Number Of Spatial Streams Research Articles

High-Performance QC-LDPC Code Co-Processing Approach and VLSI Architecture for Wi-Fi 6

The QC-LDPC code, with its excellent error correction performance and hardware friendliness, has been identified as one of the channel encoding schemes by Wi-Fi 6. Shorting, puncturing, or repeating operations are needed to ensure that user data can be sent with integer symbols and complete rate matching. Due to the uncertainty of the user data size, the modulation’s selectivity, and the difference in the number of spatial streams, the receiver must deal with more than 106 situations. At the same time, other computationally intensive tasks occupy the time slot budget of the receiver. Typical are demodulation and decoding. Hence, the receiver needs to quickly reverse the demodulated data process. This paper first proposes a co-processing method and VLSI architecture compatible with all code lengths, code rates, and processing parameters. The co-processor separates field and block splicing, simplifying the control logic. There is no throughput rate bottleneck, and the maximum delay is less than 1 us.

AARF-HT: Adaptive Auto Rate Fallback for High-Throughput IEEE 802.11n WLANs

Wireless Local Area Network (WLAN) has been progressing rapidly. The IEEE 802.11n Physical (PHY) layer provides wider channel bandwidth, shorter guard interval, and up to four data streams. Therefore PHY 802.11n has a maximum of 128 data rate options from 6.5 Mbps to 600 Mbps. In addition, Medium Access Control (MAC) has been added Aggregate MAC Protocol Data Unit (AMDPU) scheme. If AMPDU is transmitted with a data rate corresponding to the channel conditions, then the probability AMPDU is received without error becomes increased. MAC determines the data rate used for transmitting AMPDU using a rate adaptation algorithm. Therefore some papers have proposed rate adaptation algorithms based on channel conditions. In this paper we propose a new rate adaptation algorithm that we call Adaptive Auto Rate Fallback for High Throughput (AARF-HT). Our development is done using NS-3 simulator version 3.26. AARF-HT algorithm performance is also tested through a number of simulations extensively. The simulation results show the data rate adaptation function based on the channel width, guard interval and the number of spatial streams in IEEE 802.11n WLAN has functioned well. The test results also show the AARF-HT algorithm resulted in higher throughput compared to the AARF algorithm.

Motion-Aware Optimizations for Downlink MU-MIMO in 802.11ax Networks

Multi-User Multiple-Input and Multiple-Output (MU-MIMO) is a technique that allows concurrent transmissions between one access point (AP) and multiple clients to improve spectral efficiency. In practice, however, the MU-MIMO is sensitive to client mobility and is sometimes even harmful to the performance in networks with moving clients. In this paper, we identify that it is essential to optimize the MUMIMO performance with moving clients by jointly selecting the sounding period, the number of spatial streams, and client grouping with the consideration of the client density of the network. We develop a data-driven model that estimates client throughput with the consideration of these parameters, as well as an algorithm that jointly determines the parameters for each client with low computational complexity. Using a commodity 802.11ax network, we experimentally demonstrate the significant impact of the key factors on MU-MIMO performance. Based on experimental data, we develop an emulation model to evaluate network performance with different client densities and mobility. Emulation results show that our proposed algorithm outperforms conventional schemes by over 20% in MU-MIMO networks with moving clients.

Multi-User Multi-Stream mmWave WLANs With Efficient Path Discovery and Beam Steering

Multi-stream 60 GHz communication can potentially achieve data rates up to 100 Gbps via multiplexing multiple data streams. Unfortunately, establishing multi-stream directional links is a high overhead procedure as the search space increases with the number of spatial streams and the product of AP-client beam resolution. In this paper, we present MUlti-stream beam-Training for mm-wavE networks (MUTE) a novel system that leverages channel sparsity, GHz-scale sampling rate, and the knowledge of mm-Wave RF codebook beam patterns to construct a set of candidate beams for efficient multi-stream beam steering. MUTE repurposes the mandatory periodic beam sweeps in 60 GHz WLANs to discover the dominant paths of the mmWave channel between the AP and any client with zero additional overhead. Coupling path estimates with beam pattern knowledge, MUTE selects a set of candidate beams that capture diverse or ideally orthogonal paths to obtain maximum stream separability. Our over-the-air experiments demonstrate that MUTE achieves 90% of the maximum achievable aggregate PHY rate while incurring only 1.2% of exhaustive search’s training overhead.

AARF-HT: Adaptive Auto Rate Fallback for High-Throughput IEEE 802.11n WLANs

Wireless Local Area Network (WLAN) has been progressing rapidly. The IEEE 802.11n Physical (PHY) layer provides wider channel bandwidth, shorter guard interval, and up to four data streams. Therefore PHY 802.11n has a maximum of 128 data rate options from 6.5 Mbps to 600 Mbps. In addition, Medium Access Control (MAC) has been added Aggregate MAC Protocol Data Unit (AMDPU) scheme. If AMPDU is transmitted with a data rate corresponding to the channel conditions, then the probability AMPDU is received without error becomes increased. MAC determines the data rate used for transmitting AMPDU using a rate adaptation algorithm. Therefore some papers have proposed rate adaptation algorithms based on channel conditions. In this paper we propose a new rate adaptation algorithm that we call Adaptive Auto Rate Fallback for High Throughput (AARF-HT). Our development is done using NS-3 simulator version 3.26. AARF-HT algorithm performance is also tested through a number of simulations extensively. The simulation results show the data rate adaptation function based on the channel width, guard interval and the number of spatial streams in IEEE 802.11n WLAN has functioned well. The test results also show the AARF-HT algorithm resulted in higher throughput compared to the AARF algorithm.

System Level Study of LTE-Advanced Multiple Antenna System with Inter-Band Carrier Aggregation

Spatial Multiplexing (SM) multiple antenna systems and Carrier Aggregation (CA) are techniques introduced in Long Term Evolution- Advanced (LTE−Advanced) to support high data rates by increasing the number of transmission paths and the available bandwidth respectively. Therefore, in this study we evaluate the performance of LTE-Advanced physical downlink shared channel for single and SM multiple antenna systems in two different frequency bands. The radio channel is modelled using an enhanced Three-Dimensional (3D) international telecommunication union-radio communication sector channel model integrated with base station and user mobile 3D antenna patterns. Except the total received power, similar channel statistics are observed for both frequency bands. The study is performed considering 1x1, 2x2, 4x4 antenna systems in a macro-cell urban environment at Component Carries (CC) of 2600 MHz and 800 MHz to model bands 7 and 20 of CA_7-20 respectively. The performance is evaluated in terms of throughput and SM gain for many base stations and user positions considering various modulation and coding schemes. We used the computationally efficient received bit information rate algorithm to compute the throughput as a function of channel structure and signal to noise ratio. As expected higher throughput is observed for the 800 MHz band over the 2600 MHz band. This is due to the higher total received power of the 800 MHz band. The novel SM gain results show that the SM gain depends on the operating band and it’s less than the number of spatial links. Moreover, the efficiency of inter-band CA in increasing the data rates is a function cell radius and the number of spatial streams.

Modulation Coding Scheme Performance Analysis (Mcs) Wireless 802.11ac Indoor At 5 Ghz Frequency In West And East Telecommunication Labs Politechnic State Of Semarang

Modulation Coding Scheme or MCS is a value that specifies the modulation, coding and number of spatial streams and produces a fixed rate data rate based on channel conditions and RSSI values received by the user. Modulation on MCS there are 5 kinds of BPSK, QPSK, 16 QAM, 64 QAM and 256 QAM. While the coding rate there are 4 kinds of ½, 2/3, ¾ and 5/6. MCS and RSSI. Changes can not be separated from wireless propagation that includes Large Scale Propagation and Small Scale Fading in particular the existence of obstacles in the form of objects and indoor or outdoor areas. Test results show that major changes to RSSI are influenced by indoor or outdoor areas. MCS changes are uncertain and not RSSI based. MCS and RSSI will change based on channel conditions.

Higher Rank Interference Effect on Weak Beamforming or OSTBC Terminals

Spatial multiplexing is one of the multi-antenna techniques employed by current generation wireless systems. Based on existing research, spatial multiplexing is known to be susceptible to interference. However, it is not well known what the effect of spatial multiplexing on other transmissions is, i.e., how does user performance depend on whether a neighboring cochannel interferer applies a single (spatial) stream or a multi stream transmission. This work attempts to alleviate this shortcoming by analyzing the impact of interference rank (number of spatial streams) on a beamforming and orthogonal space-time block coded user transmission. We generalize existing analytical results on signal-to-interference-plus-noise-ratio distribution and outage probability under arbitrary number of unequal power interferers. Our results are in close form and include interference rank as a parameter, allowing for a thorough study of its impact. Analysis shows that higher rank interference causes lower outage probability, and can support higher outage threshold especially in the case of beamforming.

Efficient Soft-Input Soft-Output MIMO Chase Detectors for Arbitrary Number of Streams

We present novel soft-input soft-output (SISO) multiple-input multiple-output (MIMO) detectors based on the Chase detection principle [1] in the context of iterative and decoding (IDD). The proposed detector complexity is linear in the signal modulation constellation size and the number of spatial streams. Two variants of the SISO detector are developed, referred to as SISO B-Chase and SISO L-Chase. An efficient method is presented that uses the decoder output to modulate the signal constellation decision boundaries inside the detector leading to the SISO detector architecture. The performance of these detectors significantly improves with just a few number of IDD iterations. The effect of transmit and receive antenna correlation is simulated. For the high-correlation case, the superiority of SISO B-Chase over the SISO L-Chase is demonstrated.

고차 변조 방식을 사용하는 MIMO 시스템을 위한 낮은 복잡도를 갖는 연판정 알고리즘

최적 ML(Maximum Likelihood) 기법 및 sphere decoding(SD), QRM-MLD(QR decomposition with M-algorithm Maximum Likelihood Detection) 기반의 준 최적 검출 기법을 적용한 MIMO(Multiple-Input Multiple-Output) 시스템에서의 LLR(Log Likelihood Ratio) 계산은 변조 차수 및 송/수신 안테나의 수가 증가할수록 그 복잡도가 지수적으로 증가하여 구현 및 성능 면에서 큰 문제점을 야기한다. 본 논문에서는 고차 변조 방식 기반의 <TEX>$N_T{\times}N_R$</TEX> MIMO시스템 수신기의 QRM-MLD 기반 MIMO 검출기에서 연판정 시 아주 낮은 복잡도로 1dB 이내의 ML 검출 기법에 대한 오류 성능 접근도를 갖는 LLR 계산 방법을 제시하고, 컴퓨터 시뮬레이션을 통해 여러 M 값에 대한 MIMO 시스템의 BER(Bit Error Rate) 결과를 도출하고 분석하여 제시된 방법의 유효성을 검증한다. In a log likelihood ratio(LLR) calculation of the detected symbol, multiple-input multiple-output(MIMO) system applying an optimal or suboptimal algorithm such as a maximum likelihood(ML) detection, sphere decoding(SD), and QR decomposition with M-algorithm Maximum Likelihood Detection(QRM-MLD) suffers from exponential complexity growth with number of spatial streams and modulation order. In this paper, we propose a LLR calculation method with very low complexity in the QRM-MLD based symbol detector for a high order modulation based <TEX>$N_T{\times}N_R$</TEX> MIMO system. It is able to approach bit error rate(BER) performance of full maximum likelihood detector to within 1 dB. We also analyze the BER performance through computer simulation to verify the validity of the proposed method.

Energy-Constrained Link Adaptation for MIMO OFDM Wireless Communication Systems

We present a link adaptation strategy for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) based wireless communications. Our objective is to choose the optimal mode that will maximize energy efficiency or data throughput subject to a given quality of service (QoS) constraint. We formulate the link adaptation problem as a convex optimization problem and expand the set of parameters under the control of the link adaptation protocol to include: number of spatial streams, number of transmit/receive antennas, use of spatial multiplexing or space time block coding (STBC), constellation size, bandwidth, transmit power and choice of maximum likelihood (ML) or zero-forcing (ZF) for MIMO decoding. Additionally, we increase the fidelity of the energy consumption modeling relative to the prior art. The resulting solution allows us to easily and quickly search the space of possible system parameters to deliver on the QoS with minimal energy consumption. Moreover, it provides us insight into where crossovers occur in the choice of the radio parameters. Application of the results to a generic MIMO-OFDM radio shows that the proposed strategy can provide an order of magnitude improvement in energy efficiency or data throughput relative to a static strategy.

Performance of Spatial Division Multiplexing MIMO with Frequency Domain Packet Scheduling: From Theory to Practice

This paper addresses the performance of spatial division multiplexing (SDM) multiple-input multiple-output (MIMO) techniques together with frequency domain packet scheduling (FDPS) in both theory and practice. We start with a theoretical analysis under some ideal assumptions to derive the performance bounds of SDM-FDPS. To facilitate the analysis, a unified SINR concept is utilized to make a fair comparison of MIMO schemes with different number of spatial streams. The effect of packet scheduling is included in the post-scheduling SINR distribution using an analytical model. Based on that, the performance bounds are obtained with a more realistic SINR to throughput mapping metric. The system-level performance of SDM-FDPS has been evaluated under practical constraints using detailed simulations based on the UTRAN long term evolution (LTE) downlink cellular system framework. The purpose is to investigate the impact of realistic factors on performance. Results confirm that the combination of SDM and FDPS can increase the spectral efficiency significantly, particularly in a micro-cell scenario, and up to 30%-60% gain is observed over 1times2 with FDPS depending on the traffic models considered. Finally, the more practical simulation results are compared against the theoretical performance bounds. A performance loss is seen in the simulations due to realistic coding/modulation, impact of frequency selectivity, signalling constraints, imperfect channel quality indicator (CQI), etc.

Spatial-Mode Selection for the Joint Transmit and Receive MMSE Design

To approach the potential MIMO capacity while optimizing the system bit error rate (BER) performance, the joint transmit and receive minimum mean squared error (MMSE) design has been proposed. It is the optimal linear scheme for spatial multiplexing MIMO systems, assuming a fixed number of spatial streams p as well as a fixed modulation and coding across these spatial streams. However, state-of-the-art designs arbitrarily choose and fix the value of the number of spatial streams p, which may lead to an inefficient power allocation strategy and a poor BER performance. We have previously proposed to relax the constraint of fixed number of streams p and to optimize this value under the constraints of fixed average total transmit power and fixed spectral efficiency, which we referred to as spatial-mode selection. Our previous selection criterion was the minimization of the system sum MMSE. In the present contribution, we introduce a new and better spatial-mode selection criterion that targets the minimization of the system BER. We also provide a detailed performance analysis, over flat-fading channels, that confirms that our proposed spatial-mode selection significantely outperforms state-of-the-art joint Tx/Rx MMSE designs for both uncoded and coded systems, thanks to its better exploitation of the MIMO spatial diversity and more efficient power allocation.