Transmit power reduction through subcarrier selection for MCCDMAbased indoor optical wireless communications with IM/DD
 Muhammad Zubair Farooqui^{1}Email author and
 Poompat Saengudomlert^{1}
https://doi.org/10.1186/168714992013138
© Farooqui and Saengudomlert; licensee Springer. 2013
Received: 12 June 2012
Accepted: 13 May 2013
Published: 28 May 2013
Abstract
This research addresses the issue of average transmit optical power reduction in multicarrier code division multiple access (MCCDMA)based indoor optical wireless communications employing intensity modulation with direct detection. The problem is treated in a novel way by investigating pre and postequalizationbased subcarrier selection for transmit power reduction in downlink transmissions. Analytical expressions are derived for upper bounds of the required fixed DC bias for both cases. The fixed DC bias is used to reduce the system complexity on one hand and to devise optimal subcarrier selection criteria on the other. Simulation results based on the proposed subcarrier selection reveal significant power reduction subject to the 10 ^{−4} bit error rate (BER) requirement for 10Mbps 64subcarrier MCCDMAbased indoor optical wireless communication systems. In addition, the BER performance obtained from preequalization is shown to be no higher than that obtained from postequalization for the same transmit power.
Keywords
1 Introduction
Multicarrier and multiple access communication technologies like orthogonal frequency division multiple access (OFDMA) and multicarrier code division multiple access (MCCDMA) have captured different vistas of communications not only for simple text data but also for different types of multimedia requiring robust transmissions. For 4G wireless systems [1] and beyond, optical wireless communication is considered as a linchpin to serve as a complementary sibling of RF for system implementation in indoor environments. Although multicarrier models, especially OFDMbased, have been much investigated, relatively few work can be observed regarding the use of MCCDMA for indoor optical wireless communications.
Recently optical wireless systems are reported to be integrated with WiFi networks to provide ubiquitous coverage systems for indoor applications [2]. In these systems, the optical spectrum provides an encouraging potential as a complementary medium to the congested radio spectrum. For such applications, intensity modulation (IM) can be applied to either infrared or visible light. The key advantages of such optical wireless systems are usage of flexible unlicensed spectrum, high data rate support, energy efficiency, no electromagnetic interference, lowcost front ends, and inherent security. Major issues are eye and skin safety problems which can be dealt with by limiting the average transmit optical power.
 1.
Average transmit optical power reduction is accomplished by subcarrier selection for the first time in MCCDMAbased indoor optical wireless communication systems employing intensity modulation with direct detection (IM/DD).
 2.
Expressions for upper bounds of a fixed DC bias using pre and postequalizationbased subcarrier selection are analytically derived for MCCDMAbased IM/DD system.
 3.
Optimal subcarrier selection algorithms that minimizes the bit error rate (BER) for a fixed transmit optical power are proposed for both pre and postequalization.
This paper is organized as follows. In Section 2, relevant works are discussed. Section 3 presents the proposed system model. Results and discussions are given in Section 4. Finally, conclusions are given in Section 5.
2 Related works
2.1 Average transmit power issue in multicarrier optical wireless communications
One major difference between an optical IM/DD channel and a conventional radio/electrical channel is that the channel input and output are signal intensities. This property has two major consequences  the input to the optical channel must be nonnegative, while the average transmit optical power is proportional to the mean (first moment contrary to second moment for electrical domain) of the input to the channel [3]. The former requires that an optical signal be unipolar, leading to the addition of a DC bias to the transmit signal. Despite the fact that the addition of symbolbysymbol DC bias seems theoretically simple, it results in a significant increase in system implementation complexity. Hence, using a fixed DC bias is practically attractive. The use of a DC bias results in a high transmit power which may be hazardous for eye and skin safety [4, 5]. Moreover, this additional power does not increase the SNR at the receiver at all [6]. Therefore, some appropriate power reduction scheme is required so that the associated DC bias does not lead to excessive transmit optical power [7].
The Infrared Data Association (IrDA), ANSI, and IEC standards recommend to limit the transmit optical power for different applications to address eye and skin safety problems at length [8, 9]. Hence, being equivalent in connotation to the issue of peaktoaverage power (PAPR) reduction in radio transmissions, transmit power reduction is at the crux of researches in multicarrier optical wireless communications. While the issue has been investigated for OFDMbased optical wireless systems, to the best of the authors’ knowledge, any direction of reparation of this issue has not yet been reported for MCCDMAbased optical wireless systems with IM/DD.
For simple multicarrierbased and OFDMbased indoor optical wireless communications, the following prominent solutions were put forth to address the issue of average power reduction. Block coding was investigated in [3] using symbolbysymbol bias for power reduction. An approach based on optimized reserved subcarriers was investigated in [10] . Clipped OFDM was suggested in [7] instead of conventional DC bias for achieving power reduction. The technique is claimed to have better power efficiency when compared to the DC bias approach. According to [11], clipped OFDM attains some advantages over DCbiased OFDM but at the cost of sacrificing a reasonable chunk of the available signaling bandwidth. The authors of [12] addressed the same issue by employing inband coding to use with symbolbysymbol bias. A novel approach of using outofband subcarriers to reduce transmit power was proposed in [13]. The use of the selected mapping technique was investigated in [14] to achieve reduction in average transmit optical power. A simple power allocation approach was suggested in [15] to achieve power reduction for a specific BER requirement. In [16], sparsity together with uncertainty principle was used for average power reduction. The authors in [17] proposed the use of Hartley transform module instead of inverse fast Fourier transform (IFFT) module to assure real positive output, eliminating the need of adding DC bias and greatly enhancing the power efficiency in OFDMbased optical IM/DD systems. However, none of the works have been found reported for transmit power reduction in MCCDMA with IM/DD.
2.2 Optical wireless channel
The key distinction between a conventional electrical channel and an IM/DD optical channel is that data are transmitted through the optical channel in the form of signal intensity. Accordingly, an IM/DD optical wireless system imposes the constraint that the transmitted signal should be realvalued and nonnegative to appropriately drive the light source [18]. Moreover, there is no multipath fading due to a typically high ratio between a photodetector area and an optical wavelength [8].
Y(t) is the output photocurrent of the photodetector, R is the detector responsivity, and ⊗ is the convolution operation. The IM/DD optical channel impulse response h(t) is dependent on the channel DC gain H(0) and a factor a which further depends on the rms delay spread D such that $a=12\sqrt{\frac{11}{13}}D$.
The prominent cause of noise is visible background light (fluorescent light, incandescent light, and sunlight), which is independent of the nature of the signal and modeled as additive white Gaussian noise (AWGN) [19], denoted by N(t). Finally, u(t) is the unit step Heaviside function.
2.3 MCCDMA
Owing to its high spectral efficiency, flexibility, and endurance to frequencyselective fading, MCCDMA, an amalgam of OFDM and CDMA based on the principle of frequency domain spreading, has emerged as a strong candidate for future communication systems in recent years. In the last decade, MCCDMA has attracted lots of interests in the research community, especially for downlink applications, where frequency domain equalization techniques can be used to mitigate multiaccess interference (MAI) that arises due to multipath propagation. No significant linear distortion is confronted in MCCDMA because the symbol duration is much longer than the delay spread. MCCDMA also offers flexible system design since the length of orthogonal signatures distinguishing multiple users from one another need not be equal to the number of subcarriers [20].
The working of MCCDMA is such that an individual user’s complexvalued data symbol is spread over OFDM subcarriers in the frequency domain using a spreading code. These symbols from different users are summed in the frequency domain and then passed to the OFDM modulator to transform into the time domain. A cyclic prefix is appended to mitigate intersymbol interference with the result upconverted to the passband after serialtoparallel conversion. At the receiver side, cyclic prefix removal, FFT, and despreading are carried out respectively.
2.4 Equalization
Channel equalization is a crucial phase in wireless communication systems. Due to the frequencyselective nature of wireless communication channels, spread spectrum schemes suffer impairments in orthogonality, which can be restored using different equalization techniques. In essence, the exploitation of appropriate equalization helps to efficiently combine different subcarriers’ signals in order to optimize the system performance [21]. Equalization requires the availability of channel estimates at the receiver or at the transmitter or at both ends depending upon the case of post, pre or combined equalization, respectively. Preequalization focuses on precompensating the predictable channel distortions. Conventionally, MAI mitigation in MCCDMA systems is carried out by singleuser or multiuser detection schemes (SUD or MUD) at the receiver [22]. Equalization is preferred over SUD and MUD techniques in terms of system complexity [23–25].
Equalization may be linear or nonlinear [26]. Equal gain combining, maximal ratio combining, orthogonality restoring combining, and minimum mean square error techniques are some versions of linear equalization employed in MCCDMA, where appropriate coefficients are used as weighting factors for the signals from different subcarriers. Interference cancellation and maximum likelihood detection are examples of nonlinear equalization which provide performance improvement at a tradeoff with receiver complexity [27]. The authors in [28] demonstrated the significant dependence of PAPR on the equalization technique and exploited equalization coefficients for PAPR reduction in MCCMDA systems.
3 Proposed system
3.1 Methodology
In this research, we demonstrate how subcarrier selection can be exploited to achieve reduction in average transmit optical power in MCCDMAbased indoor optical wireless communications with IM/DD. We propose subcarrier selection based on linear equalization, which is considered to be the simplest and least expensive technique to be implemented [26] to mitigate various impairments in conventional MCCDMA systems. Along with taking advantage of these positive features of linear equalization, we derive upper bounds for obtaining fixed DC bias values for both and pre and postequalization in MCCDMAbased indoor optical wireless communications with IM/DD. Based on these upper bounds, we devise subcarrier selection criteria for both pre and postequalization implementation.The subcarrier selection algorithms obtained analytically are used in the simulation to observe the average transmit optical power reduction separately for both cases.
Optical wireless channels exhibit frequencyselective nature at high data rates for multicarrier signals. To use the transmission bandwidth efficiently, subcarriers with better channel gains are used through an equalizationbased criterion. For this, we investigate downlink optical wireless transmissions with the data rates of 10 Mbps, which is considered moderate for optical wirelessbased industrial applications [1, 2]. The mentioned data transmission rate is used, keeping in view the two important factors in considering IRbased indoor optical wireless systems with diffused configuration. Firstly, the standards framed by IrDA and IEEE for typical room sizes in indoor optical wireless systems are of the order of this range [9, 29]. Secondly, the operating speed of currently available commercial devices in the market is typically in the same order as for our system. According to [30], there are theoretical limits and practical constraints like suitable optical sources and drive electronics in achieving high data rates for such systems. Data transmissions are simulated separately using MATLAB (MathWorks Inc., Natick, MA, USA), for pre and postequalization cases. The key parameters used for the selection of subcarriers are the channel gains of individual subcarriers. Since channel variations are slow in indoor environments, the channel state information (CSI) derived at a particular instant can be used for some subsequent time duration in indoor optical wireless systems. Subcarrier selection for MCCDMA can be further advocated by the fact that different subcarriers contain information on the same data symbol; therefore, noisedominated subcarriers can be discarded and signal energy can be reallocated to better subcarriers.
3.2 System model

L, number of active users

N, number of subcarriers

N_{cp}=γ N, length of cyclic prefix where 0 ≤ γ ≤ 1

${\mathcal{N}}_{\mathrm{a}}$, set of active (selected) subcarrier indices

N_{a}, number of active subcarriers indices, i.e.,${N}_{\mathrm{a}}=\left{\mathcal{N}}_{\mathrm{a}}\right$

d_{ l }, data symbol from user l

c_{l,n}, CDMA codeword component for user l on subcarrier$n\in {\mathcal{N}}_{\mathrm{a}}$

T, MCCDMA symbol period

f_{c}, electronic carrier (passband) frequency

p(t), transmit pulse shape

B, fixed bias of nonnegative passband signal for IM

A_{max}, maximum amplitude of QPSK symbol

s_{b}(t), baseband MCCDMA signal

s_{p}(t), passband MCCDMA signal

s_{opt}(t), transmit optical signal

E_{s}, QPSK symbol energy

H_{ n }, FFT of the discretetime channel impulse response with length N symbol periods ( n∈{0,…,N−1})

W_{ n }, complex AWGN values, which are iid circularly symmetric complex Gaussian rv with variance σ^{2} (the variance of a complex random variable is the sum of the variance of the real part and that of the imaginary part).
Hence, users are distinguished by their respective code sequences. Every chip of the spreading code representing a fraction of the information symbol is transmitted through an active subcarrier. As described in Section 3.1, these active subcarriers are selected based on the CSI.
The above model is used to derive upper bounds for a fixed DC bias by employing preequalization and postequalization schemes. For each case under investigation, CSI is assumed to be available at the transmitter or at the receiver as per post or preequalization requirements, respectively. Then these fixed biases, denoted by B_{post} and B_{pre}, are employed in finding the optimal criteria for subcarrier selection in both cases. The following two subsections show the analytical models for both cases along with the derivation of conservative bounds for fixed DC biases. In both cases, subcarrier selection is based on maximizing the argument of the Q function in the BER expression, where the Q function is the complementary cumulative distribution function of zeromean unitvariance Gaussian random variable.
3.2.1 Postequalization case
Subcarrier selection: postequalization case. The BER expression in (18) yields the following theorem that provides a method to select active subcarriers. Let N_{c}(L) denote the length of CDMA codewords required to accommodate L users. Note that the value N_{c}(L) depends on the type of codewords used.
Theorem 1
 1.
The number of active subcarriers is N _{c}(L).
 2.
The selected active subcarriers are the N _{c}(L) subcarriers with the highest gain magnitudes, i.e., highest H _{ n }s.
Proof
The value of ξ is decreasing with N_{a} since H_{ n }’s are always positive. Consequently, the smallest possible value of N_{a} is optimal. Since we need to use at least N_{c}(L) subcarriers, it follows that N_{a}=N_{c}(L). This proves part 1.
Now, given that we must use N_{c}(L) subcarriers, the best choice is to select the subcarriers with the highest magnitude gains to maximize ξ. This proves part 2. □
3.2.2 Preequalization case
Subcarrier selection: preequalization case. The BER expression in (27) yields the following theorem that provides a method to select active subcarriers.
Theorem 2
 1.
The number of active subcarriers is N _{c}(L).
 2.
The selected active subcarriers are the N _{c}(L) subcarriers with the highest gain magnitudes i.e., highest H _{ n }s.
Proof
Since H_{ n }s are smaller than 1 (i.e., signal attenuation typically in the order of 10 ^{−7}), κ decreases with N_{a}. Consequently, the smallest possible value of N_{a} is optimal. Since we need to use at least N_{c}(L) subcarriers, it follows that N_{a}=N_{c}(L). This proves part 1.
Now, given that we must use N_{c}(L) subcarriers, the best choice is to select the subcarriers with the highest magnitude gains to maximize κ. This proves part 2. □
3.3 Comparison between BER_{ posteq }and BER_{ preeq }
From the previous discussions, we conclude that for both postequalization and preequalization it is optimal to select N_{c}(L) subcarriers with the highest H_{ n }s. The next question is whether postequalization or preequalization performs better in terms of the BER for a given DC bias B_{post}=B_{pre}=B.
The next theorem shows that preequalization always performs no worse than postequalization.
Theorem 3
Given that the DC biases in (12) and (25) are used for postequalization and preequalization respectively, the corresponding BER for preequalization is no more than the BER for postequalization.
Proof
From the direct consequence of the CauchySchwarz inequality $\frac{\sum _{i=0}^{n}{x}_{i}}{n}\le \sqrt{\frac{\sum _{i=0}^{n}{x}_{i}^{2}}{n}}$, the inequality $\frac{{N}_{\mathrm{a}}}{\sum _{n\in {\mathcal{N}}_{\mathrm{a}}}1/\left{H}_{n}\right}\ge \sqrt{\frac{{N}_{\mathrm{a}}}{\sum _{n\in {\mathcal{N}}_{\mathrm{a}}}1/{H}_{n}{}^{2}}}$ holds. It follows that BER_{preeq} ≤ BER_{posteq}. □
4 Analytical and simulation results with discussions
Simulation parameters
Parameter  Specification 

Transmission bit rate  10 Mbps 
Modulation  QPSK 
Number of subcarriers  64 
Spreading sequences  WalshHadamard 
Channel model  As in (2) [8] 
Equalization  Singletap frequency domain 
pre and postequalization  
Digitaltoanalog converter (DAC)  Rectangular pulse 
H(0) (DC channel gain)  −60 dB [8] 
N_{0} (noise variance)  10 ^{−23} A^{2}/Hz [8] 
D (rms delay spread)  10 ns [8] 
R (photodetector responsivity)  1 A/W [8] 
Transmit power calculation  As per multicarrier optical 
wireless communications 
4.1 Postequalizationbased subcarrier selection
Q function arguments for both domains employing postequalizationbased subcarrier selection
Radio domain  Optical wireless domain 

$\frac{{N}_{\mathrm{a}}}{\sigma}\sqrt{\frac{{E}_{\mathrm{s}}}{\left(\sum _{n\in {\mathcal{N}}_{\mathrm{a}}}1/{\left{H}_{n}\right}^{2}\right)}}$  $\frac{{B}_{\text{post}}}{\mathrm{L\sigma}}\sqrt{\frac{T}{1+\gamma}}\sqrt{\frac{1}{\left(\sum _{n\in {\mathcal{N}}_{\mathrm{a}}}1/{\left{H}_{n}\right}^{2}\right)}}$ 
It can be observed in Figure 3 that an optimal number of active subcarriers exists in the range 1<N_{a}<N for the radio domain. The behavior is different for the optical wireless domain where it is always better to have fewer active subcarriers, as can be observed in Figure 4. This reveals the fact that there is a fundamental difference in subcarrier selection between radio communications and optical wireless communications employing postequalization. The optimal number of subcarriers to be employed is consistent with Theorem 1 of Section 3.2.1.
4.2 Preequalizationbased subcarrier selection
Q function arguments for both domains employing preequalizationbased subcarrier selection
Radio domain  Optical wireless domain 

$\frac{1}{\sigma}\sqrt{{E}_{\mathrm{s}}{N}_{\mathrm{a}}}$  $\sqrt{\frac{T{N}_{\mathrm{a}}}{1+\gamma}}\frac{{B}_{\text{pre}}}{\mathrm{L\sigma}\sum _{n\in {\mathcal{N}}_{\mathrm{a}}}1/\left{H}_{n}\right}$ 
Based on Figure 8, in radio communications employing subcarrier selection based on preequalization, a lower BER is obtained by employing more subcarriers for data transmission. The case is exactly opposite for optical wireless communications, as can be observed in Figure 9, where a lower BER results from using fewer active subcarriers. This reveals the fact that there is a fundamental difference in subcarrier selection between radio communications and optical wireless communications employing preequalization. The optimal number of subcarriers to be employed is consistent with Theorem 2 of Section 3.2.2.
5 Conclusions
We proposed and investigated pre and postequalizationbased subcarrier selection approaches as efficient modes of average transmit optical power reduction in an MCCDMAbased indoor optical wireless communication system with IM/DD. Based on these approaches, conservative expressions for fixed DC biases to be employed in the system are derived. We then used the established DC bias expressions to construct optimal methods for choosing the number of active subcarriers for both pre and postequalization.
The simulation results validate the correctness of analytically found optimal criteria of subcarrier selection. For up to a moderate number of users, as is the case in indoor optical wireless communication systems, the amount of transmit power reduction can be significant. A typical data transmission rate of 10 Mbps with 64 subcarriers and QPSK modulation is used as an example case. For postequalizationbased subcarrier selection, reductions ranging from 10 to 24 dB are observed while 8 to 18 dB are observed for preequalizationbased subcarrier selection with the BER requirement of 10^{−4}. Finally, analytical comparison of both cases reveals that preequalization always performs no worse than postequalization in terms of the BER for the same optical transmit power.
Declarations
Acknowledgments
The authors would like to pay gratitude to the Higher Education Commission (HEC), Pakistan, for supporting this research work and for the continuous encouragement in higher education.
Authors’ Affiliations
References
 Paraskevopoulos A, Vucic J, Voss SH, Swoboda R, Langer KD: Optical wireless communication systems in the Mb/s to Gb/s range, suitable for industrial applications. IEEE/ASME Trans. Mechatronics 2010, 15: 541547.View ArticleGoogle Scholar
 Wang K, Nirmalathas A, Lim C, Skafidas E: Highspeed optical wireless communication system for indoor applications. IEEE Photonics Tech. Lett 2011, 23: 519521.View ArticleGoogle Scholar
 You R, Kahn JM: Average power reduction techniques for multiplesubcarrier intensitymodulated optical signals. IEEE Trans. Commun 2001, 49: 21642171. 10.1109/26.974263View ArticleGoogle Scholar
 Joshi H, Green RJ, Leeson MS: Multiple subcarrier optical wireless systems. 10th Anniversary Proceedings of the IEEE International Conference on Transparent Optical Networks Athens, 22–26 June 2008Google Scholar
 Hranilovic S: Wireless Optical Communication Systems. Boston: Springer; 2005.Google Scholar
 Chen L, Krongold B, Evans J: Performance evaluation of optical OFDM systems with nonlinear clipping distortions. IEEE International Conference on Communications ICC Dresden, 14–18 June 2009Google Scholar
 Armstrong J, Lawery AJ: Power efficient optical OFDM. IEEE Electron. Lett 2006, 42: 370372. 10.1049/el:20063636View ArticleGoogle Scholar
 Kahn JM, Barry JR: Wireless infrared communications. Proc. IEEE 1997, 85: 265298. 10.1109/5.554222View ArticleGoogle Scholar
 Carruthers JB: Wireless infrared communications. In Wiley Encyclopedia of Telecommunications. Edited by: Proakis JG. New York: Wiley; 2003:5376.Google Scholar
 Sharif M, Hassibi B: On the achievable average power reduction of MSM optical signals. IEEE Commun. Lett 2004, 8: 8486. 10.1109/LCOMM.2004.823418View ArticleGoogle Scholar
 Mesleh R, Elgala H, Haas H: An overview of indoor OFDM/DMT optical wireless communication systems. Proceedings of the 7th International Symposium on Communication Systems Network and Digital Signal Processing  CSNDSP’10 Newcastle, 21–23 July 2010Google Scholar
 Kang W, Hranilovic S: Inband coding for power reduction in multiplesubcarrier modulated wireless optical systems. Proceedings of the 23rd Biennial Symposium on Communications Kingston, 29 May–1 June 2006, pp. 96–99Google Scholar
 Kang W, Hranilovic S: Power reduction techniques for multiplesubcarrier modulated diffuse wireless optical channels. IEEE Trans. Commun 2008, 56: 279288.View ArticleGoogle Scholar
 Farooqui MZ, Saengudomlert P, Kaiser S: Average transmit power reduction in OFDMbased indoor wireless optical communications using SLM. Proceedings of the International Conference on Electrical and Computer Engineering, ICECE’10 Dhaka, 18–20 December 2010Google Scholar
 Farooqui MZ, Saengudomlert P: Average transmit power reduction through power allocation for OFDMbased indoor wireless optical communications. Proceedings of the 8th Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology Association of Thailand Conference, ECTICON’11 Khon Kaen, 17–19 May 2011Google Scholar
 Ilic J, Strohmer T: Average power reduction for MSM optical signals via sparsity and uncertainty principle. IEEE Trans. Commun 2010, 58: 15051513.View ArticleGoogle Scholar
 Moreolo MS, Munoz R, Junyent G: Novel power efficient optical OFDM based on Hartley transform for intensitymodulated directdetection systems. J. Lightwave Tech 2010, 28: 798805.View ArticleGoogle Scholar
 Grubor J, Langer KD: Efficient signal processing in OFDMbased indoor optical wireless links. J. Netw 2010, 5: 197211.Google Scholar
 You R, Kahn JM: Upperbounding the capacity of optical IM/DD channels with multiplesubcarrier modulation and fixed bias using trigonometric moment space method. IEEE Trans. Inf. Theory 2002, 48: 514523. 10.1109/18.979327MathSciNetView ArticleGoogle Scholar
 Fazel K, Kaiser S: MultiCarrier and Spread Spectrum Systems. West Sussex: Wiley; 2003.View ArticleGoogle Scholar
 Masini BM, Zabini F: On the effect of combined equalization for MCCDMA systems in correlated fading channels. Proceedings of the IEEE Wireless Communications and Networking Conference, WCNC Budapest, 5–8 April 2009Google Scholar
 Sanguinetti L, Cosovic I, Morelli M: Channel estimation for MCCDMA uplink transmissions with combined equalization. IEEE J. Selected Areas Commun 2006, 24: 11671178.View ArticleGoogle Scholar
 Mottier D, Castelain D: SINRbased channel preequalization for uplink multicarrier CDMA systems. Proceedings of the Personal, Indoor, Mobile Radio Communications Lisboa, 15–18 September 2002Google Scholar
 Nobilet S, Herald JF: A preequalization technique for uplink MCCDMA systems using TDD and FDD modes,Vancouver, BC, Canada. In Proceedings of the IEEE 56th Vehicular Technology Conference. IEEE: Picataway; 2002:346350.View ArticleGoogle Scholar
 Benvenuto N, Bisaglia P, Tosato F: Preequalization with subband channel loading: a technique to maximize throughput in uplink OFDMCDMA systems. IEEE Trans. Commun 2005, 53: 564568. 10.1109/TCOMM.2005.844933View ArticleGoogle Scholar
 Masini B, Zabini F, Conti A: MCCDMA systems: a general framework for performance evaluation with linear equalization. In Communications and Networking. Edited by: Peng J. Sciyo: Rijeka, Croatia; 2010:127148.Google Scholar
 Hanzo L, Yang LL, Kuan EL, Yen K: Single and MultiCarrier DSCDMA: MultiUser Detection, SpaceTime Spreading, Synchronisation, Networking and Standards. West Sussex: WileyIEEE; 2003.View ArticleGoogle Scholar
 Cosovic I, Sanguinetti L: On the peaktoaverage power ratio of preequalized multicarrier codedivision multipleaccess transmissions. IEEE 61st Vehicular Technology Conference Stockholm, 30 May–1 June 2005Google Scholar
 Borah DK, Boucouvalas AC, Davis CC, Hranilovic S, Yiannopoulos K: A review of communicationoriented optical wireless systems. EURASIP J. Wireless Commun. Netw 2012, 91: 128.Google Scholar
 O’Brien D, Minh HL, Faulkner G, Wolf M, Grobe L, Li J, Bouchet O: High datarate infrared optical wireless communications: implementation challenges. IEEE Globecom Workshop on Optical Wireless Communications Miami,6–10 December 2010Google Scholar
 Ntogari G, Kamalakis T, Sphicopoulos T: Performance analysis of space time block coding techniques for indoor optical wireless systems. IEEE. J. Selected Areas Commun 2009, 27(9):15451552.View ArticleGoogle Scholar
 Li J, Uysal M: Optical wireless communications: system model, capacity and coding. In 58th IEEE Vehicular Technology Conference. Piscataway: IEEE; 2003.Google Scholar
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