Effects of iterative detection and decoding on the performance of BLAST

Li, X.; Huang, Haiyang; Foschini, G.J.; Valenzuela, R.A.

doi:10.1109/glocom.2000.891300

Cited by 87 publications

(48 citation statements)

References 16 publications

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“…When the MIMO technique of spatial multiplexing is applied [8], encoding can be done either jointly over the multiple transmitter branches or per branch [12]. The latter option is chosen as the encoding scheme in this paper and is called per-antenna-coding (PAC).…”

Section: System Descriptionmentioning

confidence: 99%

“…Since synchronization is an essential task for any digital communication system and required for reliable reception of the transmitted data, this paper provides an overview of the necessary changes to the preamble, time and frequency synchronization, channel estimation, and synchronization tracking. Furthermore, enhanced MIMO detection algorithms are proposed, based on per-antenna-coding (PAC) (sometimes called horizontal coding [12]) at the transmitter, i.e., PAC soft-output maximum likelihood detection (MLD) and PAC V-BLAST. Finally, to verify the proposed synchronization and detection algorithms, the bit error rate (BER) and packet error rate (PER) performance of the total implementation are evaluated both with simulations and initial measurements.…”

mentioning

confidence: 99%

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Implementation of a MIMO OFDM-Based Wireless LAN System

Zelst

Schenk

2004

IEEE Trans. Signal Process.

355

172

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Abstract-The combination of multiple-input multiple-output (MIMO) signal processing with orthogonal frequency division multiplexing (OFDM) is regarded as a promising solution for enhancing the data rates of next-generation wireless communication systems operating in frequency-selective fading environments. To realize this extension of OFDM with MIMO, a number of changes are required in the baseband signal processing. An overview is given of the necessary changes, including time and frequency synchronization, channel estimation, synchronization tracking, and MIMO detection. As a test case, the OFDM-based wireless local area network (WLAN) standard IEEE 802.11a is considered, but the results are applicable more generally. The complete MIMO OFDM processing is implemented in a system with three transmit and three receive antennas, and its performance is evaluated with both simulations and experimental test results. Results from measurements with this MIMO OFDM system in a typical office environment show, on average, a doubling of the system throughput, compared with a single antenna OFDM system. An average expected tripling of the throughput was most likely not achieved due to coupling between the transmitter and receiver branches.Index Terms-MIMO systems, orthogonal frequency division multiplexing (OFDM), space division multiplexing, synchronization, wireless LAN.

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Section: System Descriptionmentioning

confidence: 99%

mentioning

confidence: 99%

Implementation of a MIMO OFDM-Based Wireless LAN System

Zelst

Schenk

2004

IEEE Trans. Signal Process.

355

172

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“…In [11], two coding architectures, vertical coding and horizontal coding, are proposed for BLAST systems. In this paper, we consider the vertical coding with binary linear codes, where a binary linear code is used to encode all the data bits going to different antennas.…”

Section: Linear Programming Decoding For Coded Mimo Systemsmentioning

confidence: 99%

“…If the minimum of (11) is not zero, the child problem is infeasible. Typically, only a few pivots are required to solve (11), much fewer than the number needed by the phase I in standard simplex algorithm. This technique can also be applied to Algorithm 2.…”

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confidence: 99%

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Linear Programming Detection and Decoding for MIMO Systems

Cui

Tellambura

2006

2006 IEEE International Symposium on Information Theory

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Abstract-1 We develop an efficient linear programming detector (LPD) for multiple-input multiple-output (MIMO) systems. Instead of using the usual l2 norm, our proposed LPD uses the l1 norm as the detection metric, resulting in a mixed-integer linear program (MILP). Two branch-and-bound algorithms are proposed to solve the MILP. The solution of the MILP achieves the same full diversity order as the maximum likelihood detector. The MILP is further relaxed to a linear program (LP), which can be readily solved using the standard simplex method. We show that in some cases the solution of the LP is guaranteed to be that of the MILP. The LPD is also extended to the joint detection and decoding of linear block coded MIMO systems. Our LPD can be immediately implemented using mature circuits design for the simplex algorithm.

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A Low Complexity Iterative Receiver based on Successive Cancellation for MIMO

Claußen

Karimi²,

Mulgrew

2003

Mobile and Wireless Communications

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Turbo-encoded mUltiple-input multiple-output (MIMO) systems have recently been proposed for the support of high-speed downlink packet access (HSDPA) in UMTS, where the re-use of spreading codes across the transmitter antennas results in high levels of interference. The state of the art receiver for this system incorporates a channel equalizer, followed by an a posteriori probability (APP) detector and a turbo decoder. However, the complexity of APP detection can become prohibitive since it grows exponentially with the number of transmitter antennas and the modulation order. In this paper, a MIMO receiver is proposed which replaces the optimum but complex APP detector by successive interference cancellation (SIC) incorporating sub-optimal matched filter detection. Using convolutional encoding at the transmitter, the receiver performance is sustained via iterations between the simplified detector and the convolutional decoder. In combination with a proposed novel soft-output combining scheme, it is shown that the new receiver can outperform the APP-based receiver at a much lower complexity and with no need for channel equalization.

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Effects of iterative detection and decoding on the performance of BLAST

Cited by 87 publications

References 16 publications

Implementation of a MIMO OFDM-Based Wireless LAN System

Implementation of a MIMO OFDM-Based Wireless LAN System

Linear Programming Detection and Decoding for MIMO Systems

A Low Complexity Iterative Receiver based on Successive Cancellation for MIMO

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