1 Introduction
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The LPP we put forward exhibits an accurate performance prediction combined with a closed-form solution which makes it eligible for practical implementation of LA algorithms. Indeed, at the generic protocol round (PR) ℓ of a given packet, the αESM is obtained recursively, by combining the aggregated effective SNR (ESNR), that stores the performance up to the previous retransmission (step ℓ−1), with the actual ESNR at PR ℓ, which depends on the current CSI and choice of the MCS.
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The αESM is shown to overcome the limitations exhibited by [20, 21], where the MCS used in the subsequent retransmission is identical with that originally chosen, in that the LPP works with CC only. Conversely, since the proposed method has the inherent possibility of choosing the MCS optimizing the GP metric within the retransmissions of the same packet, as a result, it enables a much more flexible LA strategy.
2 System model
2.1 HARQ retransmission protocol
2.2 MIMO BIC-OFDM system
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we assume the CSI \(\mathbf {H}^{(\ell)}_{n}\), \(\forall n \in {\mathcal {N}}\), to be known at the transmitter side.
3 Link performance prediction for HARQ-based MIMO BIC-OFDM systems
3.1 Rationale of the adaptive HARQ strategy
3.2 Background on the κESM LPP model
3.3 The αESM model
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The input to the ith BIOS channel, 1≤i≤B(ℓ), is the bit \(b_{\Pi ^{(\ell)}(i)}^{(\ell)}\), which is mapped in the jth position of the label of the QAM symbol \(x^{(\ell)}_{n,\nu }\) sent on subchannel (n,ν), being Φ(ℓ)(j,n,ν)=k.×
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The output is the bit log-likelihood metric \(\Lambda _{k}^{(\ell)}\), also named bit score, evaluated as in (5).
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The decoder metric for the reference codeword b(ℓ) is the BICM maximum a posteriori metric results as [28]$$ \lambda ({{b}^{(\ell)}},{{z}^{(\ell)}}) = \prod\limits_{(n,\nu) \in {\mathcal{C}}} {\prod\limits_{j = 1}^{m_{n,\nu}^{(\ell)}} {\lambda_j \left({b^{(\ell)}_{\Phi^{(\ell)}(j,n,\nu)}},{z}^{(\ell)}_{n,\nu}\right)} }, $$(11)
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the pattern \(\mathbf {q}^{(\ell)}_{k}\) can be modeled as a sequence of ℓ independent and identically distributed (i.i.d.) binary RVs taking values 0 or 1, independently of the bit index k.
4 Link adaptation for EGP optimization
4.1 Expected goodput formulation
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at PR ℓ, each packet experiences the current channel condition Υ(ℓ)) over its possible future retransmissions, then φ(ℓ+j)=φ(ℓ), j∈[0,L−ℓ].
4.2 Goodput-oriented-AMC (GO-AMC) OP
5 Simulation results
Parameter/feature | Symbol | Value/description |
---|---|---|
RLC-PDU | ||
RLC-PDU length | Np+NCRC | 1056 bits |
OFDM | ||
No. of active subcarriers |
N
| 1320 |
FFT size |
N
FFT
| 2048 |
CP length |
N
CP
| 160 samples |
Modulation and coding | ||
Bits per subcarrier |
\({\mathcal {D}}_{m}\)
| {2,4,6} |
Code type | PCCC turbo-code | |
Mother code rate | 1/3 | |
Punctured code rates |
\(\mathcal {D}_{r}\)
| {78,120,193,308,449,602,378, |
490,616,466,567,666,772,873, | ||
948}/1024 | ||
Transmitted power |
P
| 40 dBm |
Bandwidth |
W
| 20 MHz |
Multi-antenna configuration | N
R
×N
T
| |
4x4 (MIMO) in Fig. 6 | ||
8x8 (MIMO) in Fig. 7 | ||
ARQ | ||
ARQ scheme | Multiple-channel Stop & Wait | |
No. of PRs |
L
| 10 |
Parameter/feature | Value/description |
---|---|
Path-loss model | NLOS urban scenario [IEEE 802.16] |
Carrier frequency | 2 GHz |
Base station height | 12.5 m |
Mobile terminal height | 1.5 m |
Noise power level | − 100 dBm |
Long-term fading model | Log-normal distribution |
Variance of the shadowing | 6 dB |
Short-term fading model | 3 GPP typical urban channel |
Acronym | Meaning |
---|---|
ACK | Acknowledgement |
αESM | Aggregated effective SNR mapping |
AMC | Adaptive modulation and coding |
ARQ | Automatic repeat request |
AWGN | Additive white Gaussian noise |
BIC | Bit-interleaved coded |
BICM | Bit-interleaved coded modulation |
BIOS | Binary input output symmetric |
BPSK | Binary phase shift keying |
CC | Chase combining |
CCDF | Complementary cumulative distribution function |
CMGF | Cumulant moment generating function |
CP | Cyclic prefix |
CRC | Cyclic redundancy check |
CSI | Channel state information |
DFT | Discrete Fourier transform |
EESNR | Exponential effective SNR |
EGP | Expected goodput |
ESM | Effective SNR mapping |
ESNR | Effective SNR |
GO | Goodput-oriented |
GP | Goodput |
HARQ | Hybrid automatic repeat request |
H-EESM | HARQ EESM |
H-MIESM | HARQ MIESM |
IR | Incremental redundancy |
LA | Link adaptation |
LLR | Log-likelihood ratio |
LPP | Link performance prediction |
MCS | Modulation and coding scheme |
MI | Mutual information |
MIESM | Mutual information based effective SNR |
MIMO | Multiple-input multiple-output |
MRC | Maximum ratio combining |
OFDM | Orthogonal frequency division multiplexing |
OFDMA | Orthogonal frequency division multiple access |
OP | Optimization problem |
PDS | Pairwise decoding score |
PDU | Protocol data unit |
PEP | Pairwise error probability |
PER | Packet error rate |
PR | Protocol round |
RLC | Radio link control |
RV | Random variable |
SISO | Single-input single-output |
SM | Spatial multiplexing |
SNR | Signal-to-noise ratio |
UE | User equipment |
UPD | Unsuccessful packet decoding |