1. Introduction
The classical space 
, originally formulated by Coifman and Rochberg in [
1], comprises all locally integrable functions 
h such that the following is written:
	  
      where the supremum runs over all cubes 
 and the following:
	  
    A significant characterization of 
 was established by Bennett in 1982 [
2], using the natural maximal operator in connection with the 
 space. Liu and Yang [
3] extended Bennett’s result [
2] to Gauss measure metric space. For a more comprehensive account of the research on the space 
, we refer the reader to Leckband [
4], Jiang [
5], Tang [
6], Yang [
7,
8] and the references therein [
9,
10,
11,
12,
13].
The problem of characterizing 
 under weaker integrability conditions can be traced back to Strömberg [
14]. Afterwards, the studies of [
15,
16,
17] further demonstrate the weak conditions of defining 
. More recently, assuming concavity of the function 
, Canto, Pérez and Rela in [
18] (Theorem 1.1) further researched the findings of [
15] by establishing minimal integrability conditions in terms of Luxemburg-type norms, specifically expressed as follows:
      Throughout these discussions, setting 
 for some 
 yields the equivalence 
.
Although the space 
 has been extensively investigated under minimal integrability assumptions, analogous results for 
 remain largely undeveloped. Motivated by this gap, the present work is devoted to establishing Luxemburg-type characterizations of 
 spaces under both convexity and concavity conditions. The Luxemburg norm, originating from the modular approach to Orlicz spaces, provides a classical yet versatile framework for studying generalized integrability conditions. For a recent application of the Luxemburg norm in approximation theory, we refer the reader to Costarelli and Vinti [
19].
Our aim is to identify the minimal integrability requirements for characterizing  via Luxemburg-type formulations. To this end, we begin by recalling several fundamental notions.
For a cube 
R, if 
:
 is a function and 
 is a locally integrable function on 
R, then the Luxemburg-type norm is given by the following:
      Moreover, we define the following
	  
Definition 1. Let φ:. The Luxemburg-type  space, denoted by , consists of the collection of all measurable functions h: such that the composition  is locally integrable over , and satisfies the following:where  is defined as in (2). If , then the Luxemburg-type space  coincides with the classical space .  We now recall the definitions of convex and concave functions. Let 
 and 
. If the following is true:
	  
      then 
:
 is the said convex function. If the following is true:
	  
      then 
:
 is said concave function.
Remark 1. Recall [20] (Remark 1.4), if : is convex satisfying  and , then we find that the inverse function  is well defined on , where  is given by (5). In addition, if  is concave and satisfies , then  is necessarily increasing on . Furthermore, when  is increasing and concave with , it follows from [15] (Remark 1.3) that for any , the following is calculated:  Definition 2. Let φ: be a given function, and  denote a space endowed with a quasi-metric d and a doubling measure η. Let  be defined as in (2). - (i) 
- The space  consists of all functions h satisfying the following: 
- (ii) 
- The space  includes all functions h for which  is locally integrable function on  and the following: 
 Definition 3. Let φ: be a function,  be defined as in (2) and ω be non-atomic measure. - (i) 
- The space  consists of all functions h for which the following is calculated: 
- (ii) 
- The space  includes all functions h for which  is locally integrable function on  and the following: 
 Definition 4. For any cube  centered at x with side length L, assume the existence of constants  for which the following is calculated:holds for . Then we assert that the measure ω is non-atomic.  The structure of the paper is organized as follows. 
Section 2 is devoted to Luxemburg norm characterizations of 
 in Theorems 1 and 2, where we establish the fundamental equivalence results in the Euclidean setting. 
Section 3 addresses Luxemburg norm characterizations of 
 in Theorem 3, extending the previous analysis to the space of homogeneous type. 
Section 4 presents Luxemburg norm characterization of 
 in Theorem 4, in which we further investigate the weighted framework under non-atomic measures. Finally, 
Section 5 provides a conclusion, where we summarize the main contributions.
In this paper, the following terminology and notation will be employed: Define . For subset , denote its complement by . The notation  indicates the existence of a constant  such that ; similarly,  means . We write  when both  and  hold.
  2. Luxemburg Norm Characterizations of ()
In this section, we present Theorems 1 and 2, which establishes the Luxemburg norm characterizations of 
. To proceed, we begin by recalling the John–Nirenberg-type inequality for the 
 space, as stated in [
9] (Lemma 2.1).
Lemma 1 ([
9])
. If , then, there exist constants  for which it holds that the following is true:for all ,  and , where  is as in (2). Lemma 2 ([
20])
. Let φ: be convex satisfying  and . Then, for any  and , calculate the following:where  is defined in (5). Theorem 1. Assume that φ: is a function with  and . Then the following hold.
- (i) 
- Suppose that φ is convex and  denotes the inverse of φ on  with the following:If there exists  satisfying the following:then the spaces  and  can be identified with equivalent norms. 
- (ii) 
- If φ is concave, then . Moreover, there exist constants  such that the following is calculated: 
 Proof.  Now, we first verify (i). Given any 
, we will verify the following:
		
        where 
 and 
 is defined in (
5). Observe that 
 for such 
C. We normalize 
. Denote by 
 the constant defined in (
2). For any cube 
, we calculate the following:
		
        Applying Lemma 2, we deduce the following:
		
        The inequality (
7) is thus derived by applying the supremum over all cubes 
Q.
Next, suppose 
. Our goal is to prove the following:
        A sufficient condition for (
8) is the existence of a constant 
 satisfying the following:
		
        To verify (
9), assume 
. Set 
, where 
 is as in (
6) and 
 is from Lemma 1. By Remark 1, 
 exists on 
, with 
 defined in (
5). Then, we calculate the following:
		
        From condition (
6), one has the following:
		
        Furthermore, since 
 is convex with 
, then, for any 
 and 
, calculated as follows:
		
        We define the following:
		
        Using this, together with the above inequalities (
10) and (
11), we derive the following:
		
        which establishes (
9). Then (
8) holds. Finally, combining (
7) and (
8) yields that 
 with equivalent norms. This implies that (i) holds.
We now proceed to prove (ii). Assume that 
:
 is increasing and concave with 
 and 
. Let 
 be defined as in (
2). From Remark 1, we find that 
 is increasing. Given a cube 
, applying Jensen’s inequality, we obtain, for constant 
, the following:
		
        From this and Definition 1, the following is assumed:
		
        Below, we only need to verify the converse inequality, written as follows:
		
        which directly follows from the following inequality
		
        Suppose that 
. Then the Luxemburg norm condition implies that, for any cube 
Q, the following is calculated:
		
        To prove (
12), we define the following:
		
        Since the finiteness of 
X is not guaranteed, for a large number 
t, we instead consider the following truncated quantity:
		
        Then, we have 
. From (
13), we know the following:
        therefore, if we take 
 applying the Calderón–Zygmund decomposition yields non-overlapping dyadic cubes 
 and constant 
 such that the following properties hold:
        
- (i)
- ; 
- (ii)
-  for a.e.; 
- (iii)
- . 
Regarding 
, by (ii) and the increasing property of 
, it follows that for 
, the following is valid:
		
        which implies the following:
Now, we consider 
. For any 
, according to (
3), (i) and (
13), we see the following:
        From this and the following
		
        the following is calculable:
		
        where the penultimate step used the definition of 
 and the last step used (iii).
Combining the above bounds for 
 and 
, we have the following:
		
        Taking the supremum over all intervals, we choose 
 and obtain that there exists a constant 
 such that we calculate the following:
		
        Finally, we let 
 and obtain (
12). So, we conclude that (ii) holds. This finishes the proof of Theorem 1.    □
 As application of Theorem 1, we give a related result as follows:
Theorem 2. Let  be a function with  and . If , then .
 Proof.  Assume that  is measurable function with  and . By analyzing the growth of  at infinity, we construct a polygonal function  such that  is concave and  for large values of s.
Specifically, for 
, define 
. For 
, the function 
 is defined as a polygonal curve composed of linear segments joining points of the form 
 and 
, with 
 chosen so that 
 is continuous, concave, and satisfies 
. As a consequence of this construction, the following is assumed:
        Then we only need to verify the following:
		
        To simplify the argument, let 
. Assume that 
 is defined as in (
2). For a fiven cube 
Q, we following the proof of (
12), if we claim the following:
		
        Then we repeat the argument of (
12) and obtain that (
14) holds. Moreover, we calculate the following:
		
        It remains to show (
15). Referring the proof of [
18] (pp. 10–11) and replacing 
 with 
, we conclude that (
15) holds. This end the proof of Theorem 2.    □
   3. Luxemburg Norm Characterization of 
In preparation for the proof of Theorem 3, this section first recalls some concepts about the space of homogeneous type (see [
21]) and two key Lemmas from [
18] (Lemmas 3.1 and 3.2).
Assume that 
 is a set and 
d is a quasi-metric, that is, 
d satisfies quasi-triangular inequality, written as follows:
      where 
 is a finite constant. For a measure 
 and a ball 
 with center 
 and radius 
, if there exists constant 
 independent of 
y and 
t such that we calculate the following:
	  
      then we say that 
 satisfies the doubling condition. Define 
 to be the smallest constant in the doubling condition, and let 
 denote the doubling dimension of 
. For any balls 
 with 
, we utilize the above doubling condition to derive the following:
      where 
 is a positive constant, 
 and 
 mean the radius of 
 and 
, respectively.
Assume that 
 is the set, 
d is a quasi-metric and 
 is a doubling measure. The space of homogeneous type is a triple 
. To simplify the concept, for a ball 
B, we fix 
 and define the following:
      and
Lemma 3. Assume that  is a family of balls whose radius are bounded. Then one can find a subcollection  consisting of mutually disjointed balls satisfying the following:  Lemma 4. Let  and B be a ball. There is a sufficiently large constant  for which any ball P whose center lies in B and satisfies the following:it holds that . Furthermore, choosing ϵ sufficiently small ensures that .  Theorem 3. Let φ: be a function satisfying  and . If φ is concave, then  with equivalent norms.
 Proof.  Proceeding as in the proof of Theorem 1, based on Remark 1, we have that 
 exist. Let 
 be defined as in (
2). For any ball 
B, by applying Jensen’s inequality, we deduce the following:
        which implies the following:
        Therefore, we establish the following reverse inequality:
		
        To prove this, we need to show the following:
		
        for all 
B balls. Assume that 
. Then, we define the following:
		
        To prove (
17), we define the following:
		
        We claim that 
X is finite. Assume that 
 is a parameter to be determined. We define this as follows:
		
        For any 
, we use Lebesgue differentiation theorem to derive that there exists 
 centered at 
x satisfying the following:
		
        So, we construct a family 
, where 
 satisfies (
19) and 
 for all other ball 
 satisfying (
19). Using Lemma 3, we obtain a maximal subfamily 
.
Further, when 
L is chosen sufficiently large and 
, we utilize Lemma 4 to derive 
 and the following:
		
        Moreover, we have the following:
		
        where 
 refers to a constant that depends solely on 
.
Now, we summarize the key features of  as follows:
        
- (i)
- For , and , we have ; 
- (ii)
- ; 
- (iii)
-  and ; 
- (iv)
- there exist constants  such that . 
To verify (
17), by 
, we write the following:
For term 
, by the definition of 
 and Remark 1, we obtain, for any 
, the following:
        which allows us to obtain the following:
Now, we consider 
. Based to 
, by (
3), (iii) and (
18), we have the following:
        where 
 refers to a constant that depends solely on 
. Combining properties (ii) and (iv), we estimate II as follows:
        where the third step used the definition of 
X and 
 is as in (iv).
Finally, utilizing the bounds for 
 and 
 together, we obtain the following:
        Taking the supremum over all intervals and choosing 
, we conclude that there exists constant 
 dependent of 
 such that we obtain the following:
This allows us to derive (
17). We finish the proof of Theorem 3.    □