1,272 research outputs found
Receiver Architectures for MIMO-OFDM Based on a Combined VMP-SP Algorithm
Iterative information processing, either based on heuristics or analytical
frameworks, has been shown to be a very powerful tool for the design of
efficient, yet feasible, wireless receiver architectures. Within this context,
algorithms performing message-passing on a probabilistic graph, such as the
sum-product (SP) and variational message passing (VMP) algorithms, have become
increasingly popular.
In this contribution, we apply a combined VMP-SP message-passing technique to
the design of receivers for MIMO-ODFM systems. The message-passing equations of
the combined scheme can be obtained from the equations of the stationary points
of a constrained region-based free energy approximation. When applied to a
MIMO-OFDM probabilistic model, we obtain a generic receiver architecture
performing iterative channel weight and noise precision estimation,
equalization and data decoding. We show that this generic scheme can be
particularized to a variety of different receiver structures, ranging from
high-performance iterative structures to low complexity receivers. This allows
for a flexible design of the signal processing specially tailored for the
requirements of each specific application. The numerical assessment of our
solutions, based on Monte Carlo simulations, corroborates the high performance
of the proposed algorithms and their superiority to heuristic approaches
Multiuser MIMO-OFDM for Next-Generation Wireless Systems
This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems
Channel Hardening-Exploiting Message Passing (CHEMP) Receiver in Large-Scale MIMO Systems
In this paper, we propose a MIMO receiver algorithm that exploits {\em
channel hardening} that occurs in large MIMO channels. Channel hardening refers
to the phenomenon where the off-diagonal terms of the matrix
become increasingly weaker compared to the diagonal terms as the size of the
channel gain matrix increases. Specifically, we propose a message
passing detection (MPD) algorithm which works with the real-valued matched
filtered received vector (whose signal term becomes ,
where is the transmitted vector), and uses a Gaussian approximation
on the off-diagonal terms of the matrix. We also propose a
simple estimation scheme which directly obtains an estimate of (instead of an estimate of ), which is used as an effective
channel estimate in the MPD algorithm. We refer to this receiver as the {\em
channel hardening-exploiting message passing (CHEMP)} receiver. The proposed
CHEMP receiver achieves very good performance in large-scale MIMO systems
(e.g., in systems with 16 to 128 uplink users and 128 base station antennas).
For the considered large MIMO settings, the complexity of the proposed MPD
algorithm is almost the same as or less than that of the minimum mean square
error (MMSE) detection. This is because the MPD algorithm does not need a
matrix inversion. It also achieves a significantly better performance compared
to MMSE and other message passing detection algorithms using MMSE estimate of
. We also present a convergence analysis of the proposed MPD
algorithm. Further, we design optimized irregular low density parity check
(LDPC) codes specific to the considered large MIMO channel and the CHEMP
receiver through EXIT chart matching. The LDPC codes thus obtained achieve
improved coded bit error rate performance compared to off-the-shelf irregular
LDPC codes
AirSync: Enabling Distributed Multiuser MIMO with Full Spatial Multiplexing
The enormous success of advanced wireless devices is pushing the demand for
higher wireless data rates. Denser spectrum reuse through the deployment of
more access points per square mile has the potential to successfully meet the
increasing demand for more bandwidth. In theory, the best approach to density
increase is via distributed multiuser MIMO, where several access points are
connected to a central server and operate as a large distributed multi-antenna
access point, ensuring that all transmitted signal power serves the purpose of
data transmission, rather than creating "interference." In practice, while
enterprise networks offer a natural setup in which distributed MIMO might be
possible, there are serious implementation difficulties, the primary one being
the need to eliminate phase and timing offsets between the jointly coordinated
access points.
In this paper we propose AirSync, a novel scheme which provides not only time
but also phase synchronization, thus enabling distributed MIMO with full
spatial multiplexing gains. AirSync locks the phase of all access points using
a common reference broadcasted over the air in conjunction with a Kalman filter
which closely tracks the phase drift. We have implemented AirSync as a digital
circuit in the FPGA of the WARP radio platform. Our experimental testbed,
comprised of two access points and two clients, shows that AirSync is able to
achieve phase synchronization within a few degrees, and allows the system to
nearly achieve the theoretical optimal multiplexing gain. We also discuss MAC
and higher layer aspects of a practical deployment. To the best of our
knowledge, AirSync offers the first ever realization of the full multiuser MIMO
gain, namely the ability to increase the number of wireless clients linearly
with the number of jointly coordinated access points, without reducing the per
client rate.Comment: Submitted to Transactions on Networkin
非直交多元接続のための高信頼空間変調
マルチユーザ空間変調(SM: Spatial Modulation)では,SM信号の疎性を用いた圧縮センシングによるマルチユーザ検出が研究されているものの,受信機においてチャネル情報が完全に既知であるという条件の下で議論されている.実際には受信機側でチャネル情報を推定し,推定したチャネル情報を用いて復調処理を行う.推定したチャネル情報の精度は復調の精度に影響を及ぼすため,チャネル推定は重要なものであり考慮しなければならない. そこで本研究ではチャネル推定を,ブロックスパース性を有する信号の再構成問題として扱い,ブロックスパース性を考慮した複素数近似メッセージ伝播法(BS-CAMP: Block-Sparse Complex Approximate Message Passing)によって信号の再構成を行う方法を提案する.BS-CAMPは受信機が送信信号に含まれる非零要素の個数を事前に知る必要がない再構成アルゴリズムとなっており,ランダムアクセス方式にも適用可能である.計算機シミュレーションより,BS-CAMPによるチャネル推定の精度やスループット特性への影響を示す. さらに,高信頼な通信を実現するにはチャネル推定だけでなく誤り訂正符号が重要となる.そこで併せて本研究ではSMに誤り訂正符号化を組み合わせたものの一つである,ターボトレリス符号化空間変調(SM-TTC: SM with Turbo Trellis-Coding)における符号の最適化及び性能解析を行った.具体的には,シンボルベースEXIT(Extrinsic Information Transfer)チャートを用いた低演算符号探索法によって,演算量を低減しながら最良の特性を示す符号を探索する.計算機シミュレーションより,探索した符号を用いたSM-TTCが従来のものよりも優れていること,および提案手法が従来の符号探索法よりも低計算量で符号探索が可能であることを示す.電気通信大学201
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