FPGA实现的MIMO-OFDM物理层高效原型设计

需积分: 10 199 浏览量更新于2024-09-15 收藏 649KB PDF 举报

本文主要探讨了高效FPGA基础下的多输入多输出(MIMO)正交频分复用(OFDM)物理层实现。随着无线通信速率的持续提升，从一代到下一代技术至少增长了四倍，OFDM技术在其中发挥了关键作用。802.11ac标准就是一个显著的例子，它依赖于OFDM来提供高速数据传输。作者Jeoong S. Park、Hong-Jip Jung和Viktor K. Prasanna来自南加州大学洛杉矶分校，他们针对MIMO-OFDM系统的硬件效率提出了创新的解决方案。论文的核心内容是提出了一种基于FPGA的流水线架构，该架构利用共享的快速傅立叶变换（FFT）模块，能够支持多种调制方式，从而节省硬件资源。实验结果显示，与已知的基线MIMO-OFDM实现相比，该设计能够节省至少30%的硬件资源，同时保持相同的传输速率。进一步的性能分析表明，通过优化设计，数据传输速率可以翻倍，而所需的硬件资源基本保持不变。这显示出FPGA在处理高带宽需求和多模态通信方面的巨大潜力。此外，文中还强调了动态重新配置在MIMO-OFDM系统中的重要性，这种灵活性使得系统能够根据无线环境的变化实时调整其架构，提高了整体效率和适应性。关键词：MIMO、OFDM、FPGA 在实际应用中，通过高效的FPGA设计，MIMO-OFDM技术能够满足现代无线网络对于高速、低延迟和资源利用率高的需求。这样的设计不仅降低了硬件成本，也提升了系统的可扩展性和可靠性。未来的研究可能集中在如何进一步优化动态配置策略，以及探索更先进的硬件架构，以应对不断增长的数据流量和更高的多路复用技术挑战。这篇论文为FPGA在5G和下一代无线通信系统中的关键角色提供了有价值的设计策略和理论支持。

Figure 2: Transmitter data ﬂow (Symbols are 32 bit complex numbers)

Figure 3: Receiver data ﬂow ( Symbols are 32 bit complex numbers)

Guard Interval Insertion: The 64 complex outputs of

the IFFT kernel are extended to form an array of 80

complex numbers by copying the last 16 outputs as the

guard interval prior to the ﬁrst IFFT output. As previously

mentioned, this kernel is needed to avoid ISI.

Training Symbol Insertion: To help the receiver esti-

mate the eﬀects of noise and distortion in wireless channels,

the transmitter inserts small, ﬁxed length of training

symbols before transmission. In Figure 2 and 3, the kernels

used for signal recovery are ﬁlled in gray color.

2.3.2 Kernels in the Receiver

We present explanations for the only two kernels in the

receiver without counterparts in the transmitter.

Time and Frequenc y Recovery: This kernel is com-

posed of packet detection, time synchronization, and

frequency correction. Packet detection roughly identiﬁes

transmitted signals and time synchronization exactly

distinguishes transmitted signals from noise signals.

Frequency correction estimates frequency error in the orig-

inal t ransmitted signals, and recovers the original frequency.

Channel Estimation: As explained in Section 2.1,

there are multiple sub-carriers used by OFDM technology.

Each sub-carrier is located at a particular frequency.

Wireless channels aﬀect on these sub-carriers to varying

degrees. In the ideal channel case, this gain is 1 for all

sub-carriers. However, for the real channel environment,

the channel esti m ation block estimates the amount of gain

change, and recovers the original gain for each sub-carrier.

Dynamic reconﬁguration can be used in MIMO-OFDM

systems to change data rate, increase diversity, or increase

range. This idea is applied to three kernels: puncturing

(depuncturing), QAM mapping (QAM demapping) , and

parsing (deparsing). A detailed analysis of dynamic

reconﬁguration is presented in Section 4.

3 P ipelined Architecture for

MIMO-OFDM

3.1 Deﬁnitions

Before we describe our proposed architecture, we brieﬂy

deﬁne several terms and notations used in this paper.

N × M MIMO-OFDM : N indicates the number of

transmitter antennas and M indicates the number of

receiver antennas, respectively. For example, 3 × 3 MIMO-

OFDM has 3 transmitter antennas and 3 receiver antennas

as shown in Figure 1.

Baseline MIMO-OFDM : A MIMO-OFDM system that

uses as many IFFT blocks (or FFT blocks) as antennas in

the transmitter (or receiver). This simple idea conforms

with t he basic theory of MIMO-OFDM, which suggests

that multiple data streams are modulated by their own

FFT blocks [22].

Way: The number of antennas that can be supported by

the proposed pipelined architecture with one FFT. For

example, 2-W ay means that the proposed system achieves

the same data rate as the baseline 2 × 2 MIMO-OFDM

system with two FFT blocks, as shown in Figure 5.

Pipeline sta ge period : The period of a pipeline stage.

In our pipelined architecture, this period is 4 µsec given by

existing OFDM standard [1]. The number of clocks (C

P ipe

)

for this period varies with the system clock frequency. For

剩余10页未读，继续阅读

sotusotu

粉丝: 0
资源: 2

FPGA实现的MIMO-OFDM物理层高效原型设计

Programming Environments Manual for 32-Bit Implementations of the PowerPC™ Architecture

Single-file implementations of 2D and 3D acoustic and elastic

StreamBit: Sketching high-performance implementations of bitstream programs

Machine-Learning-implementations-based-on-MachineLearningR-by-Brett-Lantz

Real-Time Digital Signal Processing--Implementations

Real-Time-Digital-Signal-Processing-Implementations-Application-and-Experiments-with-the-TMS320C55X

matlab代码sqrt-Implementations-of-Digital-and-wireless-communication-syst

algorithms-and-data-structures-implementations

leetcodepushfront-My-Algorithms-and-Data-Structures-Implementations-In-

Design Of Energy-Efficient Application-Specific Instruction Set Processors

最新资源