present an efficient algorithm determining the number of antennas needed in each group for the group-based RS overhead reduction scheme. The algorithm depends on the exact inverse functions of the derived closed-form approximations of SE. It is verified with theoretical analysis and simulation that the proposed algorithm works well, and thus can be used as an important tool for massive MIMO systems to support many distributed IoT devices.

Optimal transmission power determination to increase energy efficiency of large-scale MIMO antenna systems

Large-scale (LS) MIMO antenna systems use excessive amount of TX antennas and serve limited number of users to make very high channel gain, and it is obvious that the channel gain increases spectral efficiency of the system. The transmission power of LS-MIMO systems also can be reduced from the increment of channel gain to increase energy efficiency (EE). In this situation, a determination of transmission power which is reduced from total available transmission power can be an important scheme to achieve high EE. This paper proposes a determination scheme of the EE optimum transmission power for LS-MIMO systems. The approximated optimum transmission power is derived analytically as a closed-form function based on various parameters, such as number of TX antennas, number of users, system bandwidth, interference, and so on. Using the closed-form function with the measurable parameters, we can easily get the optimum EE transmission power in real-time. The effectiveness of proposed scheme is validated with numerical simulations. According to the results, the proposed scheme can significantly increase the EE with fairly small loss of channel capacity, compared with ordinary LS-MIMO systems.

On Optimal Precoding for MISO With Nonlinear Power Amplifiers

Optimal precoding for multiple-input single-output (MISO) systems with nonlinear power amplifiers (PAs) is proposed. The idea behind the precoding is to generate a set of transmitted signals s.t., after passing through the nonlinear PAs and MISO channel, a desired signal will be obtained at the receiver’s antenna. The channel is assumed to be frequency selective. It is assumed that the channel and noise power are known at the transmitter (TX). The specific aim of the proposed precoding is to maximize signal-to-interference and noise ratio (SINR) per symbol at the receiver. The proposed technique can be seen as a generalization of the constant envelope (CE) precoding approach, based on the same concepts. However, in this work we assume a general PA nonlinearity and, therefore, the TX signals may have varying amplitude. Moreover, while in the CE only the nonlinear distortions (interference), seen at the receiver, are minimized, we propose to maximize the SINR. This approach shows better symbol error rate (SER) performance than CE precoding. For given SER requirement, the PSNR gap is clearly seen for a low number of TX antennas, although, as the number of TX antennas increases the PSNR gap decreases.

Analysis of Joint Transmit–Receive Diversity in Downlink MIMO Heterogeneous Cellular Networks

We study multiple-input–multiple-output (MIMO)-based downlink heterogeneous cellular networks (HetNets) with joint transmit–receive diversity using orthogonal space–time block coding at the base stations (BSs) and maximal-ratio combining (MRC) at the users. MIMO diversity with MRC receivers is particularly appealing in cellular networks due to the relatively low hardware complexity at both the BS and the user device. Using stochastic geometry, we develop a tractable stochastic model for analyzing such HetNets taking into account the irregular and multitier BS deployment. We derive the coverage probability for both interference-blind (IB) and interference-aware (IA) MRC as a function of the relevant tier-specific system parameters such as BS density and transmit (Tx) power, number of Tx antennas, and path-loss law. Important insights arising from our analysis for typical HetNets are as follows: 1) IA-MRC becomes less favorable than IB-MRC with Tx diversity due to the smaller interference variance and increased interference correlation across receive (Rx) antennas; 2) ignoring spatial interference correlation significantly overestimates the performance of IA-MRC; and 3) for a small number of Rx antennas, selection combining may offer a better performance–complexity tradeoff than MRC.

Spatial Diversity, Low PAPR and Fast Decoding for OFDM using L2-Orthogonal CPM ST-Codes

Orthogonal Frequency Division Multiplexing (OFDM) schemes provide high data rates and good robustness against frequency selective fading for communication systems. Space-Time Block Coding (STBC) is an efficient way to introduce space-time diversity in Multiple-Input Multiple-Output (MIMO) systems. Using non-linear modulations such as Continuous Phase Modulation (CPM) with its constant envelope property may be a way to construct MIMO OFDM systems that alleviates the typical Peak to Average Power Ratio (PAPR) issue of OFDM. However, CPM based systems are usually plagued by decoding complexity issues. In this paper, we introduce space-time-frequency diversity techniques based on L2-orthogonal multi-h CPM Space-Time codes designed for OFDM transmission. We benchmark these codes under frequency selective Rayleigh channels and show how they achieve full spatial diversity at full rate for any number of antennas, good spectral compactness, low PAPR and robustness to frequency fading. Furthermore, L2-orthogonality allows fast decoding with complexity growing only linearly in the number of Tx antennas.

Comments on "Asymptotic eigenvalue distributions and capacity for MIMO channels under correlated fading

A stronger and general sufficient condition for the asymptotic normality of MIMO channel eigenvalues and its capacity is given. Physical interpretation of this condition is discussed. Simple alternative conditions, which do not require eigenvalue decomposition, are proposed. It is demonstrated that some popular correlation matrix models satisfy these conditions. In many cases, the convergence to the asymptotic normality is at least as 1/radic( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">nt</i> ), where <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">nt</i> is the number of Tx antennas.

Generally Dimensional and Constellation Expansion Free Space–Time Block Codes for QAM With Full Diversity

This correspondence presents new rate-1 space-time block codes (STBCs) attending full diversity over every quadrature amplitude modulation (QAM) constellation when the number of Tx antennas is a power of two. From the simulation results, our design performs very closely to the quasi-orthogonal code with constellation rotation over 4-QAM and 16-QAM in the case of four Tx antennas over quasi-static Rayleigh fading channels. Moreover, the proposed codes would not cause any constellation expansion over QAM symbols in contrast with the quasi-orthogonal codes with constellation rotations