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fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Ong, Lay Teen
Languages: English
Types: Doctoral thesis
Subjects: QA

Classified by OpenAIRE into

arxiv: Computer Science::Information Theory
ACM Ref: Data_CODINGANDINFORMATIONTHEORY
Attaining the most spectrally efficient form of data transmission over a time- varying channel remains as fundamentally important target in wireless systems. Link adaptation (LA) is a promising approach to increase spectral efficiency. In general, the transmitter adjusts its parameter such as rate, power and coding in accordance with the channel state information (CSI) fed back from the receiver. Consequently, the accuracy of the CSI is prevalent in LA design. In this thesis, an investigation of the performance of a variable rate variable power (VRVP) multi-level quadrature amplitude modulation (MQAM) scheme is performed for a single antenna system. Then, a novel VRVP-MQAM system is proposed that employs a rate and power adaptation algorithm based on the statistical characterization of CSI imperfection. Instead of using the conventional signal-to-noise ratio (SNR) estimate as a CSI parameter, the proposed system is based on both an SNR estimate and a bit error rate (BER) estimate, as BER is a more direct representation for quality of service (QoS) of a communication system. The pro posed rate and power adaptation algorithm is then generalized to incorporate a pilot symbol assisted modulation (PSAM) based channel predictor. The BER and SNR estimates are then employed within a code division multiple access (CDMA) based rate and power adaptation system. Finally, the performances of the pro posed systems are shown to achieve higher spectral efficiency when compared to the alternative systems derived based on conventional approach. Another requirement in today's wireless digital communication systems is to provide services for integrated voice and data traffic. The QoS requirement for voice and data can be application specific. For example, real-time traffic is delay-constrained, whereas non-real time traffic has a relaxed requirement on delay but may be capacity-constrained. With this motivation, a rate and power adaptation technique is proposed for a multiple-input multiple-output (MIMO) based integrated voice and data service. On the basis of analytical and simulation results, the performance of the proposed scheme is assessed for a Rayleigh fading environment. Finally, the results demonstrated that the MIMO based system is suitable for integrate voice and data traffic with different requirements and specification.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • 2.1 F a d in g .........................................................................................................
    • 2.2 Small Scale Fading and M ultipath E f f e c t ..........................................
    • 2.3 M ultipath Time Delay Spread: Flat/Frequency Selective Fading . 2.3.1 F la t- F a d in g .................................................................................... 2.3.2 Frequency Selective F a d in g .........................................................
    • 2.4 Doppler Spread: Fast/Slow Fading ....................................................
    • 2.5 Summary ..................................................................................................
    • Link A d a p ta tio n T echniques under Perfect CSI K now led ge 16
    • 3.1 In tro d u c tio n ............................................................................................... 16
    • 3.2 Capacity of a Time-Varying C h a n n e l ................................................. 17 3.2.1 Optim al Rate and Power A d a p ta tio n ...................................... 17 3.2.2 Sub-Optimal Transm itter A d a p ta tio n s .................................. 19 3.2.3 Numerical Results ...................................................................... 21
    • 3.3 VRVP-MQAM S y s t e m ........................................................................... 24
    • 3.3.1 BER for M Q A M ..........................................................................
    • 3.3.2 Rate and Power A d a p ta tio n s......................................................
    • 3.3.3 Numerical Results .......................................................................
    • 3.4.1 Problem F o rm a tio n .......................................................................
    • 3.4.2 Numerical Results .......................................................................
    • 4 P ilo t S ym b ol A ssisted M o d u la tio n B a sed C h an n el P red ictor 4.1 In tro d u c tio n ............................................................................................... 4.2 P S A M ......................................................................................................... 4.3 PS AM-Based Channel Predictionfor an LA S y s te m ........................ 4.3.1 Optimal-M AP Channel P r e d i c t o r ............................................ 4.4 Statistical Properties of the Predicted and the True Fading Amplitude .......................................................................................................... 4.4.1 The Ratio r = Q / Q ....................................................................... 4.4.2 Correlation C o e ffic ie n t................................................................ 4.4.3 Relationship between r and p .................................................. 4.4.4 Selection of (L , K 0) and its impact on p .................................. 4.5 S u m m a r y ..................................................................................................
    • 5 V R V P -M Q A M S y stem u n d er Im perfect CSI K n ow led ge 5.1 In tro d u c tio n ............................................................................................... 5.2 System M o d e l............................................................................................ 5.3 BER E s tim a te ............................................................................................ 5.3.1 Derivations and Results ............................................................. 5.4 Optim al Rate and PowerA d a p ta tio n .................................................. 5.5 Results and D isc u ssio n ...........................................................................
    • 5.5.1 Instantaneous Rate and Power in the VRVP-MQAM-CSI S y ste m ............................................................................................. 62
    • 5.5.2 Instantaneous Rate and Power in the VRVP-MQAM System 64
    • 5.5.3 Instantaneous R ate and Power in the CRCP-MQAM System 6 6
    • 5.5.4 Spectral Efficiency and Average P o w e r ................................. 6 6
    • S u m m a r y .................................................................................................. 6 8
    • 6 V R V P -M Q A M S ystem w ith P S A M -B a se d C hannel P red iction 70 6.1 Performance of the VRVP-MQAM System with Channel Prediction 70 6.2 System M o d e l........................................................................................... 71 6.3 Adaptive Rate and PowerA lg o r ith m .................................................. 73 6.3.1 VRVP-CSI S c h e m e ...................................................................... 74 6.3.2 VRVP-IDEAL S c h e m e ............................................................... 76 6.3.3 Spectral Efficiency and Average B E R .................................... 77 6.4 Channel P r e d ic tio n ................................................................................. 78 6.5 Simulation R e s u l t s ................................................................................. 80 6 .6 Summary .................................................................................................. 83
    • 7 V R V P -M Q A M S ystem w ith A d a p tiv e S N R Target 7.1 In tro d u c tio n ............................................................................................... 7.2 System Model and A n a l y s is ................................................................ 7.2.1 BER E s tim a te ............................................................................... 7.2.2 Rate and SNR Target A d a p ta tio n ........................................... 7.3 Numerical R e su lts.................................................................................... 7.4 Summary ..................................................................................................
    • 8.1 In tro d u c tio n ..............................................................................................
    • 9 C on clusions and Future W ork 134 9.1 C o n c lu s io n s................................................................................................... 134 9.2 Future W o rk ................................................................................................... 137
    • A A p p en d ix: P roofs for th e D erivation s in C hapter 5 139 A .l Proof of / PB,7 (p b , 7 ) e x p r e s s io n .............................................................. 139 A.2 Proof of the iMAPeq expression..................................................................140 A.3 Proof of the p s e x p re s s io n ........................................................................ 141 A.4 Proof of the / 7)7 (7 , 7 ) e x p r e s s io n ........................................................... 159 A.5 Proof of the SNR cutoff threshold,i.e. 70 = jth + X ............................ 160
    • 6.1 Block diagram of the proposed variable rate variable power MQAM system ............................................................................................................
    • 6.2 Frame structure: 'P ' denotes pilot symbol and 'D ' denotes data symbols..........................................................................................................
    • 7.1 Block diagram of adaptive SNR target VRVP-MQAM system. . . 8 6
    • 7.2 PD F of BER estimate with BERT = 10~ 3 ........................................... 94
    • 7.3 PD F of BER estimate with BERT = 10~ 3 ........................................... 94
    • 7.4 Comparisons of average spectral e fficien cy ........................................ 95
    • 8.1 Parallel MIMO channel representation based on the SVD................... 101
    • 8 .2 Capacity for MIMO system (2 ,2 ),(4,4). Comparison between full CSI and partial CSI........................................................................................ 106
    • 8.3 MIMO based VRVP-MQAM system where M*(.) denotes MQAM constellation size adaptation and P*(.) denotes power level adaptatio n ..................................................................................................................107
    • 8.4 PD F of related eigenvalues for a (2,2) MIMO system ..............117
    • 8.5 PD F of related eigenvalues for a (4,4) MIMO system..............117
    • 8 .6 PD F of L -1 unordered eigenvalues for a (2 ,2 ) MIMOsystem.
    • 8.7 PD F of L -1 unordered eigenvalues for a (4,4) MIMOsystem.
    • 8 .8 Probability of voice outage for USVV, LSVV and SSVV schemes with antenna sets (2,2) and (4,4)................................................................124
    • 8.9 Average spectral efficiency for data transmissions with antenna sets (2 ,2 ) and (4,4), and comparisons are performed between USVV, LSVV and SSVV schemes............................................................................ 126
    • 8.10 Average spectral efficiency for data transmissions with antenna set (4,4), comparisons are made between LSVV and LSVVout schemes. 128
    • A .l F2 versus instantaneous SNR estim ate 7 ; for the VRVP-MQAMCSI system at T = f = 25 dB, BER ta rg e t^ 10~3, and p = 0.8,0.9, ~ 1 ................................................................................... 145
    • A.2 Plot of function (1 / F - B ) as a functon of 7 for F\ and F2 , at settings T = 25 dB, p = 0.9 and BERT = 0.001................. 149
    • A.3 Evaluation of MAP function at critical points (local maxima and minima), start and end points, with T = 25 dB, p = 0.9 and BERT = 0.001............................................................................. 150
    • A.4 Instantaneous BER estim ate psexact versus instantaneous SNR estim ate 7 for p = {0.8,0.9,1.0}................................................ 154
    • A.5 Comparisons of instantaneous BER estimate based on exact BER estim ate expression and approximate BER estim ate expression. . 154
    • A .6 BER error due to approxim ation........................................... 155
    • A. 7 Comparisons of functions iMAPeq - -A-o an<^ (^-o + Ai + A2). At BER targ et= 10- 3 and H = 2..................................................................... 158
    • A .8 Comparisons of functions IMAPeq = A0 and (A0 + Ai + A2), at BER targ e t= 10-3 , and H = 4...............................................................................158
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