Proposed workaround for known issue. UMa scenario: h_E uses continuous instead of discrete uniform

[JamieAGP]

sionna/src/sionna/phy/channel/tr38901/uma_scenario.py

Lines 240 to 253 in 20d2bca

	max_value = h_ut- 1.5
	# Random uniform integer generation is not supported when maxval and
	# are not scalar. The following commented would therefore not work.
	# Therefore, for now, we just sample from a continuous
	# distribution.
	#delta = tf.cast(tf.math.floor((max_value-min_value)/3.), tf.int32)
	#s = tf_rng.uniform(shape=[batch_size, num_bs, num_ut],
	# minval=0, maxval=delta+1, dtype=tf.int32)
	#s = tf.cast(s, tf.float32)*3.+min_value
	s = config.tf_rng.uniform(shape=[batch_size, num_bs, num_ut],
	minval=12., maxval=max_value, dtype=self.rdtype)
	# Itc could happen that h_ut = 13m, and therefore max_value < 13m
	s = tf.where(tf.math.less(s, 12.0),
	tf.constant(12.0, self.rdtype), s)

Table 7.4.1-1 NOTE 1: "For UMa h_E=1m with a probability equal to 1/(1+C(d_2D, h_UT)) and chosen from a discrete uniform distribution uniform(12,15,…,(h_UT-1.5)) otherwise."

Code left as continuous distribution for commented reasons. However, I propose a workaround by sampling [0,1] continuously and scale to discrete index.

Example: h_UT = 22.5m, max_value = h_UT - 1.5 = 21.0m

1. Calculate number of valid discrete values`: values = {12, 15, 18, 21}, n = 4 valid values
2. Sample uniform [0,1): u = uniform(0, 1) e.g = 0.73
3. Convert to discrete index: idx = floor(u * n )= floor(0.73 * 4) = floor(2.92) = 2.0
4. Convert index to value: values[idx] = values[2] = 18.0

max_value = h_ut - 1.5
# Sample from discrete uniform {12, 15, 18, ..., max_valid} per TR 38.901 Table 7.4.1-1 Note 1
# Workaround: sample U(0,1) with scalar bounds, then scale to discrete index
n_values = tf.maximum(tf.floor((max_value - 12.0) / 3.0) + 1.0, 1.0)
u = config.tf_rng.uniform(shape=[batch_size, num_bs, num_ut],
                          minval=0, maxval=1, dtype=self.rdtype)
s = 12.0 + 3.0 * tf.floor(u * n_values)
# Handle edge case: when h_ut <= 13.5m, max_value <= 12m, only valid value is 12
s = tf.where(tf.math.less(max_value, 12.0),
    tf.constant(12.0, self.rdtype), s)