A method for determining for the compression of an Higher Order Ambisonics, HOA, data frame representation comprising HOA data frames ( C ( k)) a lowest integer number β e of bits for representing, as an exponent to base two (2 e), non-differential gain values corresponding to total absolute amplitude changes, from a first HOA data frame up to a current HOA data frame, for channel signals in the current HOA data frame, wherein each channel signal in each HOA data frame comprises a group of sample values and wherein to each channel signal ( y 1 ( k - 2),..., y I ( k - 2)) of each one of the HOA data frames a differential gain value is assigned, wherein the differential gain value causes a change of amplitudes (15, 151) of first sample values of a channel signal in a current HOA data frame (( k - 2)) with respect to second sample values of a channel signal in a previous HOA data frame (( k - 3)), and wherein resulting gain adapted channel signals are encoded in an encoder, and wherein the HOA data frame representation was rendered in a spatial domain to O virtual loudspeaker signals w j ( t), wherein positions of the virtual loudspeakers are lying on a unit sphere and are targeted to be distributed uniformly on that unit sphere, said rendering being represented by a matrix multiplication w ( t) = ( Ψ) -1 · c ( t), wherein w ( t) is a vector containing all virtual loudspeaker signals, Ψ is a virtual loudspeaker positions mode matrix, and c ( t) is a vector of the corresponding HOA coefficient sequences of the HOA data frame representation, and wherein said HOA data frame representation ( C ( k)) was normalised such that ‖ w t ‖ ∞ = max 1 ≤ j ≤ O w j t ≤ 1 ∀ t, the method including: - forming the channel signals by: a) for representing predominant sound signals ( x ( t)) in the channel signals, multiplying a vector of HOA coefficient sequences c ( t) by a mixing matrix A, wherein mixing matrix A represents a linear combination of coefficient sequences of a normalised HOA data frame representation; b) for representing an ambient component c AMB ( t) in the channel signals, subtracting the predominant sound signals from the normalised HOA data frame representation ( C ( k)), and selecting at least part of the coefficient sequences of said ambient component c AMB ( t), wherein ∥ c AMB ( t)∥ 2 2 ≤ ∥ c ( t)∥ 2 2, and transforming a resulting minimum ambient component c AMB,MIN ( t) by computing w MIN t = Ψ MIN − 1 ⋅ c AMB, MIN t, wherein ‖ Ψ MIN − 1 ‖ 2 < 1 and Ψ MIN is a mode matrix for said minimum ambient component c AMB,MIN ( t); c) selecting part of the HOA coefficient sequences c ( t) that relate to coefficient sequences of the ambient HOA component to which a spatial transform is applied; - setting the integer number β e of bits to β e = log 2 ( log 2 ( K MAX. O)┐ + e MAX + 1)┐, wherein K MAX = max 1 ≤ N ≤ N MAX K N, Ω 1 N,..., Ω O N, N is the order, N MAX is a maximum order of interest, Ω 1 N,..., Ω O N are directions of said virtual loudspeakers, O = ( N + 1) 2 is the number of HOA coefficient sequences, and K is a ratio between the squared Euclidean norm ∥ Ψ ∥ 2 2 of a mode matrix Ψ with respect to said directions Ω 1 N,..., Ω O N and O, wherein e MAX > 0. - forming the channel signals by: a) for representing predominant sound signals ( x ( t)) in the channel signals, multiplying a vector of HOA coefficient sequences c ( t) by a mixing matrix A, wherein mixing matrix A represents a linear combination of coefficient sequences of a normalised HOA data frame representation; b) for representing an ambient component c AMB ( t) in the channel signals, subtracting the predominant sound signals from the normalised HOA data frame representation ( C ( k)), and selecting at least part of the coefficient sequences of said ambient component c AMB ( t), wherein ∥ c AMB ( t)∥ 2 2 ≤ ∥ c ( t)∥ 2 2, and transforming a resulting minimum ambient component c AMB,MIN ( t) by computing w MIN t = Ψ MIN − 1 ⋅ c AMB, MIN t, wherein ‖ Ψ MIN − 1 ‖ 2 < 1 and Ψ MIN is a mode matrix for said minimum ambient component c AMB,MIN ( t); c) selecting part of the HOA coefficient sequences c ( t) that relate to coefficient sequences of the ambient HOA component to which a spatial transform is applied; a) for representing predominant sound signals ( x ( t)) in the channel signals, multiplying a vector of HOA coefficient sequences c ( t) by a mixing matrix A, wherein mixing matrix A represents a linear combination of coefficient sequences of a normalised HOA data frame representation; b) for representing an ambient component c AMB ( t) in the channel signals, subtracting the predominant sound signals from the normalised HOA data frame representation ( C ( k)), and selecting at least part of the coefficient sequences of said ambient component c AMB ( t), wherein ∥ c AMB ( t)∥ 2 2 ≤ ∥ c ( t)∥ 2 2, and transforming a resulting minimum ambient component c AMB,MIN ( t) by computing w MIN t = Ψ MIN − 1 ⋅ c AMB, MIN t, wherein ‖ Ψ MIN − 1 ‖ 2 < 1 and Ψ MIN is a mode matrix for said minimum ambient component c AMB,MIN ( t); c) selecting part of the HOA coefficient sequences c ( t) that relate to coefficient sequences of the ambient HOA component to which a spatial transform is applied; - setting the integer number β e of bits to β e = log 2 ( log 2 ( K MAX. O)┐ + e MAX + 1)┐, wherein K MAX = max 1 ≤ N ≤ N MAX K N, Ω 1 N,..., Ω O N, N is the order, N MAX is a maximum order of interest, Ω 1 N,..., Ω O N are directions of said virtual loudspeakers, O = ( N + 1) 2 is the number of HOA coefficient sequences, and K is a ratio between the squared Euclidean norm ∥ Ψ ∥ 2 2 of a mode matrix Ψ with respect to said directions Ω 1 N,..., Ω O N and O, wherein e MAX > 0.