In this paper, we present a novel reconfigurable intelligent surface (RIS)-assisted integrated sensing and communication (ISAC) system with 1-bit quantization at the ISAC base station. An RIS is introduced in the ISAC...
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The downlink of a multi-user massive MIMO wireless system is considered, where the base station equipped with a large number of antennas simultaneously servesmultiple users. In this paper, an effective user selection ...
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The downlink of a multi-user massive MIMO wireless system is considered, where the base station equipped with a large number of antennas simultaneously servesmultiple users. In this paper, an effective user selection algorithm is proposed for quantized precoding in massive MIMO systems. The algorithm aims at minimizing the correlation of precoders among users by relaxing the optimal problem to be convex and solving it using the Primal Newton's Barrier Method. The complexity of the proposed algorithm is relatively low and the performance shown by the numerical results is close to the exhaustive search method. The advantage of the proposed algorithm increasingly shows up as the transmit antennas increase significantly.
We consider the downlink of a multi-user massive MIMO wireless system, where the base station equipped with a large number of antennas simultaneously serves multiple users. In this paper, we propose an effective user ...
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ISBN:
(纸本)9781479914067
We consider the downlink of a multi-user massive MIMO wireless system, where the base station equipped with a large number of antennas simultaneously serves multiple users. In this paper, we propose an effective user selection algorithm for quantized precoding in massive MIMO systems. The algorithm aims at minimizing the correlation of precoders among users by relaxing the optimal problem to be convex and solving it using the Primal Newton's Barrier Method. The complexity of our proposed algorithm is relatively low and the performance shown by the numerical results is close to the exhaustive search method. The advantage of the proposed algorithm increasingly shows up as the transmit antennas increase significantly.
In this paper, we study the hybrid precoding structures for massive multiuser multiple-input multiple-output ( MIMO) systems. Particularly, the practical hardware network models with insertion loss are developed. The ...
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ISBN:
(纸本)9781509050192
In this paper, we study the hybrid precoding structures for massive multiuser multiple-input multiple-output ( MIMO) systems. Particularly, the practical hardware network models with insertion loss are developed. The achievable rates of two typical hybrid precoding structures, the fully-connected structure and the sub-connected structure, are investigated, from which we discover that the sub-connected structure always outperforms the fully-connected structure in terms of the achievable rate in massive MIMO. We further characterize the effect of quantized analog precoding which indicates that the sub-connected structure is able to achieve better performance with fewer feedback bits than the fully-connected structure. We also propose a channel statistics-based codebook used for the digital precoding stage which is more suitable for hybrid precoding systems than the conventional random vector quantization (RVQ) codebook.
This study considers a generalized constant envelope-based precoding design problem in massive multiuser multiple-input multiple-output systems, in which the output signals of digital-to-analog converters are restrict...
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This study considers a generalized constant envelope-based precoding design problem in massive multiuser multiple-input multiple-output systems, in which the output signals of digital-to-analog converters are restricted to M-ary phase-shift keying signaling to facilitate the use of low-cost and power-efficient power amplifiers at a base station. We aim to jointly optimize the precoding vector and the precoding factor to minimize the mean-squared error between the transmitted and the estimated symbols. However, the considered precoding problem is nonconvex and challenging to solve because the precoding vector and the precoding factor are coupled together. To address this problem, we apply the alternating minimization (AltMin) framework to decouple the considered problem into two problems: the precoding factor design problem and the precoding vector design problem. The former has an analytical solution, while the latter requires solving a difficult combinatorial problem, which we address by proposing a simple yet efficient gradient projection (GP)-based algorithm to find an approximate precoding vector. Simulation results demonstrate that the proposed GP-based AltMin algorithm achieves the same or higher BER performance than state-of-the-art algorithms while requiring lower complexity. In addition, when higher order modulations are employed, the error floor experienced by the existing algorithms can be substantially mitigated by the proposed GP-AltMin algorithm through increasing the number of phase bits.
In modern (5G) and future Multi-User (MU) wireless communication systems Beyond 5G (B5G) using Multiple-Input Multiple-Output (MIMO) technology, base stations with a large number of antennas communicate with many mobi...
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In modern (5G) and future Multi-User (MU) wireless communication systems Beyond 5G (B5G) using Multiple-Input Multiple-Output (MIMO) technology, base stations with a large number of antennas communicate with many mobile stations. This technology is becoming especially relevant in modern multi-user wireless sensor networks in various application scenarios. The problem of organizing an MU mode on the downlink has arisen, which can be solved by precoding at the Base Station (BS) without using additional channel frequency-time resources. In order to utilize an efficient precoding algorithm at the base station, full Channel State Information (CSI) is needed for each mobile station. Transmitting this information for massive MIMO systems normally requires the allocation of high-speed channel resources for the feedback. With limited feedback, reduced information (partial CSI) is used, for example, the codeword from the codebook that is closest to the estimated channel vector (or matrix). Incomplete (or inaccurate) CSI causes interference from the signals, transmitted to neighboring mobile stations, that ultimately results in a decrease in the number of active users served. In this paper, we propose a new downlink precoding approach for MU-MIMO systems that also uses codebooks to reduce the information transmitted over a feedback channel. A key aspect of the proposed approach, in contrast to the existing ones, is the transmission of new, uncorrelated information in each cycle, which allows for accumulating CSI with higher accuracy without increasing the feedback overhead. The proposed approach is most effective in systems with dynamic user selection. In such systems, increasing the accuracy of CSI leads to an increase in the number of active users served, which after a few cycles, can reach a maximum value determined by the number of transmit antennas at the BS side. This approach appears to be promising for addressing the challenges associated with current and future massiv
Implementing large antenna arrays for massive multiple-input multiple-output (MIMO) base stations requires transmit radio frequency (RF) chains with low complexity and high power amplifier (PA) efficiency. One approac...
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ISBN:
(纸本)9781728189642
Implementing large antenna arrays for massive multiple-input multiple-output (MIMO) base stations requires transmit radio frequency (RF) chains with low complexity and high power amplifier (PA) efficiency. One approach to achieve this goal is to relax PA linearity and to digitally compensate for some of the resulting non-linear effects such as an increased error vector magnitude (EVM) and adjacent channel leakage ratio (ACLR). The required compensation method can be implemented in a non-linear precoding module that exploits the large spatial degrees of freedom in a massive MIMO system. In this paper, we propose using outphasing RF chains with low-resolution phase shifters to generate constrained amplitude and phase-modulated signals with very low hardware complexity. To improve transmit power efficiency and to control the ACLR and EVM, we develop a novel non-linear precoding algorithm that incorporates the quantized phase-shift constraints in the outphasing RF chains. The achieved flexibility to trade-off EVM and ACLR in favor of a higher PA efficiency (and vice versa) is demonstrated by means of simulations.
The sum rate performance of nonlinier quantized precoding using Gibbs sampling are evaluated in a massive multiuser multiple-input multiple-output (MU-MIMO) system in this paper. Massive MU-MIMO is a key technology to...
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The sum rate performance of nonlinier quantized precoding using Gibbs sampling are evaluated in a massive multiuser multiple-input multiple-output (MU-MIMO) system in this paper. Massive MU-MIMO is a key technology to handle the growth of data traffic. In a full digital massive MU-MIMO system, however, the resolution of digital-to-analogue converters (DACs) in transmit antenna branches have to be low to yield acceptable power consumption. Thus, a combinational optimization problem is solved for the nonlinier quantized precoding to determine transmit signals from finite alphabets output from low resolution DACs. A conventional optimization criterion minimizes errors between desired signals and received signals at user equipments (UEs). However, the system sum rate may decrease as it increases the transmit power. This paper proposes two optimization criteria that take the transmit power into account in order to maximize the sum rate. Mixed Gibbs sampling is applied to obtain the suboptimal solution of the nonlinear optimization problem. Numerical results obtained through computer simulations show that the two proposed criteria achieve higher sum rates than the conventional criterion. On the other hand, the sum rate criterion achieves the largest sum rate while it leads to less throughputs than the MMSE criterion on approximately 60% of subcarriers.
Orthogonal space-time block codes (OSTBCs) are a class of easily decoded space-time codes that achieve full diversity order in Rayleigh fading channels. OSTBCs exist only for certain numbers of transmit antennas and d...
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Orthogonal space-time block codes (OSTBCs) are a class of easily decoded space-time codes that achieve full diversity order in Rayleigh fading channels. OSTBCs exist only for certain numbers of transmit antennas and do not provide array gain like diversity techniques that exploit transmit channel information. When channel state information is available at the transmitter, though, precoding the space-time codeword can be used to support different numbers of transmit antennas and to improve array gain. Unfortunately, transmitters in many wireless systems have no knowledge about current channel conditions. This motivates limited feedback precoding methods such as channel quantization or antenna subset selection. This paper investigates a limited feedback approach that uses a codebook of precoding matrices known a priori to both the transmitter and receiver. The receiver chooses a matrix from the codebook based on current channel conditions and conveys the optimal codebook matrix to the transmitter over an error-free, zero-delay feedback. channel. A criterion for choosing the optimal precoding matrix in the codebook is proposed that relates directly to minimizing the probability of symbol error of the precoded system. Low average distortion codebooks are derived based on the optimal codeword selection criterion. The resulting design is found to relate to the famous applied mathematics problem of subspace packing in the Grassmann manifold. Codebooks designed by this method are proven to provide full diversity order in Rayleigh fading channels. Monte Carlo simulations show that limited feedback precoding performs better than antenna subset selection.
Next-generation wireless communications rely on multiple-input-multiple-output (MIMO) techniques to achieve high data rates. Feedback of channel information can be used in MIMO precoding to fully activate the stronges...
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Next-generation wireless communications rely on multiple-input-multiple-output (MIMO) techniques to achieve high data rates. Feedback of channel information can be used in MIMO precoding to fully activate the strongest channel modes and improve MIMO performance. Unfortunately, the bandwidth of the control channel by which the feedback is conveyed is severely limited. An important issue is how to improve the MIMO precoding performance with minimal feedback. In this paper, we present a method that uses a rotating codebook technique to effectively improve the precoding performance without the need to increase feedback overhead. The basic idea of the rotating codebook precoding is to expend the effective precoding codebook size via rotating multiple codebooks so that the number of feedback bits remains unchanged. Simulation results are presented to show the performance gain of the proposed rotating codebook precoding over conventional precoding.
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