MIMO Systems With Quantized Covariance Feedback

Multi input multi output (MIMO) system with the multiple antennas at both the transmitter and receiver is the emerging technology in the modern wireless system. MIMO systems are well adopted due to its high spectral efficiency and high data rates. For the detection of MIMO systems, a powerful technique called Lattice Reduction (LR) algorithm are used to obtain the better orthogonality in the channel matrices and is aided with the linear and low complexity detectors such as Zero forcing(ZF) and Minimum mean square error (MMSE) for the reduction in complexity. In this paper we propose a new algorithm called Enhanced lattice reduction algorithm to improve the error performance for the linear detectors with the lesser complexity and also it is aided with the non linear precoding called Tomlinson-Harashima precoding (THP) in the presence of channel state information (CSI). Lattice reduction aided with THP improves the performance linearly. BER performance of the proposed algorithm is determined and it is compared with the other LR aided algorithms in the literature.

최근 대용량, 초고속 통신 서비스의 비중이 높아짐에 따라 배열 안테나를 사용하는 MIMO(Multi-Input Multi-Output) 시스템의 활용이 중요하게 평가되고 있다. 하지만 기존의 MIMO 시스템은 다수의 안테나를 사용하기 때문에 안테나의 개수만큼 RF(Radio Frequency) 체인이 요구되며, 이로 인해 복잡도와 전력 소모가 크다는 단점을 가진다. 이러한 기존 MIMO 시스템의 단점을 해결하기 위해서 단일 능동 소자와 다수의 기생 소자를 이용하는 방식의 ESPAR(Electronically Steerable Parasitic Array Radiator) 안테나를 사용하는 빔 공간 MIMO 시스템에 대한 연구가 활발히 진행되고 있다. ESPAR 안테나를 사용하는 빔 공간 MIMO 시스템은 단일 RF 체인으로 구성되어 있기 때문에 기존 MIMO 시스템의 단점을 해결할 수 있다. 본 논문에서는 시스템의 보안성을 향상시키기 위해 QPSK(Quadrature Phase Shift Keying) 변조 방식의 ESPAR 안테나를 사용하는 빔 공간 MIMO 시스템에 비예측성, 비주기성, 구현의 용이성, 민감한 초기조건 등의 특징을 가지고 있는 카오스 통신 알고리즘을 적용하여 QPSK 변조 방식의 ESPAR 안테나를 사용하는 카오스 빔 공간 MIMO 시스템을 구성하고 성능을 평가한다. Recently, utilization of MIMO(Multi-Input Multi-Output) system using array antennas is evaluated significantly according to the extension of high-capacity and high-speed communication services. However, MIMO system has disadvantages such as high-complexity and high-power-consumption, because RF(Radio Frequency) chain is required as antenna number, and several array antenna is used in conventional MIMO system. In order to solve these problems, research about beamspace MIMO system using ESPAR(Electronically Steerable Parasitic Array Radiator) antenna that has single RF chain by using one active antenna and several parasitic elements has been studied actively. Beamspace MIMO system using ESPAR antenna is possible to solve the problems of conventional MIMO system, because this system is composed by single RF chain. In this paper, in order to improve the system security, chaos communication algorithm that has characteristics such as non-periodic, non-predictability, easy implementation and initial condition is applied to QPSK (Quadrature Phase Shift Keying) modulated beamspace MIMO system. We design the chaos QPSK modulated beamspace MIMO system, and evaluate SER performance of this system.

In wireless communication, multiple signals are utilized to receive and send information in the form of signals simultaneously. These signals consume little power and are usually inexpensive, with a high data rate during data transmission. An Multi Input Multi Output (MIMO) system uses numerous antennas to enhance the functionality of the system. Moreover, system intricacy and power utilization are difficult and highly complicated tasks to achieve in an Analog to Digital Converter (ADC) at the receiver side. An infinite number of MIMO channels are used in wireless networks to improve efficiency with Cross Entropy Optimization (CEO). ADC is a serious issue because the data of the accepted signal are completely lost. ADC is used in the MIMO channels to overcome the above issues, but it is very hard to implement and design. So, an efficient way to enhance the estimation of channels in the MIMO system is proposed in this paper with the utilization of the heuristic-based optimization technique. The main task of the implemented channel prediction framework is to predict the channel coefficient of the MIMO system at the transmitter side based on the receiver side error ratio, which is obtained from feedback information using a Hybrid Serial Cascaded Network (HSCN). Then, this multi-scaled cascaded autoencoder is combined with Long Short Term Memory (LSTM) with an attention mechanism. The parameters in the developed Hybrid Serial Cascaded Multi-scale Autoencoder and Attention LSTM are optimized using the developed Hybrid Revised Position-based Wild Horse and Energy Valley Optimizer (RP-WHEVO) algorithm for minimizing the "Root Mean Square Error (RMSE), Bit Error Rate (BER) and Mean Square Error (MSE)" of the estimated channel. Various experiments were carried out to analyze the accomplishment of the developed MIMO model. It was visible from the tests that the developed model enhanced the convergence rate and prediction performance along with a reduction in the computational costs.

We consider the design of the precoder for a multi-input multi-output (MIMO) communication system equipped with a decision feedback equalizer (DFE) receiver. For such design problems, perfect knowledge of the channel state information (CSI) at both the transmitter and the receiver is usually required. However, in the wireless communications environment, it is often difficult to provide sufficiently timely and accurate feedback of CSI from the receiver to the transmitter for such designs to be practically viable. In this paper, we consider the optimum design of a precoder for a wireless communication link having M transmitter antennas and N receiver antennas (M ≪ N), in which the channels are assumed to be flat fading and may be correlated. We assume that full knowledge of CSI is available at the receiver. At the transmitter however, only the second order statistics of the channels are available. Our goal here is to come up with an efficient design of the optimal precoder for such a MIMO system by minimizing the average arithmetic mean-squared error (MSE) of zero-forcing (ZF) decision feedback detection subject to a constraint on the total transmitting power. Applying some of the properties of the matrix parameters, this non-convex optimization problem can be transformed into a convex geometrical programming problem which can then be efficiently solved using an interior point method. The superior performance of our MIMO system equipped with the optimum precoder is verified by computer simulations.

Present wireless technologies demand high quality broadband services even at cell edges. Multi-hop relay (MHR) network is one of the suitable solutions for the above demands. The standards like IEEE 802.16j and Long Term Evolution (LTE) are using relay architecture which mainly focuses on capacity and coverage improvement. In recent days, multi antenna MHR networks are becoming more popular. However obtaining accurate channel state information (CSI) has become a crucial issue in MHR network performance. In this paper, we analyze the effect of delayed CSI at the transmitter (CSIT) in a system with N transmit antennas and one receive antenna, which uses antenna selection (AS). Assuming perfect CSI at the receiver (CSIR), only two out of the N transmit antennas is selected by the receiver and the indices for the same are fed back to the transmitter over a noiseless link with some finite delay. Thus this paper studied the reduced multiple input single output (MISO) systems for MHR networks which perform well even with delayed CSIT. The simulation results also validate the same.

In this paper, we study the two-user Gaussian fading Multiple Access Channel (MAC) with cooperative encoders. Two different scenarios are studied: the Gaussian fading MAC with a common message, and the Gaussian fading MAC with conferencing encoders. The throughput capacity region of these channels with partial Channel State Information (CSI) at the transmitters (CSIT) and perfect CSI at the receiver (CSIR) is established. For the Gaussian fading systems with only CSIR (transmitters have no access to CSIT), some numerical examples and simulation results are provided for Rayleigh fading models.

The effect of DC offset on multi-input multi-output (MIMO) direct transceivers with adaptive modulation (AM) is discussed in this paper. A variable-rate variable-power (VRVP) AM system with perfect channel state information (P-CSI) at both the transmitter and receiver in a MIMO scenario is considered. The DC offset is modeled as a zero mean complex Gaussian distributed random variable. By this modeling of the DC offset, the analytical expression for degraded bit error rate (BER) is derived. To derive this analytical expression, we establish a reasonable approximation. The good agreement between the analytical and simulation results shows that the approximation is valid and confirms the accuracy of the analytical expressions. Moreover, an approach to improve the degraded BER in these systems is introduced. For this purpose, we introduce a design for AM MIMO systems that takes account of DC offset and its effectiveness is confirmed. Throughput analysis for the AM MIMO system in the presence of DC offset is presented in this paper too. An analytical expression for throughput is derived and approximated to a simpler equation. At last, throughput results are compared to the simulation outcomes.

In this paper, a new proof for the degrees of freedom (DoF) region of the K-user multiple-input multiple-output (MIMO) broadcast channel (BC) with no channel state information at the transmitter (CSIT) and perfect channel state information at the receivers (CSIR) is provided. Based on this proof, the capacity region of a certain class of MIMO BC with channel distribution information at the transmitter (CDIT) and perfect CSIR is derived. Finally, an outer bound for the DoF region of the K-user MIMO interference channel (IC) with no CSIT is provided.

Transmit diversity schemes have been studied for high spectral-efficiency and high bit-rate transmission, such as multi-input multi-output (MIMO) systems. In this paper, a novel dual polarized ceiling-mounted antenna is designed and simulated. In the MIMO systems, forward error correction coding is essential for high quality communications. At the two typical scenes, the single-input single-output system compared with two single polarized antennas and an dual polarized antenna MIMO system is tested. It is shown that the MIMO system have improved throughput level obviously. The dual polarized ceiling-Mounted dual streams MIMO antenna will save much construction cost in the long-term evaluation systems in the future, which can be called the “green” MIMO antenna.

We study a practical version of the broadcast channel (BC) where the channel state information at the transmitter (CSIT) is available only for some of the users, dubbing the system as mixed CSIT. We start with the simplest instance of such a heterogeneous BC where a multi-antenna transmitter base-station (BS) is trying to communicate data to two single-antenna user equipments (UE), having the perfect CSIT about UE1 and no CSIT about UE2. We propose a very simple transmission strategy at the BS for such a system and compare its performance with the interference alignment solution proposed elsewhere which achieves full degrees-of-freedom (DOF) when channel coherence lengths and switching instants abide by certain restrictions. Then with an additional receive antenna granted to UE2 (whose CSIT is not available) and keeping the same CSIT perspective, achievable rates for two users are derived and compared with earlier schemes. Analytical and simulation results show that this additional receive antenna brings significant gains in the system with the same transmission strategy and without any extra requirement of channel training or feedback.

This paper addresses the performance analysis of an adaptive wireless link with one antenna transmitter and a multiple antenna maximum-ratio combining (MRC) receiver. Two main assumptions are used in this paper: (1) Rayleigh fading correlated channels (i.e., MRC branch correlation) and (2) imperfect (outdated) channel state information at the transmitter (CSIT) side. The main contribution of this work lies in the derivation of analytic expressions (in terms of a series expansion) of the statistics of correct packet reception conditional on the decisions made by the transmitter based on outdated CSIT. The novelty of this derivation is the joint modelling of spatially correlated branches, imperfect CSIT, and adaptive modulation based on threshold-trigger decision. Contrary to common belief, the results presented here suggest that spatial correlation not always affects the performance of the MRC receiver: at low signal-to-noise ratio (SNR), correlation can improve performance rather than degrading it. In contrast, at high SNR, correlation is found to always degrade performance. At high SNR, correlation tends to worse the degrading effects of imperfect CSIT, particularly when the number of antennas increases. Imperfect CSIT causes errors in the assignment of MCSs, thus reducing throughput performance. These errors become more evident in the high SNR regime, particularly when the values of branch correlation and the number of antennas increase.

The degrees of freedom (DoFs) of the two-user multiple-input single-output (MISO) broadcast channel (BC) are studied under the assumption that the form, <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$I_{i},\;i=1, 2$</tex></formula> , of the channel state information at the transmitter (CSIT) for each user's channel can be either perfect <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$(P)$</tex></formula> , delayed <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$(D)$</tex></formula> , or not available <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$(N)$</tex></formula> , i.e., <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$I_{1},I_{2} \in \{P,N,D\}$</tex> </formula> , and therefore, the overall CSIT can alternate between the nine resulting states <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$I_{1}I_{2}$</tex></formula> . The fraction of time associated with CSIT state <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$I_{1}I_{2}$</tex></formula> is denoted by the parameter <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$\lambda_{I_{1}I_{2}}$</tex></formula> and it is assumed throughout that <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$\lambda_{I_{1}I_{2}} = \lambda_{I_{2}I_{1}}$</tex></formula> , i.e., <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$\lambda_{PN} = \lambda_{NP}, \lambda_{PD}=\lambda_{DP}, \lambda_{DN}=\lambda_{ND}$</tex> </formula> . Under this assumption of symmetry, the main contribution of this paper is a complete characterization of the DoF region of the two-user MISO BC with alternating CSIT. Surprisingly, the DoF region is found to depend only on the marginal probabilities <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$(\lambda_{P}, \lambda_{D},\lambda_{N})=\left(\sum_{I_{2}}\lambda_{PI_{2}},\sum_{I_{2}}\lambda_{DI_{2}}, \sum_{I_{2}}\lambda_{NI_{2}}\right)$</tex></formula> , <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$I_{2} \in \{P,D,N\}$</tex></formula> , which represent the fraction of time that any given user (e.g., user 1) is associated with perfect, delayed, or no CSIT, respectively. As a consequence, the DoF region with all nine CSIT states, <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">${\cal {D}}(\lambda_{I_{1}I_{2}}:I_{1},I_{2} \in \{P,D,N\})$</tex> </formula> , is the same as the DoF region with only three CSIT states <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">${\cal {D}}(\lambda_{PP}, \lambda_{DD}, \lambda_{NN})$</tex> </formula> , under the same marginal distribution of CSIT states, i.e., <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$(\lambda_{PP}, \lambda_{DD},\lambda_{NN})=(\lambda_{P},\lambda_{D},\lambda_{N})$</tex></formula> . The sum-DoF value can be expressed as <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">${\rm DoF}=\min \left({{4+2\lambda_{P}} \over {3}}, 1+\lambda_{P}+\lambda_{D}\right)$</tex></formula> , from which one can uniquely identify the minimum required marginal CSIT fractions to achieve any target DoF value as <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$(\lambda_{P},\lambda_{D})_{\min}=\left({{3} \over {2}} {\rm DoF}-2,1- {{1} \over {2}} {\rm DoF}\right)$</tex></formula> when <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">${\rm DoF} \in \big [{{4} \over {3}},2\big]$</tex></formula> and <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$(\lambda_{P},\lambda_{D})_{\min}=(0,({\rm DoF}-1)^{+})$</tex></formula> when <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">${\rm DoF} \in \big [0, {{4} \over {3}}\big)$</tex></formula> . The results highlight the synergistic benefits of alternating CSIT and the tradeoffs between various forms of CSIT for any given DoF value. Partial results are also presented for the multiuser MISO BC with <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$M$</tex></formula> transmit antennas and <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$K$</tex> </formula> single antenna users. For this problem, the minimum amount of perfect CSIT required per user to achieve the maximum DoFs of <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$\min (M,K)$</tex></formula> is characterized. By the minimum amount of CSIT per user, we refer to the minimum fraction of time that the transmitter has access to perfect and instantaneous CSIT from a user. Through a novel converse proof and an achievable scheme, it is shown that the minimum fraction of time perfect CSIT is required per user in order to achieve the DoF of <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$\min (M,K)$</tex></formula> is given by <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$\min (M,K)/K$</tex></formula> .

In this paper, a comprehensive comparison analysis in terms of outage probability and average symbol error ratio (SER) is presented for cooperative cognitive multiple-input and multiple-output (CC-MIMO) multiuser systems with amplify-and-forward (AF) protocol. Specially, we consider two scenarios where the CC-MIMO multiuser systems have the perfect and imperfect channel state information (CSI). The CC-MIMO multiuser systems consist of one multi-antenna source, one single-antenna relay, and multiple multi-antenna destinations. At the secondary source and destinations, the maximal ratio transmission (MRT) and maximal ratio combining (MRC) are employed, respectively. For such CC-MIMO multiuser systems, we first obtain the exact closed-form expressions of outage probability under the two cases where the CC-MIMO multiuser systems have the perfect and imperfect CSI. Then, to reduce the implementation complexity, the tight lower bounds of outage probability and average SER are derived. Finally, to obtain insight, by using the high signal-to-noise ratio (SNR) approximation, the asymptotic estimations of outage probability are achieved. The numerical results show that the derivations are agreed with the simulations, which validate our derivations. At the same time, the results show that, for the systems without perfect CSI, the achievable diversity order reduces to one, regardless of the number of antennas at the cognitive source and destinations as well as the number of the cognitive destinations. Nevertheless, these key parameters affect the coding gain of the CC-MIMO multiuser systems. When the systems have the perfect CSI (or without feedback delay), the achievable diversity gain is determined by the minimum between the number of source’s antennas and the product of the number of destinations and the number of destination’s antennas. For the effect of PU’s parameters, our results indicate that primary systems only affect the coding gain but not the diversity gain.

This paper investigates the massive multi-input multi-output (MIMO) system in practical deployment scenarios, in which, to balance the economic and energy efficiency with the system performance, the number of radio frequency (RF) chains is smaller than the number of antennas. The base station employs antenna selection (AS) to fully harness the spatial multiplexing gain. Conventional AS techniques require full channel state information (CSI), which is time-consuming as the antennas cannot be simultaneously connected to the RF chains during the channel estimation process. To tackle this issue, we propose a novel joint channel prediction and AS (JCPAS) framework to reduce the CSI acquisition time and improve the system performance under temporally correlated channels. Our proposed JCPAS framework is a fully probabilistic model driven by deep unsupervised learning. The proposed framework is able to predict the current full CSI, while requiring only a historical window of partial observations. Extensive simulation results show that the proposed JCPAS can significantly improve the system performance under temporally correlated channels, especially for very large-scale systems with highly correlated channels. multi-output (MIMO) system in practical deployment scenarios, in which, to balance the economic and energy efficiency with the system performance, the number of radio frequency (RF) chains is smaller than the number of antennas. The base station employs antenna selection (AS) to fully harness the spatial multiplexing gain. Conventional AS techniques require full channel state information (CSI), which is time-consuming as the antennas cannot be simultaneously connected to the RF chains during the channel estimation process. To tackle this issue, we propose a novel joint channel prediction and AS (JCPAS) framework to reduce the CSI acquisition time and improve the system performance under temporally correlated channels. Our proposed JCPAS framework is a fully probabilistic model driven by deep unsupervised learning. The proposed framework is able to predict the current full CSI, while requiring only a historical window of partial observations. Extensive simulation results show that the proposed JCPAS can significantly improve the system performance under temporally correlated channels, especially for very large-scale systems with highly correlated channels.

This paper addresses the problem of frequency offsets and channel gains estimation for a multi-input multi-output (MIMO) system in flat-fading channels. The general case where the frequency offsets are possibly different for each transmit antenna is considered. The maximum-likelihood (ML) estimation of the carrier frequency offset for each transmit antenna in a MIMO system is investigated in this paper, assuming that a training sequence is available. The exact solution to this estimation problem turns out to be too complex as it involves a search over a multi-dimensional domain. To solve this complex estimation problem, a novel joint estimation algorithm of frequency offsets and channel gains is proposed. Frequency offsets are first estimated by the particle swarm optimization theory. Then channel gains are estimated by the ML estimator. Simulation results show that the proposed algorithm has better performance as compared with the correlation-based estimation algorithm and asymptotically achieves the Cramer-Rao lower bound (CRLB), which provides a new idea to solve the problem of joint frequency offsets and channel gains estimation for MIMO systems.