2,884 research outputs found
Design guidelines for spatial modulation
A new class of low-complexity, yet energyefficient Multiple-Input Multiple-Output (MIMO) transmission techniques, namely the family of Spatial Modulation (SM) aided MIMOs (SM-MIMO) has emerged. These systems are capable of exploiting the spatial dimensions (i.e. the antenna indices) as an additional dimension invoked for transmitting information, apart from the traditional Amplitude and Phase Modulation (APM). SM is capable of efficiently operating in diverse MIMO configurations in the context of future communication systems. It constitutes a promising transmission candidate for large-scale MIMO design and for the indoor optical wireless communication whilst relying on a single-Radio Frequency (RF) chain. Moreover, SM may also be viewed as an entirely new hybrid modulation scheme, which is still in its infancy. This paper aims for providing a general survey of the SM design framework as well as of its intrinsic limits. In particular, we focus our attention on the associated transceiver design, on spatial constellation optimization, on link adaptation techniques, on distributed/ cooperative protocol design issues, and on their meritorious variants
Multiple Beamforming with Perfect Coding
Perfect Space-Time Block Codes (PSTBCs) achieve full diversity, full rate,
nonvanishing constant minimum determinant, uniform average transmitted energy
per antenna, and good shaping. However, the high decoding complexity is a
critical issue for practice. When the Channel State Information (CSI) is
available at both the transmitter and the receiver, Singular Value
Decomposition (SVD) is commonly applied for a Multiple-Input Multiple-Output
(MIMO) system to enhance the throughput or the performance. In this paper, two
novel techniques, Perfect Coded Multiple Beamforming (PCMB) and Bit-Interleaved
Coded Multiple Beamforming with Perfect Coding (BICMB-PC), are proposed,
employing both PSTBCs and SVD with and without channel coding, respectively.
With CSI at the transmitter (CSIT), the decoding complexity of PCMB is
substantially reduced compared to a MIMO system employing PSTBC, providing a
new prospect of CSIT. Especially, because of the special property of the
generation matrices, PCMB provides much lower decoding complexity than the
state-of-the-art SVD-based uncoded technique in dimensions 2 and 4. Similarly,
the decoding complexity of BICMB-PC is much lower than the state-of-the-art
SVD-based coded technique in these two dimensions, and the complexity gain is
greater than the uncoded case. Moreover, these aforementioned complexity
reductions are achieved with only negligible or modest loss in performance.Comment: accepted to journa
Golden Coded Multiple Beamforming
The Golden Code is a full-rate full-diversity space-time code, which achieves
maximum coding gain for Multiple-Input Multiple-Output (MIMO) systems with two
transmit and two receive antennas. Since four information symbols taken from an
M-QAM constellation are selected to construct one Golden Code codeword, a
maximum likelihood decoder using sphere decoding has the worst-case complexity
of O(M^4), when the Channel State Information (CSI) is available at the
receiver. Previously, this worst-case complexity was reduced to O(M^(2.5))
without performance degradation. When the CSI is known by the transmitter as
well as the receiver, beamforming techniques that employ singular value
decomposition are commonly used in MIMO systems. In the absence of channel
coding, when a single symbol is transmitted, these systems achieve the full
diversity order provided by the channel. Whereas this property is lost when
multiple symbols are simultaneously transmitted. However, uncoded multiple
beamforming can achieve the full diversity order by adding a properly designed
constellation precoder. For 2 \times 2 Fully Precoded Multiple Beamforming
(FPMB), the general worst-case decoding complexity is O(M). In this paper,
Golden Coded Multiple Beamforming (GCMB) is proposed, which transmits the
Golden Code through 2 \times 2 multiple beamforming. GCMB achieves the full
diversity order and its performance is similar to general MIMO systems using
the Golden Code and FPMB, whereas the worst-case decoding complexity of
O(sqrt(M)) is much lower. The extension of GCMB to larger dimensions is also
discussed.Comment: accepted to conferenc
Generalized Spatial Modulation in Large-Scale Multiuser MIMO Systems
Generalized spatial modulation (GSM) uses transmit antenna elements but
fewer transmit radio frequency (RF) chains, . Spatial modulation (SM)
and spatial multiplexing are special cases of GSM with and
, respectively. In GSM, in addition to conveying information bits
through conventional modulation symbols (for example, QAM), the
indices of the active transmit antennas also convey information bits.
In this paper, we investigate {\em GSM for large-scale multiuser MIMO
communications on the uplink}. Our contributions in this paper include: ()
an average bit error probability (ABEP) analysis for maximum-likelihood
detection in multiuser GSM-MIMO on the uplink, where we derive an upper bound
on the ABEP, and () low-complexity algorithms for GSM-MIMO signal detection
and channel estimation at the base station receiver based on message passing.
The analytical upper bounds on the ABEP are found to be tight at moderate to
high signal-to-noise ratios (SNR). The proposed receiver algorithms are found
to scale very well in complexity while achieving near-optimal performance in
large dimensions. Simulation results show that, for the same spectral
efficiency, multiuser GSM-MIMO can outperform multiuser SM-MIMO as well as
conventional multiuser MIMO, by about 2 to 9 dB at a bit error rate of
. Such SNR gains in GSM-MIMO compared to SM-MIMO and conventional MIMO
can be attributed to the fact that, because of a larger number of spatial index
bits, GSM-MIMO can use a lower-order QAM alphabet which is more power
efficient.Comment: IEEE Trans. on Wireless Communications, accepte
Dispensing with channel estimation: differentially modulated cooperative wireless communications
As a benefit of bypassing the potentially excessive complexity and yet inaccurate channel estimation, differentially encoded modulation in conjunction with low-complexity noncoherent detection constitutes a viable candidate for user-cooperative systems, where estimating all the links by the relays is unrealistic. In order to stimulate further research on differentially modulated cooperative systems, a number of fundamental challenges encountered in their practical implementations are addressed, including the time-variant-channel-induced performance erosion, flexible cooperative protocol designs, resource allocation as well as its high-spectral-efficiency transceiver design. Our investigations demonstrate the quantitative benefits of cooperative wireless networks both from a pure capacity perspective as well as from a practical system design perspective
Generalized feedback detection for spatial multiplexing multi-antenna systems
We present a unified detection framework for spatial multiplexing multiple-input multiple-output (MIMO) systems by generalizing Heller’s classical feedback decoding algorithm for convolutional codes. The resulting generalized feedback detector (GFD) is characterized by three parameters: window size, step size and branch factor. Many existing MIMO detectors are turned out to be special cases of the GFD. Moreover, different parameter choices can provide various performance-complexity tradeoffs. The connection between MIMO detectors and tree search algorithms is also established. To reduce redundant computations in the GFD, a shared computation technique is proposed by using a tree data structure. Using a union bound based analysis of the symbol error rates, the diversity order and signal-to-noise ratio (SNR) gain are derived analytically as functions of the three parameters; for example, the diversity order of the GFD varies between 1 and N. The complexity of the GFD varies between those of the maximum-likelihood (ML) detector and the zero-forcing decision feedback detector (ZFDFD). Extensive computer simulation results are also provided
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