Abstract
Abstract. In search for faster and more reliable communication, multiple-input multiple-output (MIMO) in conjuction with Orthogonal Frequency Division Multiplexing (OFDM) are subject of extensive research. In spatial multiplexing transmission an instantaneous rise of data rates governed by the number of transmit antennas can be realised. The system performance depends highly on signal-to-interference-plus-noise ratios (SINR) at the receiver. The receiver's equaliser is supposed to maximize the SINR by mitigating the spatial interference and thus separating the transmitted signals. For this problem several solutions exist such as linear and nonlinear, per subcarrier or OFDM symbol-based. An overview of common algorithms is given and complexity is discussed. Bit error rate (BER) performance evaluations are presented. Another aspect is the impact of the equalisation strategy on the performance of bit-interleaved soft information-based channel coding schemes. As a representative, LDPC codes are chosen. Simulation results show a significant BER performance loss for symbol decision-based equalisers compared to the uncoded performance. To overcome this problem a modification of the Maximum Likelihood algorithm is proposed which yields good performance for low SNR applications.
Highlights
In upcoming multiple-input multiple-output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems Spatial Multiplexing is an convenient way to linearly increase bandwidth efficiency with the number of transmit and receive antennas primary at the expense of higher SNR demands
Mobile scenarios are a particular challenge. This is partly due to outdated channel state information (CSI) as well as the fact that many receivers neglect the time-variant behaviour of the channel during a frame and even OFDM symbol
The vector of received values r at the time sample m of a MIMO system is the superposition of L · nT previously sent samples and the current nT samples, where L+1 is the length of the sampled channel impulse response and nT is the number of transmit antennas
Summary
In upcoming MIMO OFDM systems Spatial Multiplexing is an convenient way to linearly increase bandwidth efficiency with the number of transmit and receive antennas primary at the expense of higher SNR demands. This is partly due to outdated channel state information (CSI) as well as the fact that many receivers neglect the time-variant behaviour of the channel during a frame and even OFDM symbol. The multiple, independent OFDM send signals are superposed in the wireless channel, modelled by a channel matrix and additive, white gaussian noise (AWGN). The signals are convoluted by a time-varying channel matrix that results in a nonlinear system model. Simulation results based on 3GPP MIMO Spatial Channel Model show the detection performance over SNR for a range of velocities. The underlying system model in time and frequency-domain, as well as a vectorised representation are presented, followed by a brief review of per layer MIMO detection algorithms in Sect. 5. The paper is concluded by illustrating simulation results in Sect.
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