Orthogonal Frequency Division Multiplexing with Diversity for Future Wireless Systems

This chapter studies the influence of spatial diversity on the synchronization of MIMO-OFDM systems. Upon revising the main features of OFDM and diversity techniques, this chapter focuses on the following topics. First, the sensitivity of the MIMO-OFDM receivers to the residual synchronization errors is examined. Then the effects of spatial diversity on symbol timing and carrier frequency synchronization are investigated. Computer simulation results show that by exploiting the spatial diversity in MIMO-OFDM systems, the synchronization performance can be significantly improved.

Cyclic prefix or guard interval is usually used in OFDM to mitigate interblock interference (IBI). It must be longer than the delay span of wireless channels to completely cancel IBI. In some environments, the delay span of wireless channels is very large; therefore, the efficiency of OFDM is significantly reduced if it is still designed with long enough cyclic prefix. An alternative way is to use certain cyclic prefix to deal with those channels with reasonable length of delay span and to apply signal processing techniques at the receiver to deal with IBI caused by the channels with extremely long delay spans. In this chapter, we first analyze IBI and inter-carrier interference (ICI) for OFDM systems with insufficient cyclic prefix or zero-padding guard interval and propose a dynamic and static timing approach to mitigate ICI and IBI. We then develop iterative signal detection approaches for OFDM systems with insufficient cyclic prefix and zero-padding guard interval, respectively.

This chapter considers pilot symbol assisted linear mean square error channel estimation in the joint space-time-frequency (STF) domains, for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. Through the use of properly designed and placed pilot sequences, and three dimensional processing, the proposed STF channel estimator exploits the correlation that may exist in the three domains, yielding performance gains. Computer simulation results for a coded MIMO-OFDM system illustrate the performance advantages of our approach. As a specific example we show that in a MIMO-OFDM system employing a space-frequency orthogonal block code, such an STF channel estimation technique limits the bit error probability (BEP) degradation with respect to perfect channel knowledge to 2 dB at a BEP of 10-5 over the 3GPP fast-fading suburban macro environment with high transmit space correlation. Furthermore, we show that STF channel estimation reduces variability in BEP performance when the mobile speed varies.

An efficient way to reduce the peak-to-average power ratio (PAPR) in OFDM systems is clipping. After the clipping in an MIMO-OFDM system, the additive noise may not be white. In this chapter, we develop fast (single-symbol) maximum likelihood (ML) decoding algorithms for orthogonal space-time block codes (OSTBC) and (linearly transformed) quasi orthogonal space-time block codes (QOSTBC) in clipped MIMO-OFDM systems by using a clipping noise model with Gaussian approximation. By using the statistics of the clipping distortions, our newly developed fast ML decoding algorithms improve the performance for clipped MIMO-OFDM systems with OSTBC and QOSTBC while the decoding complexities are not increased. Simulation results are presented to illustrate the improvement.

In this chapter, we study transmit diversity scheme employed in multipleinput,
multiple-output (MIMO) systems and analyze its performance theoretically in
random fading channels under different conditions, e.g. with and without spatial correlations,
with and without transmit antenna selection. The transmit diversity scheme
in its original form does not take the frequency selectivity of the channel into account,
therefore it has to be modified in order to be applicable for real life applications. To
this end, we introduce two solutions to combat the intersymbol interference caused by
frequency selective channels and in the meantime, exploit the spatial and multi-path diversities
with simple linear processing at the receiver. We aim at providing readers with
a comprehensive view on different aspects of MIMO transmit diversity and a practical
guideline on how to design a wireless communication system with transmit diversity.

The multiple antenna techniques can be used to increase transmission data rates through multiplexing or to improve the transmission quality through diversity. When multiple antennas are utilized in OFDM systems, models such as SISO-OFDM, SIMO-OFDM, MISOOFDM, and MIMO-OFDM are formed and their performances are strictly related to linear diversity. For the transmit linear diversity, schemes such as Delay Diversity (DD), Cyclic Delay Diversity (CDD), Alamouti and phase based precoding are analyzed for MISO-OFDM systems in this chapter. While in the single-stream and multi-stream MIMO-OFDM systems, linear receive diversity techniques such as maximal ratio combing (MRC), minimum mean square error (MMSE) and MMSE-SIC (successive interference cancellation) are introduced and discussed. Simulation results show that the OFDM system configuring with the linear diversity scheme achieves a great improvement.

Orthogonal frequency division multiple access (OFDMA) becomes a popular framework of future cellular systems such as 3GPP LTE and IEEE 802.16e WiMAX. Spatial diversity and multiuser diversity are expected to play a key role in future OFDMA based cellular systems. Considering that cellular systems will operate in an interferencelimited environment, it is required to understand the effect of co-channel interference on spatial and multiuser diversity. This chapter highlights the effects of co-channel interference on spatial and multiuser diversity and provides insights into the interactions between multiuser diversity and spatial diversity in the presence of co-channel interference.

Dynamic resource allocation and throughput behaviour of multiuser OFDM will be considered with three limited CSI feedback schemes, namely sub-channelized OFDM, 1-bit/sub-carrier and selective feedback. It should be noted, however, that our aim is not to compare them in strict sense, i.e. comparison of throughput for a fixed amount of feedback. In fact, these limited feedback schemes are not technically conflicting, but can be used simultaneously for further reduction in feedback overhead, and our objective is to provide insight into the system behaviour under the limited feedback schemes by exploring the relationship between the throughput and the respective design parameters.

To achieve higher spectral efficiency and more efficient usage of channel resources, adaptive modulation can be used jointly with diversity combining, or with power-loading, or with both selection diversity and power loading. We derive closed-form expressions of the performance of multi-channel systems with the conventional adaptive modulation and hybrid schemes, in terms of the spectral efficiency, the average bit error rate and the outage probability. Numerical results show that average modulation with selection-combining and power-loading (AMSP) offers higher spectral efficiency and lower outage probability than other schemes, and is more reliable in low signal to noise ratio (SNR) regions.

Inter-carrier interference power PICI of Gaussian and hyperbolic scattering channels in a mobile orthogonal frequency division multiplexing (OFDM) system using their angle-of-arrival (AoA) probability density functions (pdf) is estimated. The PICI difference of the two channels is estimated and plotted as functions of ( , ζ), ( ,) and ( , fdTs). Experimental PICI difference for = 0, ζ = 0 and fdTs = 0.05 is obtained and plotted with the simulated results for comparison purposes. The ICI power is also plotted against (fdTs,), (fdTs,ζ), and (ζ,) for specific values of . Closed-form bit error rate (BER) expressions of OFDM communication systems in an added white Gaussian noise (AWGN) and Rayleigh fading environments using bipolar phase shift keying (BPSK), OFDM-BPSK, are derived.

This chapter investigates performance of OFDMA based mobile WiMAX downlink Multiple Input Multiple Output (MIMO) beamforming algorithms and analyzes Signal to Interference plus Noise Ratio (SINR) distribution for the OFDMA based WiMAX uplink multi-user MIMO systems. MIMO techniques are supported in IEEE 802.16 standard to achieve array gain, diversity gain and multiplexing gain. Beamforming and beamforming plus MIMO increase transmission ranges and improve SINR for MIMO systems by reducing co-channel interferences. The beamforming-only scheme aims at interference cancelation to improve link SINR. The beamforming Plus MIMO scheme can not only exploit the array gain by using beamforming but can also achieve transmit or receive diversity gain and spatial multiplexing gain. Our simulation results show that beamforming plus MIMO significantly improves the performance by combining diversity gain and beamforming gain and alleviating the effect of antenna correlation. Therefore, the beamforming plus MIMO is a promising technique for the mobile WiMAX applications. For WiMAX uplink MIMO systems, a mathematical expression of the received SINR is derived, which provides an analysis tool for the studied WiMAX systems.

OFDM/OFDMA Cellular Networks

Actual systems for broadband wireless access adopt multi-carrier signals based on OFDM and OFDMA formats. These systems are practically deployed as traditional cellular networks, i.e. their planning is based on classical single carrier based strategies. However, these methodologies do not account for the features of a multicarrier systems in which coded bits in a block are transmitted over M spared sub-carriers undergoing (possibly) uncorrelated fading and interference effects. In this case the decoder in the receiver can be able to mitigate the detrimental channel effects even when some sub-carriers are received with individual SINR below the specified target quality level. In order to account for this aspect, network planning based on single SINR needs to be extended to multi-carrier. As shown in this work, this extension can be achieved by reformulating the planning procedure in terms of the effective SINR which, in general, is a combination of the SINRs received on the M sub-carriers.