ofdm_siso.m File Reference

Functions
Scale for Tx	waveform ([0:1]) else nt
Theoretical BER	fprintf ("Channel type: %s \n", chan_type)
Modulation	order (2/4/16/64=BSPK/QPSK/16-QAM/64-QAM) % OFDM params SC_IND_PILOTS
Number of data	symbols (one per data-bearing subcarrier per OFDM symbol) N_LTS_SYM
id	FFT_OFFSET ()
Number of CP samples to use in	FFT (on average) DO_APPLY_PHASE_ERR_CORRECTION
other subcarriers will remain at	fdd_mat (SC_IND_DATA, :)
	fdd_mat (SC_IND_PILOTS, :)
1, N_ZPAD_POST	zeros ()
abs(tx_vec_iris	max ()
	ue_ids (end+1)
	sdr_params (2)
id	a ()

Variables
Author(s) close	all
if ~isloaded pyversion usr bin python py print() %weird bug where py isn 't loaded in an external script end % Params Enable writing plots to PNG	CHANNEL = 11
Channel to tune Tx and Rx radios	SIM_MOD = 1
if SIM_MOD	chan_type = "rayleigh"
	nt = 100
	sim_SNR_db = 1:20
	nsnr = length(sim_SNR_db)
	snr_plot = 20
	TX_SCALE = 1
end	ber_SIM = zeros(nt,nsnr)
BER	berr_th = zeros(nsnr,1)
Iris	params
	N_UE = 1
	TX_FRQ = 2.5e9
	RX_FRQ = TX_FRQ
	TX_GN = 43
	RX_GN = 20
	SMPL_RT = 5e6
	N_FRM = 10
	b_ids = string.empty()
	b_scheds = string.empty()
	ue_ids = string.empty()
	ue_scheds = string.empty()
Waveform params	N_OFDM_SYM = 46
Number of OFDM symbols for	burst
Number of OFDM symbols for it needs to be less than	MOD_ORDER = 16
Pilot subcarrier indices	SC_IND_DATA = [2:7 9:21 23:27 39:43 45:57 59:64]
Data subcarrier indices	N_SC = 64
Number of subcarriers	CP_LEN = 16
Cyclic prefix length	N_DATA_SYMS = N_OFDM_SYM * length(SC_IND_DATA)
Number of	N_SYM_SAMP = N_SC + CP_LEN
Number of samples that will go over the air	N_ZPAD_PRE = 90
Enable Residual CFO estimation correction Define the preamble LTS for fine CFO and channel estimation	lts_f
	lts_t = ifft(lts_f, 64)
time domain	preamble = [lts_t(33:64) lts_t lts_t]
Generate a payload of random integers	tx_data = randi(MOD_ORDER, 1, N_DATA_SYMS) - 1
	tx_syms = mod_sym(tx_data, MOD_ORDER)
Reshape the symbol vector to a matrix with one column per OFDM symbol	tx_syms_mat = reshape(tx_syms, length(SC_IND_DATA), N_OFDM_SYM)
Define the pilot tone values as BPSK symbols	pilots = [1 1 -1 1].'
Repeat the pilots across all OFDM symbols	pilots_mat = repmat(pilots, 1, N_OFDM_SYM)
Time Domain Do	yourselves
Insert the data and pilot	values
Do Insert the cyclic prefix if(CP_LEN > 0) % Do yourselves	tdd_tx_payload_mat = [tx_cp
end Reshape to a vector	tx_payload_vec = reshape(tdd_tx_payload_mat, 1, numel(tdd_tx_payload_mat))
Leftover from zero	padding
for	isnr
	rx_vec_iris = rx_vec_iris.'
just to agree with what the hardware spits out else Init Iris nodes Set up the Iris experiment Create two Iris node	objects
	b_prim_sched = "PGGGGGRG"
BS primary noede s	schedule
for	iu
end	n_samp = length(tx_vec_iris)
Iris nodes parameters	sdr_params
	l_rx_dec =length(rx_vec_iris)

Function Documentation

a()

id a ( )

virtual

fdd_mat() [1/2]

other subcarriers will remain at fdd_mat	(	SC_IND_DATA	,
		:
	)

fdd_mat() [2/2]

fdd_mat	(	SC_IND_PILOTS	,
		:
	)

FFT()

Number of CP samples to use in FFT

(

on

average

)

FFT_OFFSET()

id FFT_OFFSET ( )

virtual

fprintf()

Theoretical BER fprintf	(	"Channel type: %s \n"	,
		chan_type
	)

max()

abs(tx_vec_iris max ( )

staticvirtual

order()

Modulation order

(

2/4/16/

64 = BSPK/QPSK/16-QAM/64-QAM

)

sdr_params()

sdr_params

(

2

)

symbols()

Number of data symbols

(

one per data-bearing subcarrier per OFDM

symbol

)

ue_ids()

ue_ids

(

end+

1

)

waveform()

Scale for Tx waveform

(

)

zeros()

1,N_ZPAD_POST zeros ( )

virtual

Variable Documentation

all

Author (s) close all

b_ids

b_ids = string.empty()

b_prim_sched

b_prim_sched = "PGGGGGRG"

b_scheds

UE schedule b_scheds = string.empty()

ber_SIM

end ber_SIM = zeros(nt,nsnr)

berr_th

BER berr_th = zeros(nsnr,1)

burst

Number of OFDM symbols for burst

chan_type

if SIM_MOD chan_type = "rayleigh"

CHANNEL

if ~isloaded pyversion usr bin python py print () %weird bug where py isn't loaded in an external script end % Params Enable writing plots to PNG CHANNEL = 11

CP_LEN

Number of subcarriers CP_LEN = 16

isnr

for isnr

Initial value:

= 1:nsnr
    for it = 1:nt
if (SIM_MOD)        
    rx_vec_iris = getRxVec(tx_vec_iris, N_BS_NODE, N_UE, chan_type, sim_SNR_db(isnr))

iu

for iu

Initial value:

= 1:N_UE
        ue_scheds(iu,:) = ue_sched

l_rx_dec

l_rx_dec =length(rx_vec_iris)

lts_f

Enable Residual CFO estimation correction Define the preamble LTS for fine CFO and channel estimation lts_f

Initial value:

= [0 1 -1 -1 1 1 -1 1 -1 1 -1 -1 -1 -1 -1 1 1 -1 -1 1 -1 1 -1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 ...
    1 1 -1 -1 1 1 -1 1 -1 1 1 1 1 1 1 -1 -1 1 1 -1 1 -1 1 1 1 1]

lts_t

lts_t = ifft(lts_f, 64)

MOD_ORDER

Number of OFDM symbols for it needs to be less than MOD_ORDER = 16

N_DATA_SYMS

Cyclic prefix length N_DATA_SYMS = N_OFDM_SYM * length(SC_IND_DATA)

N_FRM

N_FRM = 10

N_OFDM_SYM

Time Domain Do N_OFDM_SYM = 46

n_samp

end n_samp = length(tx_vec_iris)

N_SC

Do N_SC = 64

N_SYM_SAMP

Number of N_SYM_SAMP = N_SC + CP_LEN

N_UE

N_UE = 1

N_ZPAD_PRE

Number of samples that will go over the air N_ZPAD_PRE = 90

nsnr

nsnr = length(sim_SNR_db)

nt

nt = 100

objects

just to agree with what the hardware spits out else Init Iris nodes Set up the Iris experiment Create two Iris node objects

padding

Leftover from zero padding

params

Iris params

pilots

Define the pilot tone values as BPSK symbols pilots = [1 1 -1 1].'

pilots_mat

Repeat the pilots across all OFDM symbols pilots_mat = repmat(pilots, 1, N_OFDM_SYM)

preamble

time domain preamble = [lts_t(33:64) lts_t lts_t]

RX_FRQ

RX_FRQ = TX_FRQ

RX_GN

RX_GN = 20

rx_vec_iris

end rx_vec_iris = rx_vec_iris.'

SC_IND_DATA

Pilot subcarrier indices SC_IND_DATA = [2:7 9:21 23:27 39:43 45:57 59:64]

schedule

BS primary noede s schedule

sdr_params

Iris nodes parameters sdr_params

Initial value:

= struct(...
        'id', b_ids, ...
        'n_chain',N_BS_NODE, ...
        'txfreq', TX_FRQ, ...
        'rxfreq', RX_FRQ, ...
        'txgain', TX_GN, ...
        'rxgain', RX_GN, ...
        'sample_rate', SMPL_RT, ...
        'n_samp', n_samp, ...          % number of samples per frame time.
        'n_frame', N_FRM, ...
        'tdd_sched', b_scheds, ...     % number of zero-paddes samples
        'n_zpad_samp', (N_ZPAD_PRE + N_ZPAD_POST) ...
        )

SIM_MOD

Channel to tune Tx and Rx radios SIM_MOD = 1

sim_SNR_db

sim_SNR_db = 1:20

SMPL_RT

SMPL_RT = 5e6

snr_plot

snr_plot = 20

tdd_tx_payload_mat

tdd_tx_payload_mat = [tx_cp

tx_data

Generate a payload of random integers tx_data = randi(MOD_ORDER, 1, N_DATA_SYMS) - 1

TX_FRQ

TX_FRQ = 2.5e9

TX_GN

TX_GN = 43

tx_payload_vec

end Reshape to a vector tx_payload_vec = reshape(tdd_tx_payload_mat, 1, numel(tdd_tx_payload_mat))

TX_SCALE

TX_SCALE = 1

tx_syms

tx_syms = mod_sym(tx_data, MOD_ORDER)

tx_syms_mat

Reshape the symbol vector to a matrix with one column per OFDM symbol tx_syms_mat = reshape(tx_syms, length(SC_IND_DATA), N_OFDM_SYM)

ue_ids

ue_ids = string.empty()

ue_scheds

ue_scheds = string.empty()

values

Insert the data and pilot values

yourselves

Do yourselves