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Soft-in/ Soft-out Noncoherent Sequence Detection for Bluetooth: Capacity, Error Rate and Throughput Analysis. Rohit Iyer Seshadri and Matthew C. Valenti Lane Dept. of Computer Science and Electrical Engineering West Virginia University iyerr, mvalenti @csee.wvu.edu. Objectives.

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Soft-in/ Soft-out Noncoherent SequenceDetection for Bluetooth:Capacity, Error Rate and Throughput Analysis

Rohit Iyer Seshadri and Matthew C. Valenti

Lane Dept. of Computer Science and Electrical Engineering

West Virginia University

iyerr, mvalenti @csee.wvu.edu

objectives
Objectives
  • Achieve dramatic improvements in energy efficiency and throughput for Bluetooth with a minimal increase in complexity by using:
    • Sequence based, noncoherent demodulator
    • Bit-interleaving
    • Soft-decision decoding
    • Feedback from channel decoder to demodulator
  • Obtain an information theoretic bound on the minimum signal to noise ratio required for reliable signaling
    • Bit-wise log-likelihood ratios used to compute Shannon capacity under modulation, channel and receiver design constraints
  • Demonstrate performance improvements over popular receivers using an extensive simulation campaign
    • Evaluate packet error rate (PER) and throughput performance for data medium (DM) - rate packet types

SISO-Noncoherent Sequence Detection for Bluetooth

bluetooth
Bluetooth
  • Low cost/ low power connectivity for wireless personal area networks
  • Operates in the license free 2.4 GHz ISM band
  • Band divided into 79 channels, each 1 MHz wide. Channels changed up to 1600 times per second
  • Channel symbol rate of 1 Mbps
  • Uses Gaussian frequency shift keying (GFSK)
    • M =2
    • BgT =0.5
    • 0.28 ≤h ≤0.35

SISO-Noncoherent Sequence Detection for Bluetooth

benchmark bluetooth system
Benchmark Bluetooth System

Encoder: (15, 10) Shortened Hamming Code (SHC), single error correction code

Baseband GFSK signal during kT≤ t ≤ (k+1)T

GFSK phase

Detector: Limiter discriminator integrator (LDI)

SISO-Noncoherent Sequence Detection for Bluetooth

bluetooth system with sequence detection
Bluetooth System with Sequence Detection

GFSK pulse shape causes adjacent symbol interference

Detector: Soft-Decision differential phase detector with

Viterbi decoding (SDDPD-VD), [Fonseka, 2001]

Viterbi decoding can produce burst errors, which could be mitigated by bit-interleaving

SISO-Noncoherent Sequence Detection for Bluetooth

bluetooth system with siso sddpd
Bluetooth System with SISO-SDDPD

SDDPD-VD forms hard estimates on code bits

SISO-SDDPD generates bit-wise LLRs for the code bits

LLRs from detector passed to decoder, which performs soft-decision decoding

Bit-interleaved coded modulation (BICM)

Additionally, soft-information can be also be fed from decoder to detector: BICM with iterative decoding (BICM-ID)

No gains over BICM

Behavior explained using EXIT curves

SISO-Noncoherent Sequence Detection for Bluetooth

siso soft decision differential phase detection
SISO-Soft-Decision Differential Phase Detection
  • Received signal at the output of a frequency nonselective, Rician channel, before filtering

r’(t, a) = c(t) x(t, a) + n’(t)

  • Received signal after filtering

r(t, a) = c(t) x(t, a) + n(t)

  • Received signal phase

(t, a) =

(t, a) +

SISO-Noncoherent Sequence Detection for Bluetooth

siso soft decision differential phase detection8
SISO-Soft-Decision Differential Phase Detection
  • Detector finds the phase difference between successive symbol intervals
  • The GFSK pulse shape causes adjacent symbol interference
  • The phase difference space from 0 to 2 is divided into R sub-regions
  • Detector selects the sub-region Dk in which lies
  • The sequence of phase regions (D0, DI, …) is sent to a branch metric calculator

SISO-Noncoherent Sequence Detection for Bluetooth

siso soft decision differential phase detection9
SISO-Soft-Decision Differential Phase Detection
  • Let be the phase differences corresponding to any transmitted sequence
  • A branch metric calculator finds the conditional probabilities
  • Branch metrics sent to a 4-state MAP decoder whose state transition is from

to

  • The SISO-SDDPD estimates the LLR zk for ak as

SISO-Noncoherent Sequence Detection for Bluetooth

fec for bluetooth
FEC for Bluetooth
  • Bluetooth specifies 7 types of ACL packets for data transfer
  • 6 out of the 7 packet types use cyclic redundancy check (CRC) and ARQ
  • 3 out of these 6, i.e. data medium (DM1, DM3, DM5) also use a (15, 10) shortened Hamming code (SHC) for forward error correction (FEC)
  • The (15, 10) SHC is cyclic and described by the generator polynomial
  • The cyclic code can hence be expressed using a 25= 32 state trellis and decoded by running either a Viterbi or MAP algorithm over the trellis

SISO-Noncoherent Sequence Detection for Bluetooth

capacity under modulation channel and receiver design constraints
Capacity Under Modulation, Channel And Receiver Design Constraints
  • Channel capacity denotes maximum allowable data rate for reliable communication over noisy channels
  • In any practical system, the input distribution is constrained by the choice of modulation
    • Capacity is mutual information between the bit at modulator input and LLR at detector output
  • Constrained capacity in nats is; [Caire, 1998]

SISO-Noncoherent Sequence Detection for Bluetooth

capacity under modulation channel and receiver design constraints12
Capacity Under Modulation, Channel And Receiver Design Constraints
  • Constrained capacity for the proposed system is now
  • In bits per channel use
  • Constrained capacity hence influenced by
    • Modulation parameters (M, h and BgT)
    • Channel
    • Detector design
  • Computed using Monte-Carlo simulations

SISO-Noncoherent Sequence Detection for Bluetooth

performance evaluation and comparisons
Performance Evaluation and Comparisons
  • Performance of proposed SISO-SDDPD with BICM compared against
    • Limiter discriminator integrator detector with hard decision channel decoding, with and without bit-interleaving: LDI-HDD
    • SDDPD-VD, followed by hard decision channel decoding, with and without bit-interleaving: SDDPD-HDD
    • SISO-SDDPD followed by soft decision channel decoding, without bit-interleaving: SISO-SDDPD-SDD
  • Comparisons made on the basis of
    • Bit error rate
    • Packet error rate
    • Throughput

SISO-Noncoherent Sequence Detection for Bluetooth

bit error rate comparison
Bit Error Rate Comparison

Scenario:

Minimum Eb/No to achieve BER= 10-4. Six simulated points from top to bottom are

1) LDI-HDD

2) LDI-HDD with interleaving

3) SDDPD-HDD

4) SDDPD-HDD with interleaving

5) SISO-SDDPD-SDD

6) SISO-SDDPD with BICM

Information theoretic bound for SISO-SDDPD based BICM

SDDPD specifications:

R=24 uniform sub-regions

Channel parameters:

Nonselective, Rician fading, K =2 dB

Bluetooth specifications:

h =0.315,

DM1 packet types

SISO-SDDPD with BICM gives the best BER performance

SISO-Noncoherent Sequence Detection for Bluetooth

packet error rate comparison
Packet Error Rate Comparison

Scenario:

Packet error rate for DM1 packet types.

SDDPD specifications:

R=24 uniform sub-regions

Channel parameters:

Nonselective, Rician fading, K =2 dB

Bluetooth specifications:

h =0.315

DM1 packet types

SISO-SDDPD with BICM gives the best packet error rate performance.

Gain over LDI based systems = 9 dB

Gain over SDDPD-HDD based systems =4 dB

SISO-Noncoherent Sequence Detection for Bluetooth

throughput comparison
Throughput Comparison

Scenario:

Throughput for DM1, DM3 and DM5 packet types

Solid curve: Systems without interleaving

Dotted curve: Systems with interleaving

SDDPD specifications:

R=24 uniform sub-regions

Channel parameters:

Nonselective, Rician fading, K =2 dB

Bluetooth specifications:

h =0.315

SISO-SDDPD with BICM gives the best throughput performance

For maximal throughput, packet type should be adaptively selected to match SNR

SISO-Noncoherent Sequence Detection for Bluetooth

conclusions
Conclusions
  • An energy efficient, noncoherent receiver design investigated for Bluetooth
    • Soft-in/ soft-out, soft decision differential phase detector developed
    • BICM paradigm applied to Bluetooth
  • Error rate and throughput compared against LDI detector and Fonseka’s SDDPD with Viterbi decoding
    • SISO-SDDPD-SDD shown to outperform LDI-HDD and SDDPD-HDD
    • Additional gains possible with interleaving
  • Constrained capacity found using Monte Carlo simulations

SISO-Noncoherent Sequence Detection for Bluetooth

future work
Future Work
  • An algorithm that designs nonuniform phase regions using received phase differences and adapts itself to varying channel conditions and GFSK parameters
    • Nonunifrom regions can perform better than uniformly phase regions [Fonseka, 1999]
    • Results in a smaller look-up table
  • Estimating the Rician K factor and Eb/No at the receiver using the Expectation-Maximization algorithm

SISO-Noncoherent Sequence Detection for Bluetooth

complexity
Complexity
  • Branch metric calculations in SISO-SDDPD
    • Metric calculations involve nonlinear functions
    • Pre-calculated and stored in a look-up table
    • Table needs to be updated once at each Eb/No
  • Number of states in the detector
    • SISO-SDDPD operates on a M2- state trellis
  • Number for states in the channel decoder, with soft-decision decoding
    • ML/ MAP decoding performed on a 32- state trellis

SISO-Noncoherent Sequence Detection for Bluetooth

sensitivity to h estimation errors
Sensitivity to h estimation errors

Scenario:

Effect of incorrect estimates of h on SISO-SDDPD and LDI detectors

SDDPD specifications:

R=24 uniform sub-regions

Channel parameters:

Nonselective, Rician fading, K =2 dB

Bluetooth specifications:

Correct value of h =0.315

Values assumed at detector =0.28, 0.35

DM1 packet types

SISO-SDDPD more robust to incorrect estimates of h

SISO-Noncoherent Sequence Detection for Bluetooth

exit chart
EXIT Chart

Scenario:

EXIT chart for the SISO-SDDPD based BICM receiver

SD-DPD specifications:

R=24 uniform sub-regions

Channel parameters:

Nonselective, Rician fading, K =2 dB

Bluetooth specifications:

h =0.315, BgT =0.5

Detector EXIT curve predicts no improvement with BICM-ID

SISO-Noncoherent Sequence Detection for Bluetooth

throughput calculations
Throughput Calculations
  • Throughput: Maximum achievable, one way data rate [Valenti, 2002]

Nt: Total number of times a given packet must be transmitted (on an average) until it is successfully decoded

Ns: Number of slots occupied per round trip, including one return slot

Duration of each slot: 625 µsec

Ku: Number of data bits in the packet type

SISO-Noncoherent Sequence Detection for Bluetooth