How to Broadcast Multimedia Contents? IV Hierarchical Modulation
[How to Broadcast Multimedia Contents? I Introduction]
[How to Broadcast Multimedia Contents? II Lessons from The Channel]
[How to Broadcast Multimedia Contents? V Overloaded Tx and IC]
[How to Broadcast Multimedia Contents? VI Open-Loop MIMO for BCMCS]
[How to Broadcast Multimedia Contents? VII Network Layer or Steam Layer Design]
[Contribution to 3GPP2 Next Generation Technologies Ad Hoc Group (NTAH) 2007]
[On Enhancing Hierarchical Modulations, 2008 IEEE Int. Sym. on BMSB ]
[How to Broadcast Multimedia Contents? II Lessons from The Channel]
[How to Broadcast Multimedia Contents? V Overloaded Tx and IC]
[How to Broadcast Multimedia Contents? VI Open-Loop MIMO for BCMCS]
[How to Broadcast Multimedia Contents? VII Network Layer or Steam Layer Design]
[Contribution to 3GPP2 Next Generation Technologies Ad Hoc Group (NTAH) 2007]
[On Enhancing Hierarchical Modulations, 2008 IEEE Int. Sym. on BMSB ]
As shown in Figure 1, hierarchical modulation, also called layered modulation, is one of the techniques for multiplexing and modulating multiple data streams into one single symbol stream, where the base-layer symbols and enhancement-layer symbols are synchronously overlapped together before being transmitted. When hierarchical modulation is employed, users with good reception and advanced receiver can demodulate more than one layer of data streams. For a user with conventional receiver or poor reception, it may be able to demodulate the data streams embedded in low layer(s), e.g, the base layer only. From an information-theoretical perspective, hierarchical modulation is taken as one of the practical implementations of superposition precoding, which can help achieve the maximum sum rate of Gaussian broadcast channel with employing interference cancellation by receivers. From a network operation perspective, a network operator can seamlessly target users with different services or QoS’s with this technique. However, traditional hierarchical modulation suffers from inter-layer interference (ILI) so that the achievable rates by low-layer data streams, e.g. the base-layer data stream, can be dented by the interference from high-layer signal(s). For example, for the hierarchically modulated two-layer symbols with a 16QAM base layer and a QPSK enhancement layer, the base layer throughput loss can be up to about 1.5bits/symbol with the total receive signal-to-noise ratio (SNR) of about 23 dB. This means, due to ILI, there is about 1.5/4 = 37.5% loss of the base-layer achievable throughput with 23dB SNR. And the demodulation error rate of either the base-layer and enhancement-layer symbols increases too. From a practical implementation point-view, it is also known that the severe amplitude and phase fluctuations of wireless channels can significantly degrade the receiver demodulation performance since the demodulator must scale the received signal so that the result signals is within the dynamic range of the followed analog-to-digital convertor (ADC) or, more generally, the receiver processing region, mostly with automatic gain control (AGC). Even though pilots may be available for assisting the receiver channel estimation and equalization, there are channel estimation errors, especially when the channel coherent time is short. If the channel is estimated in errors, it can lead to improperly compensated signals and incorrect demodulation even in the absence of noise. On the other hand, multicarrier transmission, e.g. orthogonal frequency-division multiplexing (OFDM), is widely used for broadcast multicast services (BCMCS) as well as next generation wireless systems, due to its high diversity gain and high spectral efficiency with simple receiver design. However, the advantages of OFDM, specially when it is modulated by high-order signal constellations, are counter-balanced by the high peak-to-average-power ratio (PAPR) issue. High PAPR of modulated signals can significantly reduce the average output power of the high-power amplifier (HPA) at the transmitter due to more back-offs. It also increases the receiver demodulation and decoding errors and therefore limits the throughput of whole transceiver chain. Therefore it is important to understand and optimize regular hierarchical modulations for the best achievable performance.
Figure 1. Enhanced hierarchical modulation example: QPSK/QPSK |
In this contribution, the regular hierarchical modulation is firstly extended by allowing additional rotation on the enhancement layer signal constellation. The generalized hierarchical modulations are then studied and analyzed from four different perspectives, such as achievable capacity [Figure 2], modulation efficiency [Figure 4], demodulation robustness and peak-to-average-power ration (PAPR) when it is combined with the popular OFDM. At first, the achievable capacities of hierarchical modulations over Gaussian broadcast channel are studied from an information-theoretical perspective. As an example, the capacity of a regular 16QAM is tore down into the equivalent capacities of a base layer and enhancement layer. It is shown that there is a capacity loss on the base layer due to the inter-layer interference (ILI) from the enhancement layer [Figure 2]. And this capacity loss can be mitigated by properly rotating the enhancement signal constellation. From a signal-processing perspective, it is known that the capacity loss is also related to the Euclidean distance profile of the hierarchical modulation signal constellation. For example, in high signal-to-noise ration (SNR) region, the symbol error rate usually is dominated by the minimum Euclidean distance. Obviously, with properly rotating the enhancement layer signal constellation and maximizing the minimum Euclidean distance, the resulted symbol error rate will decrease. Additionally, for tracking Euclidean distance profile changes, several parameters like effective signal power, effective SNR and modulation efficiency are discussed too. After this, hierarchical modulations are analyzed from an implementation perspective with considering channel estimation errors, which includes both channel amplitude estimation errors and channel phase estimation errors. It is shown that the demodulation robustness of hierarchical modulations can also be controlled by changing the Euclidean distance profile. Finally hierarchical modulations are discussed from a transmit power efficiency perspective when it is combined with multicarrier transmission. With avoiding high back-offs and maximizing average output power, it shows that high RF transmitter power efficiency is achievable by properly rotating the enhancement layer signals. With the analyses from different aspects of hierarchical modulation, a in-depth understanding of it can be achieved.
Figure 2. Capacity tear-down of 16QAM, a hierarchical modulation perspective |
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